Factors Blog

If you still spend time randomly sending emails to prospects in your account list with a generic pitch slap, you’re selling wrong. An effective sales strategy is all about driving consideration for high-intent prospects at the right time with the right pitch, whether they’ve just signed up, completed a demo, or are suddenly showing interest in your product again. 

However, the major hurdle is the tedious process of manually finding contact data, syncing CRMs, and personalizing emails for every prospect on the list. 

Enter: Automation. 

A sales automation workflow helps busy sales teams turn prospects into pipeline by streamlining business processes and ensuring that you reach out to prospects promptly. 

In this article, we explain the different types of automation workflows we can create for your sales teams ⬇️

Creating sales automation workflows using Factors: Case Study 

At Factors, we create custom workflows for customers to simplify data transfer so that their sales teams can effectively act on the data. For this, we make these signals available in the format that the salesperson needs in the tool of their choice. Here’s an example of a workflow we set up for a CreativeOps company

This workflow demonstrates the process of transferring Factors data to create a contact in HubSpot, which is then pushed to Apollo to be added to their email sequences. 

The Problem

Our customer wanted to ensure their salespeople could promptly act on these signals to build pipeline. Since they used HubSpot and Apollo, they requested a custom workflow that could sync new leads from the accounts that Factors identified on their website and organize this data in a specific way such that all accounts received personalized emails based on the deal stage. For example, if 50 companies visit the customer’s website, they want to automate the process of identifying their leads from each account and adding them to their outreach sequences. To accomplish this, we built a custom workflow with 4 different criteria to streamline their outbound efforts.

The Solution

We used webhooks and make.com to create multiple workflows for the following scenarios:

1. The account identified is a new company
2. The account is an existing company in the CRM that was identified as “closed lost.”
3. Existing company in the CRM but with no deal associated 
4. The contact doesn’t exist in the CRM 

💡Learn more about using Webhooks with Make.com

Here’s a detailed explanation of how each of the above workflows operates:

1. The account identified is a new company

The first branch involves identifying the new account and creating a new company on HubSpot. While Factors cannot identify user-level data due to privacy concerns, we can potentially identify the leads associated with the account via job titles.

The brand has included 25 job titles under its ICP, so now, our customer can automatically identify relevant contact data via Apollo, add the email IDs to their CRM, and send out outreach emails based on their website activity (e.g., visited paid landing page, pricing page, etc.). 

💡Factors allows you to send personalized outreach emails to your prospects based on how they engage with your brand. 

2. The account is an existing company in the CRM 

We set up this workflow branch to identify leads who visited the website after getting marked as “closed lost” on Hubspot. Here’s how you can set up the filter on Make.com: 

The customer wanted to re-engage with closed, lost accounts older than 90 days. In this case, we again re-route to Apollo to identify and add potentially new leads associated with the account to an email sequence. The workflow also automatically adds the existing contacts from Hubspot to the sequence. 

3. Existing company in the CRM but with no deal associated

This part of the workflow follows a similar process to the one mentioned above, with the only difference being that we automate contact creation on HubSpot as an additional step.

4. No contact exists in their CRM

We set up a filter to identify accounts that visit the company’s website but aren’t associated with any contacts in HubSpot.

In this case, we automate identifying leads via Apollo and update contacts on HubSpot before pushing them to an email sequence. 

The Result

Our workflows simplified their outbound process. Instead of manually identifying accounts by deal stage and writing out emails, they could effortlessly send personalized email sequences automatically via Apollo while simultaneously identifying and updating new leads within their CRM. 

Build stellar workflow automations with Factors

Every company's sales team operates differently and has multiple tools in its tech stack. Instead of having your account data in messy and disparate systems, it’s critical to have a custom workflow that saves you the time and effort spent on sales outreach. 

Factors’ sales automation workflows are a boon for busy sales teams who want to skip tedious tasks and focus on generating revenue for the company. We create customized workflows that integrate with the right tools and use your data to its maximum potential. Speak to our team today to understand how you can automate your business processes with Factors.

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Imagine working hard for months to close the deal with a prospect, only for them to churn in less than a year. There could be several reasons, such as:

• Poor customer service
• Choosing a competitor's solution 
• Users not achieving their KPIs

Reducing customer churn is vital for businesses because it ensures customer satisfaction and boosts profitability. The best way to avoid high churn rates is to predetermine the customers at a churn risk. 

In this article, we'll detail how customer churn prediction is the key to reducing churn and keeping the cash flowing in 💸

What is Customer Churn Prediction?

Customer churn prediction involves analyzing data to detect customers likely to cancel subscriptions. SaaS businesses use this analysis to identify at-risk customers, leading to cost savings and improved customer lifetime value.

Analyzing churn through data-driven insights can help your business understand patterns and provide a roadmap for improvement. For example, if your surveys reveal that your platform has a complicated onboarding process – you can direct users to your onboarding specialist to assist them.

Why is Customer Churn Prediction important?

Losing customers is always costly. However, the costs involved go beyond the revenue lost from the customers who leave. It also includes the marketing expenses required to find new customers to replace the old ones. In many cases, the amount spent on acquiring a new customer is not covered by the amount paid during their time with the company. This means that customer acquisition is usually more expensive than customer retention.

Plus, unhappy customers share their experiences with others, impacting the company's reputation and customer acquisition budget. Businesses must predict churn and take action beforehand to prevent customers from leaving. 

Once you know a customer is going to churn, you can take actions such as:

• Providing more targeted re-engagement campaigns
• Launching incentives such as loyalty programs that encourage them to stay 
• Creating educational material that is tailored toward their specific needs
• Ensuring accessible and improved customer support 

How to Build a Customer Churn Prediction Model

Creating a churn prediction model can help businesses retain customers and sustain growth. Using data analytics and machine learning, companies can identify which customers are likely to leave and take action to prevent it. 

Here are the key steps to develop an effective churn prediction model ⬇️

1. Data collection and review

Ensure that the data is accurate by handling missing values, removing duplicates, and converting it into a suitable format for analysis. Before moving on to calculations, reviewing the data for accuracy and validity is crucial. Every piece of customer info is valuable in the upcoming churn calculations, so it's worth ensuring accuracy.

2. Model selection

Select an appropriate machine learning algorithm for churn prediction, such as logistic regression, decision trees, random forests, or gradient boosting machines. Split the data into training and testing sets, train the model, and tune hyperparameters to optimize performance. Evaluate the model using testing data and cross-validation. Deploy the model into production to make real-time predictions and prevent churn.

3. Use an automated predictive model

Do people with lower NPS scores tend to leave more? Are they evaluating competitor solutions? You can predict who might leave by spotting these signs in the data. You must use machine learning with a dataset containing all the information you have about customers who stayed and those who left. The algorithm learns from this historical data to understand how different factors relate to churn. Then, it can predict if future customers with similar behaviors might leave or stay.

💡Factors can help you identify customers evaluating competitor solutions by helping you track when they visit their G2 pages. 

4. Establish retention strategy

Optimize your retention strategy by prioritizing actions based on the probability of customer churn. When customers first sign up, use checklists and personalized help to ensure they understand and use the product. As they keep using it, watch out for signs they might leave. For instance, if they're not using a feature they need, you can send them helpful tips to get them back on track.

5. Track results regularly 

Continuously monitor the churn prediction model's performance and update it with new data periodically to ensure it remains effective as customer behavior evolves. Before introducing any further changes to your plan, collect enough data to measure the real impact of your efforts.

Your churn model will provide probabilities for various customer segments. It's essential to keep testing new strategies and recording the impact on these segments. While creating a mathematical model of churn requires time and resources from your team, each test can help you create a better model for the future. 

6 Customer churn prediction best practices

Now that you know how to build a churn prediction model, here are a few handy tips you must remember to prevent customer churn:

1. Segment Customers

After obtaining your data, it's time to shift your focus towards the users and begin segmenting them. Since users have distinct needs and usage patterns, they don't churn for the same reason. Hence, it's essential to categorize them into separate segments. You can segment them based on their:

• Demographics, such as location, region, company size, and the year they signed up for your company.
• Behavior and usage, such as how often they log in, whether they use a particular feature more or less, or whether they have completed the onboarding process.
• Contract terms include pricing plans and whether customers signed up for a monthly, quarterly, or yearly deal.

You can design retention strategies and marketing campaigns tailored to specific customer segments by segmenting customers based on their churn likelihood and characteristics. Domain knowledge or clustering techniques can help you define meaningful segments.

2. Monitor product usage data of existing customers

Product usage data captures how and when customers use your software. Important data points include feature usage, customer behavior, clicks, and other metrics such as time-to-value and product stickiness.

To build an effective model, it's important to consider some key product usage data points such as:

• Monitor feature usage data to show users' engagement with your product's features, indicating popularity and relevance.
• Observe users’ actions within your product, like when they use it, how long they use it, which features they engage with, and how they progress through it.
• Track the number of times a user clicks or interacts with a UI element, such as a button, checkbox, text area, or menu.
• Track other product usage data such as time-to-value, product stickiness, interactions, and more.

3. Keep an eye on customer success metrics

Understanding your users' success with your product is crucial in determining if they will continue using it. Surveys such as NPS and CSAT can be used to measure customer success. An NPS score of less than 7 or 8 means you may need a win-back campaign or value incentive to change their attitude towards your product. NPS measures loyalty and willingness to recommend, while CSAT measures customer satisfaction. Conduct these surveys periodically to track customer success and satisfaction.

4. Gather customer feedback regularly

Apart from gathering feedback through conventional ways, you can use various other forms of customer feedback to gain insights into their experience with your product or service. For example, in-app surveys can provide you with contextual input from users. You can use them to find out about your customer's overall satisfaction with your product, their experience with a particular feature, any issues they may have faced, or even the features they would like you to add or implement. This can be very helpful in understanding the general sentiment of users and identifying areas of improvement or strengths.

To promptly address issues and demonstrate responsiveness to user input, incorporate real-time feedback loops within your product. Acknowledge the feedback received through in-app surveys and communicate any actions taken to address user concerns.

5. Enhance customer experience

You can streamline the customer experience using automated onboarding, self-service options, and personalized support. Furthermore, you should use customer feedback to identify areas of improvement and proactively address any customer dissatisfaction rather than reacting after the fact.

6. Improve customer service

Respond promptly to inquiries and complaints, offer helpful advice, and measure performance using metrics like support tickets, call center response times, and social media interactions. Monitor these metrics to gain insights into customer service trends and effectiveness.

Customer Churn Prediction: Key Steps & Benefits

Predicting customer churn helps businesses retain clients and reduce acquisition costs through data-driven strategies.

1. Key Steps in Churn Prediction: Data collection, feature selection, model selection (Logistic Regression, Decision Trees, Random Forests, Gradient Boosting), model training, and real-time monitoring.

2. Essential Features: Customer tenure, usage frequency, service interactions, and engagement metrics.

3. Strategic Benefits: Identify at-risk customers, implement targeted retention efforts, and enhance profitability.

Leveraging churn prediction models enables businesses to proactively improve customer retention and long-term growth.

Wrapping up

Reducing customer churn is crucial for businesses as it directly impacts long-term revenue, customer loyalty, and overall business stability. However, understanding why customers leave requires analyzing data and tracking various metrics over time. Effective churn analysis involves monitoring overall customer turnover rates and identifying factors contributing to attrition.

Businesses can use advanced analytics and machine learning techniques to identify potential churners and implement targeted retention strategies.

There’s no doubt that paid advertising is one of the best channels for marketing teams to generate and capture demand. Plus, we're seeing the rise of paid social media, with over 66% of B2B marketers acknowledging its impact on improving ROI. By targeting specific audiences and broadcasting your message across various channels, paid advertising can help drive the success of your campaigns.

However, running a few ads at random does not get you conversions. A strong strategy is key to maximizing ROI on expensive ads.

Let's dive in and look at how paid advertising can benefit your B2B company ⬇️

Google ads vs LinkedIn ads: Which one is best for B2B?

While many businesses advertise online, only a few do it well. It's especially tough when you have heaps of options to choose from. So, Google, LinkedIn, Search, Display, or a combination of all of the above? The choice isn't that simple, as each platform has its unique features and capabilities. In some instances, using either of the channels would be enough. For example, you should use Google Ads to target people based on their search queries, location, device, and more. LinkedIn ads can help create targeted ABM campaigns.

However, if you’re running a full-funnel campaign, you must use both Google and LinkedIn ads to their fullest potential.

Let's understand the differences between these platforms, how they work, their pros and cons, and which platform is better for your unique needs.

Google Ads

Google search ads appear when users search for specific keywords related to your business. Here are their pros and cons:

Pros of Search Ads

• Access to a larger audience when bidding on high-volume keywords
• Typically attract in-market leads as they're based on search intent
• Detailed analytics allow you to track clicks, conversions, and ROI effectively

Cons of Search Ads

• Popular keywords in B2B industries can be highly competitive, leading to higher costs per click.
• Demographic targeting is limited compared to social media platforms.
• Primarily text-based, offering less opportunity for visual branding.
• Lesser segmentation opportunities

LinkedIn Ads

LinkedIn ads target users based on their professional profiles, interests, and behavior. Here are their pros and cons:

Pros of LinkedIn Ads

• Extensive targeting options based on job title, company size, and industry, allowing precise audience segmentation.
• Ideal for B2B marketing.
• Access to high-value prospects and decision-makers
• Account-based marketing opportunities
• Offers various ad formats, like sponsored content, text ads, and InMail, providing flexibility in messaging and creative presentation

Cons of LinkedIn Ads

• Relatively costlier than Google search ads
• Cannot identify high-intent buyers unless they click on the ad
• Greater risk of ad fatigue and decreased engagement over time
• Lack of in-depth reporting and analytics tools

How to use Google ads and LinkedIn ads in tandem for a successful paid advertising strategy

While search ads and LinkedIn ads have distinct pros and cons, integrating them into a cohesive paid advertising strategy allows businesses to use each platform's strengths and increase their reach, engagement, and conversions. Here are a few ways to do so:

• Use search ads to capture users actively searching for solutions, and LinkedIn ads to raise awareness and nurture leads at different stages of the buyer's journey.
• Retarget users who interact with your LinkedIn ads through search ads and vice versa, reinforcing your messaging across platforms.
• Use data from both platforms to inform targeting and messaging strategies, optimizing performance across the board.
• Broaden your advertising channels and reduce reliance on a single platform to mitigate performance variations and adapt to algorithmic shifts.

💡Read: How to Measure LinkedIn True ROI With Factors

How to execute paid advertising across the funnel

When it comes to paid marketing, most people start with Google, which provides a decent number of quality leads by capturing searches that show intent. However, it's essential to create a well-structured funnel that attracts the right audience and converts them quickly. Instead of having countless uninterested users, it's better to have interested ones heading in the right direction. 

Here's where LinkedIn retargeting helps you reach a high-intent audience from Google and target them on LinkedIn.

1.  Pick the right advertising channels 

Consider where your ideal customers spend their time online and choose platforms with the potential to reach them. Before selecting the right platform, consider your budget and advertising goals for your paid advertising efforts. By thoughtfully selecting the right mix of channels, you can create a cohesive and effective B2B advertising strategy tailored to your unique business needs.

2. Get a high-quality and high-intent audience.

When reaching an audience on LinkedIn, you have two options. You can either target a new audience or retarget an existing one. If you choose the former, you'll reach out to a completely cold audience that may not be familiar with you or your brand, making it more challenging to capture their attention. However, suppose you choose to retarget your Google ads traffic. In that case, you'll reach out to an audience that has already shown interest in your brand by searching for relevant keywords on Google, clicking on your search or display ad, and visiting your website. This audience is more likely to have high intent and be receptive to your message.

Ideally, you should invest in both options if your budget allows it. However, if you have to choose between the two, it makes more sense to retarget a warm audience that has already shown interest in your product or service.

💡Also read: Build Better LinkedIn Retargeting Audiences with Factors

3. Optimize ad spend

Many clients want to establish a presence on LinkedIn but find advertising on the platform expensive. LinkedIn's cost per click (CPC) and lead (CPL) are relatively high compared to other platforms. However, the quality of leads on LinkedIn is worth the extra cost.

If you have already advertised on other channels, you can use LinkedIn to enhance your conversion rates. Different channels can add relevant leads to your LinkedIn campaigns, which can be part of your mid-funnel strategy. Proper retargeting of high-intent traffic via LinkedIn ads can lead to increased conversions.

4. Convert more by staying on top of their mind

According to the marketing rule of 7, "a prospect needs to "hear" the advertiser's message at least seven times before they'll take action to buy that product or service."

A customer's journey towards making a purchase is not always straightforward. They may come across your business through a LinkedIn Ad, search for your business on Google, visit your website, leave, and stumble upon you again on LinkedIn. They may revisit your website before deciding to reach out or make a purchase. Retargeting helps push website traffic towards purchase.

💡Also read: How to Measure the Impact of Paid Marketing Using Factors

Paid advertising best practices

Paid ad campaigns are dynamic, and the right strategies can significantly impact your brand's success. To improve your efforts at online paid advertising, consider the following best practices:

1. Establish realistic goals

Having measurable goals allows you to track your progress and stay on schedule. Define your KPIs to measure lead generation, sales conversion, or brand awareness success. This will help you make informed decisions and optimize your ad spend.

2. Create compelling paid campaigns 

Your ad creatives must grab the attention of your target audience. Keep them engaging, informative, and visually appealing. Avoid using jargon or complex language. Instead, focus on the value of your product and how it can solve a problem for your audience. Create a strong value proposition that highlights your unique benefits. Stand out from competitors and guide prospects to take action with a persuasive CTA.

Source: LinkedIn

3. Personalize your campaigns

Retargeting is a great way to personalize your marketing funnel for each campaign and tailor your message to the audience of that campaign. 

For example, you have a search ad campaign targeting your competitors' branded keywords, which generates much interest. You can use LinkedIn and launch a retargeting campaign based on how you compare against them and what you offer that they don't. Running retargeting ads helps you identify what drives people to click and then adjust your LinkedIn ads to push them toward your offerings.

💡Factors helps you identify accounts that view your LinkedIn ads and visit your website through a search ad. You can use this information to personalize your cold outreach and focus on accounts with higher intent. 

4. Measure and analyze

Track key metrics like click-through rates, conversion rates, CPA, and ROAS to make data-driven decisions. By setting campaign goals such as a target cost per lead or target conversion rate, you can track performance and analyze audience data like CTR and impressions to improve your marketing. 

Rev up your paid advertising game with Factors

While search and LinkedIn ads have unique features and capacities, integrating them into a cohesive paid advertising strategy allows businesses to use each platform's strengths and increase their reach, engagement, and conversions. Companies can optimize performance across the board by using data from both platforms to inform targeting and messaging strategies.

Thanks to Factors, you can gain a comprehensive view of buyer journeys, understand how your target accounts interact with your ads and determine whether your ad strategy is increasing revenue. Speak to our team today to optimize your paid advertising strategy in 2024.

Knowing how to build buyer trust through B2B marketing content can help create lasting customer relationships, drive sales, and foster customer retention. 

A recent survey by Forrester reported that B2B buyers are twice as likely to recommend a company to a colleague if they trust it. 

In this article, we’ll share insights on how to build buyer trust through B2B marketing content. 

What is a B2B content marketing strategy?

A B2B content marketing strategy is a carefully curated roadmap outlining how a company will create and share content that attracts and engages its audience.

A great content marketing strategy results in an impressive ROI. This explains why 90% of marketers use content as their primary digital marketing tool. 

That said, 97% of these marketers admit that their content marketing efforts have been successful, as shown in the HubSpot report below. 

Content comes in various forms, including blog posts, videos, webinars, e-books, social media posts, and case studies.

A well-defined content marketing strategy provides a plethora of benefits to B2B owners. These include:

• Increased website traffic, ultimately improving your brand’s visibility and driving more visitors
• Amplified B2B sales lead generation and conversion as quality content attracts prospects and guides them through a sales funnel.
• Improved relationships with customers by offering valuable resources that address common pain points and provide solutions
• Enhanced audience engagement, resulting in meaningful discussions and interactions that help build customer loyalty
• Increased brand awareness, helping to reach a larger audience

How to build buyer trust through B2B marketing content

Engaging B2B buyers can be challenging. To build trust, your content marketing strategy must be convincing enough to move your prospects past the decision stage in the customer journey.

Here are seven effective winning strategies for building buyer trust through B2B marketing content.  

1. Defining your target audience

When you know your audience and identify who you’re connecting to, it’s easier to tailor content that engages and resonates with them.

You can conduct successful audience research through the following ways:

• Create B2B buyer personas: Identify your ideal client profile. Understand their decision-making process and the reasoning behind their decisions.
• Collaborate with sales teams: Work with your sales team to understand your customer base. They’ve interacted with your prospects firsthand, so they should have valuable insights into their demographic data.
• Follow consumer conversations: Reading conversations on social media platforms can help you gauge your prospect's age, gender, geography, and more.

2. Knowing your audience’s preferences

Empathy is crucial in learning how to build buyer trust through B2B marketing. Consumers are generally drawn to companies that are genuinely interested in their success. 

You can show this by building an emotional connection with your customers through content. Observe their behaviors and preferences. Try to understand what they could hope to achieve with your product or service. 

With proper communication with your customers, you can grow your business with minimum cost on customer acquisition.

You can leverage great customer service software like Freshdesk to help you streamline your support processes and improve your customer experience. 

But it’s also crucial to consider other great Freshdesk competitors like Zendesk to ensure you’re selecting the best software for your business needs. 

There are multiple ways to establish an emotional connection with your audience and show them you’re listening. Here are some: 

• Analyze what makes your consumers interact with your content. What type of content do they like the most? What prompts them to leave your site? How many times do they visit your site before taking an action?
• Directly ask your customers what kind of content they expect from you, including what they enjoy or dislike about your content. You can do this through feedback forms, surveys, and focus groups.
• Gather information from your sales and customer service teams on what questions your customers ask the most. Then, define their needs and pain points to address these questions on a massive scale.
• Use social media platforms to have conversations with your audience. Respond to comments, share user-generated content, and participate in discussions to show that you value their feedback and engagement. 

The key to building buyer trust through B2B marketing content is to provide tailored content they can resonate with. Through your content, you can demonstrate that you’re attentive to their needs and feedback. 

3. Create informative content

When writing for B2B audiences, you need a deeper understanding of complicated concepts and technology.

Therefore, creating educational content that breaks down complex topics into digestible formats will help your audience understand your business better. This will, in turn, cause them to trust your content as a reliable source. 

A great example is the Amazon Web Services (AWS) blog below.

Leverage content recommendations to increase awareness on your educational blogs, extending their reach and allowing you to educate more of your audience. 

Whether it’s informational videos, articles, or blog posts, recommending high-quality content demonstrates your commitment to providing valuable information. As explained in the Attrock guide, some other ways exist to insert recommended content within a website. 

Here’s an example of content recommendation by Attrock. 

4. Establish your authority and expertise

One of the factors that B2B buyers consider before making a purchase is a brand’s authority in their niche. They like knowing you have the credentials, knowledge, and experience to support your claims. 

That’s why, as a B2B owner, building trust with your audience and showcasing your skills will help you stand out from the competition.

Craft top-of-the-funnel content that positions your company as a trusted expert in your industry. Discuss top practices and address your buyers’ queries.

You can even suggest your product or services as a viable solution to help your customers. However, be sure to do it tastefully without overpromoting your brand. Simply pitch the value your customers can get from your offerings. 

Remember, your B2B buyers just want to trust that your company can solve their problems. Providing reassurance on this assumption makes your content marketing strategy effective.

Here are some of the ways to use content marketing to establish authority within your industry:

• Share success stories from real customers, demonstrating how you helped them solve their specific problems
• Participate in industry conversations via webinars, forums, and guest articles
• Include authors’ headshots and bios when publishing articles
• Partner with industry influencers and leaders to further add credibility

You can also use social proof, particularly case studies, reviews, and awards, to show how others trust and have benefited from your brand.

5. Be authentic and transparent

Authenticity plays a significant role in building buyer trust through B2B marketing content. The more authentic you are, the more your readers will trust you.

Create blogs and videos that share the rationale for critical decisions on product launches, changes, and discontinuations, if any.

Also, ensure that your audience can quickly find information about your brand. Utilize search engine optimization strategies to help your website rank higher in search engines. With ample information about your brand online, you can maintain transparency. 

Creating “About Us” pages can also help your audience learn everything about your company. These pages humanize your values, history, journey, leadership, and work culture.

The image below exemplifies a well-drafted “About Us” page.

Other ways to maintain authenticity and trustworthiness in your B2B marketing content strategy are: 

• Explaining your product or service in detail 
• Answering questions upfront with FAQs on product pages
• Displaying pricing, lead times, ratings, and details about customer support
• Openly comparing yourself with competitors and acknowledging your similarities and differences 

6. Stay consistent

B2B sales cycles are generally complex and lengthy. Earning and maintaining your customer’s trust requires consistency and commitment.

You can start by maintaining a consistent presence on social media by regularly posting valuable content, responding to messages promptly, and actively participating in industry talks.

If you’re short on time and expertise, consider outsourcing content marketing tasks. This will help ensure a steady stream of high-quality content while you work on other strategic initiatives to improve your content. 

7. Ask for feedback and improvement

B2B buyers are more likely to trust your brand if you consider their opinion. They want assurance that you value their opinions and listen to their complaints.

This is why you need to ask for their feedback and input. You can do this through surveys, reviews, focus groups, and interviews. You can even provide incentives to encourage your customers to leave feedback. 

You can also utilize marketing measuring metrics, analytics, and testing to measure your performance, determine your strengths and weaknesses, and optimize your content.

Wrapping up

There you have it—the seven best ways to build buyer trust through B2B marketing content and stay ahead of your competition. 

Remember, trust takes time to build. However, it’s worth the time and effort. Once established, trust becomes an important asset. Having your audiences’ trust sets your brand apart and creates long-term customer loyalty. This is ultimately instrumental in your sales and profitability. 

Keep pushing and using the right marketing solutions to gain customers’ trust and expand your B2B services

The following article documents Chris Perrine's excellent presentation of the same name. Chris Perrine is VP & MD, Asia Pacific at G2 — and a leading mind on all things go-to-market. Check him out on LinkedIn.

B2C leads, B2B follows

Credit card payments, customer reviews, eCommerce, affiliate programs, and self-service are but a few selling trends that B2B companies have adopted from their trailblazing B2C counterparts. Without a doubt, implementing these practices have dramatically improved what was otherwise a tedious, time-consuming experience for B2B buyers and sellers alike. In fact, purchase decisions that once took several months (if not years), now take place in under a quarter.

As part of this evolution in buying patterns, B2B customers increasingly choose to conduct their own research — evaluating features, comparing alternatives, considering customer reviews, etc. — before speaking to sales or making a purchase decision. As you might have already guessed, this makes relevant, reliable content assets all the more valuable. Ironically, however, four of the top obstacles to make good software purchase decisions revolve around insufficient content.

This article explores what Chris refers to as The Trinity of Content — a content framework to resolve these common obstacles in making good software purchasing decision

What is the Trinity of Content?

The trinity of content refers to the idea that buyers view content as one entity, but it emanates from three key sources:

• Vendor content
• Expert content
• Customer content

Before diving into the B2B context of the Trinity of Content, let’s take an easier example: buying a car. Before you purchase a shiny new car (or most other things, for that matter), you consume a range of content — product specs, expert reviews, customer feedback, and more — before arriving at a decision.

What’s more? The consumption of this content is rarely ever linear. Instead, most of us go back and forth between vendor content (company website, dealer, test drive, etc), expert content (automobile magazines, awards, etc) and customer content (customer reviews, reddit, etc) — resulting in a great big mess of a customer journey. This mess is all the more pronounced in the case of B2B deals as they typically involve lengthy sales cycles and several stakeholders atop multiple channels and touchpoints. You might first learn about a product or service via a search ad, a blog, or a social media post — either way, the next few weeks and months would involve learning more about the offering, comparing alternatives, reading reviews, and eventually, speaking with sales. The next few sections explore the influence of vendor, expert, and customer content in this journey.

I. Vendor Content 

The most important aspect with vendor content is that you are in control of it. Everything from the messaging, volume, focus, and placement is in your hands. In the B2B context, few examples of Vendor content include:

• Website
• Sales collateral 
• Case studies
• Product demo
• Trials
• Blogs
• Ads
• Events
• Thought-leadership posts

While there’s no doubt that this type of content is absolutely essential to build up a brand as an authority in its space, there are a couple of reasons why it’s insufficient to rely exclusively on vendor content:

• For one, B2B verticals are becoming increasingly competitive across the board. If everyone is pumping out high-quality vendor content, there’s not much scope to stand out. 
• More importantly, however, the trust and influence that buyers have of vendor content has never been lower. In fact, only about 38% of buyers consider the website to be the most trust-worth resource. 

II. Expert Content

To solve this issue of trust, buyers typically consult industry experts for relevant, neutral feedback on products and services. You might have experienced expert content in the form of Gartner/Forrester reports, LinkedIn influencers, or management consultant reports from McKinsey, BCG, etc. 

The benefits of expert content are that they take neutral PoVs and are typically extremely well-researched and data-driven. That being said, expert content is not without its limitations:

III. Customer Content

Finally, we arrive at customer content. When was the last time you purchased a product on Amazon without reading the reviews? If you’re like most consumers, the answer is probably never. Customer content is, by far, the most trusted type of content out there — simply because of its in the hands of (generally) unbiased users that have actually adopted the product you’re considering. 

And there you have it! A combination of Vendor, Expert, and Customer content to drive trust, and ultimately, pipeline. Here are three key takeaways from the Trinity of Content:

Paint with a broad brush: the current state of GTM analytics

Across the board, B2B companies plan their go-to-market strategy around a list of target accounts, otherwise known as segments. Regardless of whether these segments are vague, specific, broad, or focused, they’re at the heart of nearly every single go-to-market effort:

• How can we acquire our first 20 customers in this new vertical?
• How can we penetrate North America with our existing verticals?
• How can we upsell or cross-sell to existing mid-market and enterprise customers?
• How can we capture demand amongst EU-based fintech SMEs with over 100 employees?

Despite the way we typically think about GTM, however, our tooling has continued to remain lacking. Even the most popular analytics solutions (Looking at you, Google Analytics 👀) still report GTM KPIs at a channel-level, rather than at a segment-level. Sure, tools like GA4 can say a lot about your overall website performance — but how are your GTM efforts influencing your target accounts in particular? 

How does that LinkedIn ad, search campaign, website copy, blog article, thought-leadership post, newsletter, or webinar impact the niche audience you actually care about? Are the right accounts…

• Viewing your LinkedIn ads?
• Clicking on your search ads?
• Driving up website traffic?
• Responding to your emails?
• Submitting demo forms?

You may find such questions difficult to answer with run of the mill analytics and CRM tools because manually parsing aggregated data, across multiple channels by individual segments is, well, a tedious, time-consuming chore. It also tends to be free of nuance or granularity — resulting in hazy paintings with a broad brush. Additionally, while most analytics tools do a decent job of reporting high-level metrics (traffic, clicks, impressions, etc), they struggle to unify the buying journey in its entirety across:

• Cross-channel engagement
• Meetings booked
• SQL/opportunity conversions
• Pipeline value
• Win rate
• Sales cycle length
• Revenue sourced

The result? Marketers and sales folk are left with a heap of channel data, generic reports, and no real understanding of whether their efforts reached and resonated with the right audience.

Introducing Segment Insights By Factors

Establishing the segments you care about is the first step to GTM success. However, in our conversation with several B2B teams, we’ve learned that achieving granular insight into how these segments are performing is a real challenge. This is where Factors steps in to provide a robust and intuitive approach to GTM analytics with Segment Insights.

What is Segment Insights?

Segment insights is our latest product feature to help businesses measure, compare and improve segment performance for a targeted group of accounts.

What can I do with Segment Insights?

There are several use-cases powered by Segment Insights. Here, we highlight a few.

1. Segment-level measurement

It’s one thing to track generic website and campaign KPIs — but Factors helps you measure those same metrics (and more) specific to the segment of accounts you care about. This way, you eliminate irrelevant data and zero in on pertinent engagement across website, LinkedIn, G2 and more to answer burning questions such as:

• How many (and which) accounts in this segment are showing disproportionate buying intent? 
• How are accounts in this segment converting to MQL/SQL/Opportunity/etc? Is this improving?
• How many (and which) accounts from this cohort or segment have viewed LinkedIn ads?
• How many (and which) accounts from this cohort or segment visited G2 and then your website?
• How have these KPIs trended over time? How do they compare from last quarter?
• What is the health of this particular segment? How does it compare to overall health average? 

And the best part? If none of the several pre-built KPIs fit what you’re looking for, you always have the option to design custom KPIs for bespoke analysis of a particular segment. 

2. Segment-level comparison

Data-driven marketing teams are often keen to compare metrics across cohorts to better understand which efforts and touchpoints resonate with whom. For example, you may want to compare business metrics between:

• Segments of two different industry verticals (Eg: SaaS SMEs vs SaaS Mid-market) 
• Segment of accounts that attended a flagship event vs segment of account that did not
• Segment of accounts that visited a paid landing page vs segment of accounts that did not

On the other hand, you might also choose to perform an A/B test: altering a single variable (budgets, creatives, etc) from otherwise identical segments (eg: US-based software SMEs) to better gauge resonance and optimize GTM efforts.  

3. ROI-boosting lift analysis

It’s not exactly news that spending money on ads, SEO, events, and other B2B marketing activity results in increased website activity. This, in itself, doesn’t really mean much. What B2B marketers really care about is how their efforts influence their target accounts. This is where lift analysis comes in:

Say you have an ABM account list. You’re targeting these accounts with ads, emails, calls, and other tactics. But which combination of tactics work best? How are your ABM efforts influencing pipeline? And where should you reallocate budgets to improve ROI? To have a better sense of this, leverage Factors by creating two similar segments: one that receives ABM treatment and the other doesn’t. Once set up, you’ll have visibility into the impact of ABM on win rates, sales velocity, ACV, and much, much more. For instance, the first segment might show higher conversions rates and deal sizes despite the second segment showing more top of the funnel website engagement. Ultimately, learnings from this kind of analysis will result in deeper insights to prove and improve marketing impact.   

4. Organizational alignment 

Marketing, sales, and revenue leaders typically prioritize segments over channels — where the deals are coming from don’t matter as much as the quality of those deals. Accordingly, Segment Insights facilitates a similar perspective, enabling marketing teams to analyze data and make strategic decisions based on their target market, not just clicks and impressions. This fosters organizational alignment between GTM teams and leadership.

The bottom line is this: with Factors, you needn’t limit yourself to broad analytics across website engagement and marketing campaigns, and sales touchpoints. Instead, leverage Segment Insights to achieve a deeper, relevant understanding of the target accounts you actually care about. Learn more about Segment Insights over a chat with our product experts today!

Sales and marketing teams struggle to identify and prioritize leads that are highly likely to convert. Manually scoring leads is time-consuming and often results in guessing and methodology inconsistencies.

What if there was a way to automatically score leads based on their conversion likelihood using data-driven insights and machine learning algorithms? This would allow teams to focus on the most promising prospects, personalize outreach, and improve conversion rates significantly.

The answer—predictive lead scoring. 

Predictive lead scoring optimizes lead management by identifying leads most likely to convert using AI and historical data. This article will explore predictive lead scoring, its benefits, and how it transforms lead management strategies.

What is Predictive Lead Scoring?

At its core, predictive lead scoring ranks leads based on their likelihood of converting into customers. 

It’s a modern approach, evolved from traditional, manual lead-scoring methods.

Previously, sales and marketing teams manually assigned scores to leads based on factors like demographic information and behavior. 

This approach was time-consuming and often relied on gut instincts rather than data. 

But, as platforms became more advanced, so did their methodologies for lead scoring. In recent years, many platforms have also started using AI to power their lead scoring instead of rule-based scores. 

Most lead scoring models use the following pieces of data to make sense of what stage of the buyer’s journey the lead could be at:

• CRM data
• Website behavior
• Social media interactions
• Email Engagement
• Demographic information

With this data, AI algorithms can identify patterns and correlations that indicate a lead’s likelihood of converting. You can use a lead scoring tool to identify and prioritize customers interested in your product.

The idea behind predictive lead scoring is  to eliminate the unnecessary blockers that slows and help them make real-time decisions based on the right data. Let’s further explore the benefits of predictive lead scoring 

5 Benefits of Predictive Lead Scoring

Predictive lead scoring can be quite powerful and lead to several impactful benefits, including:

1. Increased Efficiency: When you prioritize leads based on their likelihood of conversion, your sales team can focus their time and resources on the most promising opportunities. This leads to higher conversion rates, shorter sales cycles, and improved efficiency.
2. Better Alignment Between Sales and Marketing: Predictive lead scoring helps bridge the gap between sales and marketing teams. Once you establish a common framework for evaluation, both teams can work together more effectively, ensuring that marketing efforts generate high-quality leads and sales teams follow up on the most valuable prospects.
3. Personalized Engagement:  You can tailor your engagement strategies to match the preferences and needs of individual leads. , When you know what influences a prospect’s buying decision, you can deliver targeted content, personalized offers, and customized communication that resonates with each lead, increasing the likelihood of conversion.
4. Improved Resource Allocation: When you can predict which leads are most likely to convert, you can easily move resources from other leads to focus on them.
5. Data-Driven Decision Making: Instead of relying on guesswork and intuition, predictive lead scoring helps you base your decisions on actual customer behavior and preferences. Basing decisions on objective data can help you optimize your sales and marketing strategies, identify areas for improvement, and continuously refine your approach.

Implementing predictive lead scoring has various other benefits that you realize as you start using it within your day-to-day workflows.  

Let’s now see how predictive lead scoring works. 

How Predictive Lead Scoring Works

Let's examine the process of predictive lead scoring and how it uses data, analytics, and automation to identify and prioritize the leads most likely to become customers. We'll explain each step so you can understand how it all fits together.

1. Know Your Leads

 Collect detailed information about your leads from different sources. This includes basic data like job titles and company size, activity data like website visits and email engagement, and any other information that helps you understand their needs, interests, and buying likelihood. 

The better you know your leads, the easier it is to evaluate their potential.

2. Add Mined Information

You can improve your lead data by using data mining techniques and adding information from third-party data sources. This means pulling valuable insights from unorganized data like social media posts and web forums and combining them with the lead records you already have.  You can find hidden patterns, connections, and details that make your lead-scoring model more accurate.

3. Apply Predictive Analytics

Now, here's where things get interesting. Once you have the improved lead data, you can use predictive analytics algorithms. These algorithms look at past data to find the main factors and patterns that match up with successful conversions. 

Suppose your historical purchase data shows that leads from the healthcare industry who visit your pricing page or attend a webinar are 80% more likely to convert than the average lead. 

Predictive analytics algorithms can detect this pattern and assign a higher lead score to prospects who exhibit similar behavior.

Using methods like logistic regression, decision trees, and machine learning, you can create a predictive model that gives each lead a score based on how likely they are to convert.

4. Identify Sales Ready Leads

After the predictive model is set up, you can use it on your current lead database to create scores for each lead. These scores show how likely a lead is to become a customer, with higher scores meaning a better chance of conversion. 

With this information, you can rank and group your leads based on their buying readiness so your team can focus on the most promising opportunities.

5. Prioritize Highest Value Leads

The leads with the highest scores are the real standouts—they're the most valuable and ready to buy. These are the people whose traits and behaviors most closely match successful conversions in the past. 

These high-value leads can help your sales team make the most of their time and resources, increasing their chances of closing deals and growing revenue.

The above steps are automatically handled with predictive lead scoring after you integrate the data. 

The result is a ranked list of the high-fit and high-intent leads.

This helps your sales team target the right leads at the right time with personalized outreach strategies. Predictive lead scoring also helps achieve higher conversion rates and grow your business, as your team can connect with potential leads while they’re still hot. 

What Data is Used for Predictive Lead Scoring?

Creating an effective predictive lead scoring model requires considering a wide range of factors influencing a lead’s likelihood to convert. These factors can be grouped into several categories:

Demographic Data

Demographic information, such as age, location, industry, and company size, can provide valuable insights into a lead’s potential fit for your product or service. For example, if you’re selling enterprise software, leads from larger companies may be more likely to convert than those from small businesses.

Behavioral Signals

A lead’s behavior can tell you a lot about their level of interest and engagement with your brand. Some key behavioral signals to consider include:

• Website visits: How often does a lead visit your website, and which pages do they view?
• Content engagement: Do they download whitepapers, attend webinars, or engage with your blog posts?
• Email interactions: Do they open and click through your emails?
• Social media activity: Do they follow your company on social media or engage with your posts?

External Data Sources

Predictive lead scoring models can also incorporate information from external sources, in addition to data from your systems, such as:

• Social media data: Insights from a lead’s social media profiles and activity can provide valuable context about their interests and behavior. You can even use intent data to drive your pipeline further. 
• Third-party data providers: Companies like Clearbit and 6sense can provide additional firmographic and technographic data to enrich your lead profiles. Factors integrates with both the data providers, helping you reveal an industry-leading 64%+ anonymous accounts.

When put together, you get a complete picture of the journey of the lead going from 

Challenges with Predictive Lead Scoring

While AI-powered lead scoring can be a powerful tool, there are also some challenges and considerations to keep in mind:

Highly Dependent on Data Quality 

The accuracy of predictive lead scoring models depends heavily on the quality of the data they’re trained on. If the data is incomplete, inconsistent, or inaccurate, the model’s predictions will be less reliable. Ensuring that data is properly collected, cleaned, and maintained is crucial.

Regular Model Training

Predictive models require continuous refinement and retraining to stay accurate as new data comes in. This means that implementing AI-powered lead scoring is not a one-and-done process, but rather an ongoing commitment.

Cannot Replace Human Judgment

While AI can provide valuable insights and predictions, it’s important to remember that it’s ultimately a tool to augment human decision-making, not replace it entirely. Sales and marketing teams should use AI-powered lead scoring as one input among many when prioritizing their efforts.

Take Advantage of Predictive Lead Scoring!

Predictive lead scoring offers clear benefits: it increases conversion rates, shortens sales cycles, improves sales and marketing alignment, and optimizes resource allocation.

However, it is a challenge to implement. 

You must either rely on internal developer resources and sufficient data to ensure success or partner with third-party tools specializing in this area and have access to extensive datasets for accurate lead scoring and account intelligence features. 

Enter Factors.

A powerful platform that combines data from across your marketing stack and channels to get you the best insights under a single roof. Factors automatically assigns lead scores based on data from your CRM and the ads you run, the pages your visitors view, and more to give you a holistic score that considers as much relevant data as possible.

Factors also partners with Clearbit and 6sense to help you reveal anonymous accounts browsing your website or interacting with other marketing channels, which enhances your account-based marketing. 

Get ready to level up your marketing stack. Hop on a demo call with Factors and see how you can benefit from Factors today!

Business success isn’t just about attracting leads—it's about converting them into loyal customers. That's where lead tracking comes in. With lead tracking, you can seamlessly monitor and analyze customer interactions across all touchpoints, from social media to email campaigns. You can determine who's interested in what you're offering and how likely they will buy from you.

Without much ado, let’s understand more about lead tracking.

Lead Tracking Vs. Lead Scoring

While many use “lead tracking” and “lead scoring” interchangeably, they’re distinct concepts. Here is a list of differences between the two:

Read more about lead scoring software tools for B2B SaaS here.

Consider a software company specializing in customer relationship management (CRM) solutions. The company can leverage lead tracking to monitor when prospects download a lead magnet on your website. Subsequently, these leads receive targeted emails with relevant content and invitations to attend webinars on CRM best practices. Meanwhile, lead scoring assigns higher scores to leads who engage with multiple resources, attend webinars, and request product demonstrations, indicating a higher likelihood of conversion.

So, are the two interrelated?

Lead tracking and scoring are closely intertwined and complement each other in several ways. Here’s how:

1. Data Collection 

Lead tracking provides the necessary data and insights for lead scoring. Businesses gather valuable information about lead behavior, interests, and engagement levels, which serves as the basis for lead scoring by monitoring and documenting lead interactions.

2. Behavioral Analysis 

Lead tracking allows businesses to observe how leads interact with various marketing channels, content, and touchpoints. This behavioral data forms the basis for lead scoring criteria, helping identify key indicators of lead interest and readiness to purchase. For example, if a lead spends time on your pricing page, watches a demo, and engages with your emails, they're likely ready for a personalized sales pitch.

3. Scoring Criteria Refinement 

As businesses track leads' interactions and analyze their behavior over time, they gain insights into which actions and behaviors correlate most strongly with conversion. This information can be used to refine and optimize lead scoring criteria, ensuring that the scoring model accurately reflects lead quality and likelihood of conversion.

4. Continuous Improvement 

Lead tracking and lead scoring are iterative processes that feed into each other. The data collected through lead tracking informs lead scoring models, while the results of lead scoring provide feedback that informs adjustments to lead tracking strategies and criteria. This continuous cycle drives ongoing improvement in lead qualification and conversion rates.

5. Effective Lead Management 

 lead tracking and lead scoring enable businesses to manage leads more effectively throughout the sales funnel. Businesses can ensure that their sales teams focus their efforts where they are most likely to yield results by identifying high-value leads early in the process and prioritizing follow-up based on lead score and behavior.

Why do Sales and Marketing need Lead Tracking?

Lead tracking is the backbone of effective sales and marketing strategies. It provides valuable insights into customer behavior, preferences, and engagement levels, allowing teams to tailor their efforts accordingly. By tracking leads, sales and marketing teams can:

Maximize Efficiency

In the hustle and bustle of daily operations, time is money. Lead tracking streamlines the process by allowing teams to zero in on high-value prospects. Instead of casting a wide net and hoping for the best, sales and marketing teams can focus on leads with the highest potential for conversion. This targeted approach reduces time wasted on unqualified leads, allowing teams to allocate resources more efficiently.

Improve Conversion Rates

At the end of the day, it's all about conversions. Lead tracking provides valuable insights into lead behavior, preferences, and pain points, enabling teams to tailor their communication and follow-up strategies accordingly. By delivering personalized messages at the right time and through the right channels, teams can significantly increase the likelihood of converting leads into paying customers. It's all about striking the right chord and nurturing relationships that lead to conversions.

Enhance Customer Experience

Lead tracking enables teams to understand leads' needs and interests on a deeper level. Armed with this knowledge, teams can deliver relevant and timely information, providing a seamless and satisfying experience for potential customers. Whether it's sending a personalized email, offering a tailored solution, or addressing a specific pain point, lead tracking allows teams to create meaningful interactions that leave a lasting impression.

Optimize Resource Allocation

Every dollar counts in sales and marketing. Lead tracking helps teams identify which marketing channels and campaigns are yielding the best results. Teams can pinpoint the most effective strategies and allocate their resources accordingly by analyzing lead data and conversion metrics. Whether it's doubling down on a successful social media campaign or tweaking the messaging of a lackluster email campaign, lead tracking empowers teams to make informed decisions that maximize ROI.

Measure Performance

You can't improve what you can't measure. Lead tracking provides teams with comprehensive data on lead interactions, conversions, and sales pipeline progression. Armed with this data, teams can evaluate the effectiveness of their sales and marketing efforts and make data-driven decisions for improvement. Whether it's identifying bottlenecks in the sales process, optimizing the performance of a landing page, or fine-tuning the messaging of a sales email, lead tracking enables continuous improvement and optimization.

Understanding the Sales Funnel to Track Leads

The sales funnel represents the journey that prospects undertake from initial awareness of a product or service to make a purchase decision. While the exact steps may vary depending on the industry and business model, the typical stages include:

1. Awareness 

At this stage, prospects become aware of a company's products or services, often through marketing efforts such as advertisements, content marketing, or social media.

2. Interest 

Prospects show interest in the offerings and seek more information. They may visit the company's website, download resources, or subscribe to newsletters.

3. Consideration 

In this phase, prospects evaluate the value proposition and compare the company's offerings with competitors. They may communicate directly with sales representatives or request product demos.

4. Decision 

Prospects reach a decision point where they decide whether to make a purchase. This stage often involves negotiating terms, addressing objections, and finalizing the transaction.

After making a purchase, customers enter the retention phase, where efforts focus on providing excellent post-sales support, fostering customer loyalty, and encouraging repeat business.

By aligning lead tracking efforts with the stages of the sales funnel, organizations can tailor their communication strategies to address prospects' specific needs and move them seamlessly through the buying journey.

Retention 

After making a purchase, customers enter the retention phase, where efforts focus on providing excellent post-sales support, fostering customer loyalty, and encouraging repeat business.

By aligning lead tracking efforts with the stages of the sales funnel, organizations can tailor their communication strategies to address prospects' specific needs and move them seamlessly through the buying journey.

Capturing Leads: Where and How?

Before we start tracking leads, it’s important to understand where and how to capture these leads. Capturing leads involves enticing potential customers to provide their contact information or engage with your brand in some way. 

Here are some common channels and methods for capturing leads:

Website Forms

Embedding lead capture forms on your website allows visitors to submit their contact information in exchange for valuable content, such as ebooks, whitepapers, or webinars.

Landing Pages

Designing dedicated landing pages optimized for lead generation can help capture leads from specific marketing campaigns or promotions.

Social Media

Leveraging social media platforms to promote gated content and engage with followers can generate leads and foster relationships with potential customers.

Email Marketing

Including calls-to-action (CTAs) and lead capture forms in email campaigns encourages subscribers to take the next step and provide their contact information.

Events and Webinars

Hosting events, webinars, or workshops provides opportunities to capture leads from attendees interested in your topic or industry.

Networking and Referrals

Building relationships with industry peers and existing customers can lead to referrals and introductions to potential leads.

By diversifying lead capture channels and methods, organizations can reach a broader audience and generate a steady stream of leads for their sales and marketing efforts.

Types of Leads for Tracking

Not all leads are created equal, and it's essential to track different types of leads based on their stage in the buyer's journey and their level of engagement. Some common types of leads to track include

Cold Leads

These are leads who have shown minimal interest or engagement with your brand. Tracking cold leads allows teams to nurture them over time and gradually build trust and rapport.

Warm Leads

Warm leads have shown some level of interest or engagement with your brand, such as downloading a whitepaper or attending a webinar. Tracking warm leads helps teams prioritize follow-up efforts and tailor their messaging to address specific needs and pain points.

Hot Leads

Hot leads are highly engaged and have demonstrated a strong intent to purchase, such as requesting a product demo or submitting a contact form. Tracking hot leads allows teams to capitalize on buying signals and expedite the sales process.

Qualified Leads

Qualified leads meet specific criteria set by the organization, such as budget, authority, need, and timeline (BANT). Tracking qualified leads helps teams focus their efforts on prospects who are most likely to convert into customers.

By tracking different types of leads, sales and marketing teams can tailor their approach to each segment of their audience, delivering personalized and relevant content and increasing the likelihood of conversion.

Collecting Lead Infomation

Collecting lead information involves gathering relevant data points about potential customers to facilitate communication and relationship building. 

Here are some key pieces of information to collect from leads:

Basic Contact Information

This includes name, email address, phone number, and company name, enabling teams to initiate and maintain communication with leads.

Demographic Information 

Gathering demographic data such as location, industry, job title, and company size helps teams segment and target their audience more effectively.

Behavioral Data

Tracking lead interactions with your website, emails, and marketing campaigns provides insights into lead engagement and interests, allowing for more personalized and relevant communication.

Lead Source 

Identifying how leads found your company, whether through organic search, social media, referrals, or other channels, helps measure the effectiveness of your marketing efforts and allocate resources accordingly.

Purchase Intent

Assessing the level of interest and intent to purchase allows teams to prioritize follow-up activities and tailor their messaging to meet the needs of each lead.

When collecting lead information, it's important to strike a balance between gathering enough data to personalize communication and respecting the lead's privacy and preferences. Providing clear and transparent explanations of how their information will be used and giving them control over their data builds trust and fosters positive relationships with potential customers.

How to qualify leads and prospects?

Qualifying leads involves determining their suitability and readiness to engage with your sales team and move through the sales process. 

But wait, why qualify leads?
By qualifying leads effectively, sales and marketing teams can focus their efforts on leads with the highest potential for conversion, improving efficiency and driving revenue growth. This, in turn, prevents the organization’s resources from being drained out.

Now since that’s out of the way, here are some common criteria and methods for qualifying leads:

BANT Criteria

BANT stands for Budget, Authority, Need, and Timeline. Assessing leads against these criteria helps determine their readiness to purchase and their fit with your product or service.

Lead Scoring

Assigning numerical values to various lead attributes, such as engagement level, company size, and purchase intent, allows teams to prioritize leads based on their likelihood of conversion.

Behavioral Signals

Monitoring lead behavior, such as website visits, content downloads, and email interactions, provides insights into their level of interest and engagement, guiding qualification decisions.

Qualification Questions

Asking specific questions during lead capture or follow-up conversations helps uncover key information about the lead's needs, challenges, and buying timeline.

Sales and Marketing Alignment

Establishing clear criteria and processes for lead qualification ensures alignment between sales and marketing teams, preventing leads from falling through the cracks and maximizing conversion opportunities.

Methods of Lead Tracking

Lead tracking can take various forms, depending on the nature of the business and the preferences of the organization. Some common methods of lead tracking include

Manual Tracking

This involves recording lead interactions and information manually, using spreadsheets, notebooks, or other documentation methods. While simple, manual tracking can be time-consuming and prone to errors.

CRM Software

Customer Relationship Management (CRM) software automates lead tracking processes, capturing and organizing lead information in a centralized database. CRM systems offer features such as lead scoring, activity tracking, and pipeline management, streamlining lead management and improving efficiency.

Marketing Automation Platforms

Marketing automation platforms automate lead tracking and nurturing processes, allowing teams to create targeted campaigns, track engagement metrics, and analyze lead behavior. These platforms integrate with CRM systems to ensure seamless data synchronization and workflow automation.

Website Analytics

Website analytics tools track visitor behavior on a company's website, providing insights into traffic sources, page views, and conversion rates. By analyzing website data, teams can identify patterns and trends and optimize their website for better lead generation and conversion.

Call Tracking

Call tracking allows organizations to attribute inbound calls to specific marketing campaigns, enabling accurate measurement of campaign effectiveness. By recording and analyzing phone calls, businesses gain valuable insights into customer conversations, helping to refine sales approaches and improve the overall customer experience. Integrated with CRM systems, call tracking enhances lead management, streamlines the sales process, and facilitates effective lead qualification, ultimately driving revenue growth.

Lead Tracking Metrics

By measuring key metrics, businesses gain valuable insights into the effectiveness of their lead generation efforts, the health of their sales pipeline, and the overall performance of their sales and marketing initiatives. Let's explore some of the essential lead tracking metrics that organizations need to measure to drive success.

1. Lead Generation Metrics

• Number of Leads

This metric quantifies the volume of leads generated within a specific timeframe, providing a high-level overview of lead generation efforts.

• Lead Source

Understanding where leads are coming from—organic search, social media, email marketing, or paid advertising—helps organizations optimize their marketing channels and allocate resources effectively.

• Conversion Rate

The conversion rate measures the percentage of leads that convert into qualified prospects or customers. It provides insights into the effectiveness of lead generation strategies and the quality of leads being generated.

2. Lead Quality Metrics

• Lead-to-Opportunity Ratio

This metric compares the number of leads generated to the number of opportunities created, highlighting the quality of leads and the effectiveness of lead qualification efforts.

• Sales Accepted Leads (SAL)

SALs are leads that meet specific criteria and are accepted by the sales team for further follow-up and engagement. Tracking SALs helps measure lead quality and alignment between sales and marketing efforts.

• Marketing Qualified Leads (MQL) and Sales Qualified Leads (SQL)

MQLs and SQLs are leads that meet specific criteria and are deemed ready for marketing or sales engagement, respectively. Measuring MQL and SQL conversion rates provides insights into lead nurturing and qualification processes.

3. Sales Pipeline Metrics

• Pipeline Velocity

Pipeline velocity measures the speed at which leads move through the sales pipeline, from initial contact to closing. It helps identify bottlenecks and inefficiencies in the sales process and informs sales forecasting efforts.

• Average Deal Size

This metric calculates the average monetary value of closed deals, providing insights into the revenue potential of individual leads and the overall health of the sales pipeline.

• Win Rate

The win rate measures the percentage of leads that successfully convert into customers. It helps evaluate sales effectiveness and the quality of lead management practices.

4. Lead Engagement Metrics

• Email Open Rate and Click-through Rate (CTR)

These metrics measure the effectiveness of email marketing campaigns in capturing leads' attention and driving engagement.

• Website Traffic and Engagement

Tracking website traffic, page views and engagement metrics such as bounce rate and time on the page provides insights into lead behavior and interests.

• Social Media Engagement 

Metrics such as likes, shares, comments, and click-throughs on social media posts help gauge audience engagement and the effectiveness of social media marketing efforts.

5. Customer Lifetime Value (CLV)

CLV quantifies the total revenue generated from a customer over their entire relationship with the organization. By understanding CLV, businesses can prioritize high-value leads and tailor their marketing and sales strategies accordingly.

6. Return on Investment (ROI)

ROI measures the profitability of lead generation and marketing campaigns by comparing the revenue generated to the cost of acquiring leads. It helps organizations evaluate the effectiveness of their marketing spend and allocate resources to initiatives that deliver the highest ROI.

Benefits of Lead Tracking for Businesses

The benefits of lead tracking extend far beyond merely organizing contact information. 

Let's see why lead tracking is essential for business success:

Improved Targeting 

Lead tracking enables organizations to segment their audience based on demographics, behavior, and interests, allowing for personalized communication and targeted marketing campaigns.

• Enhanced Lead Nurturing 

By tracking interactions with leads over time, businesses can identify their interests, pain points, and preferences, enabling more effective lead nurturing and relationship building.

• Optimized Resource Allocation

Lead tracking helps prioritize leads based on their level of engagement and likelihood of conversion, allowing sales teams to focus their efforts on high-value opportunities and maximize their productivity.

• Data-Driven Decision Making 

With comprehensive data on lead interactions and conversion metrics, organizations can make informed decisions regarding marketing strategies, product development, and sales tactics.

• Increased Revenue 

By effectively tracking and managing leads, businesses can streamline the sales process, reduce lead leakage, and ultimately increase revenue through higher conversion rates and customer retention.

Why should you care about Lead Tracking?

When customer acquisition costs are rising, and customer loyalty is increasingly elusive, lead tracking has become a necessity.

Here are some reasons why businesses of all sizes should prioritize lead tracking

• Gain Insights into Customer Behavior

Lead tracking provides valuable insights into customer behavior, preferences, and pain points, enabling organizations to tailor their marketing messages and sales pitches for maximum impact.

• Maximize Marketing ROI

By tracking the effectiveness of various marketing channels and campaigns in generating leads and conversions, businesses can allocate their marketing budget more efficiently and achieve a higher return on investment (ROI).

• Shorten Sales Cycle

With timely and targeted follow-ups based on lead tracking data, businesses can accelerate the sales cycle and minimize the time between initial contact and conversion, thus increasing revenue and improving cash flow.

• Build Long-Term Relationships

Effective lead tracking allows businesses to nurture relationships with prospects over time, earning their trust and loyalty, which can result in repeat business, referrals, and positive reviews.

• Stay Ahead of the Competition

Lead tracking gives businesses a competitive edge by enabling them to anticipate customer needs, adapt quickly to market trends, and deliver exceptional customer experiences.

Challenges of Lead Tracking

From data management woes to organizational alignment hurdles, navigating the complexities of lead tracking requires a strategic approach and a deeper understanding of potential roadblocks. 

Here are some of the key challenges of lead tracking and how organizations can overcome them.

• Data Overload and Management

One of the most significant challenges of lead tracking is dealing with a deluge of data. With leads coming in from multiple channels and touchpoints, organizations often struggle to manage and organize the vast amounts of information effectively. From contact details and interaction history to demographic data and behavioral insights, keeping track of it all can quickly become overwhelming.

Solution

Implement a robust CRM system that centralizes lead data and provides tools for segmentation, categorization, and analysis. Invest in data management best practices, such as regular data cleansing, deduplication, and data validation, to ensure data accuracy and integrity.

• Lack of Integration and Siloed Data

In many organizations, lead tracking systems and processes operate in silos, leading to disjointed data and fragmented insights. Marketing teams may use one platform for lead generation, while sales teams rely on another for lead management, resulting in a disconnect between departments and duplication of efforts.

Solution

Foster cross-departmental collaboration and alignment by integrating lead tracking systems with other sales and marketing tools, such as marketing automation platforms, email marketing software, and customer support systems. Establish clear processes and communication channels to ensure that lead data is shared seamlessly across departments.

• Inaccurate or Incomplete Data

Maintaining data accuracy and completeness is another common challenge in lead tracking. Leads may provide inaccurate or incomplete information during the initial capture process, leading to errors and inefficiencies downstream. Additionally, data decay over time can result in outdated or stale lead information, diminishing the effectiveness of lead tracking efforts.

Solution

Implement data validation mechanisms, such as real-time form validation and automatic data enrichment, to ensure that leads provide accurate and complete information during the capture process. Regularly update and cleanse lead data to remove duplicates, correct errors, and refresh outdated information.

• Difficulty in Lead Attribution

Attributing leads to specific marketing campaigns or channels can be challenging, especially in multi-channel marketing environments. With leads interacting with multiple touchpoints and engaging in cross-channel journeys, accurately attributing conversions to the appropriate source can be a daunting task.

Solution

Implement multi-touch attribution models that assign credit to multiple touchpoints along the customer journey, rather than relying solely on last-click attribution. Utilize advanced analytics and tracking tools to track and analyze lead interactions across various channels and touchpoints, providing a holistic view of the customer journey.

• Ensuring Compliance with Data Privacy Regulations

With the increasing focus on data privacy and security, organizations must navigate a complex landscape of regulations and compliance requirements when collecting and managing lead data. From GDPR in Europe to CCPA in California, failing to comply with data privacy regulations can result in hefty fines and reputational damage.

Solution 

Stay informed about relevant data privacy regulations and ensure compliance with applicable laws and regulations when collecting, storing, and processing lead data. Implement robust data protection measures, such as encryption, access controls, and data anonymization, to safeguard lead data and mitigate the risk of non-compliance.

Lead Tracking and Accuracy

While lead tracking offers a multitude of benefits, its effectiveness hinges on the accuracy and reliability of the data collected. 

Here are some strategies for ensuring accuracy in lead tracking

• Standardize Data Collection

Establish standardized processes for capturing and recording lead information across all touchpoints, ensuring consistency and accuracy in data entry.

• Use Automation Tools

Leverage automation tools such as customer relationship management (CRM) software to streamline lead tracking processes, minimize manual errors, and ensure data integrity.

• Regular Data Cleansing

Conduct regular audits of lead data to identify and rectify inaccuracies, duplicates, and outdated information, maintaining a clean and reliable database.

• Train Sales and Marketing Teams

Provide training and ongoing support to sales and marketing teams on the importance of accurate lead tracking practices and the use of CRM tools effectively.

• Monitor Key Metrics

Continuously monitor key metrics such as lead conversion rate, lead velocity, and lead-to-opportunity ratio to assess the quality and accuracy of lead tracking efforts and identify areas for improvement.

Consistency in Lead Tracking

Consistency is paramount in lead tracking to ensure that no potential opportunities slip through the cracks. 

Here are some strategies for maintaining consistency in lead tracking

• Establish Clear Processes

Document standardized processes and workflows for lead tracking, outlining roles, responsibilities, and timelines to ensure consistency and accountability.

• Implement Cross-Departmental Collaboration

Foster collaboration between sales, marketing, and customer service teams to ensure seamless handoffs and continuity throughout the customer journey.

• Regular Communication

Facilitate regular communication and alignment between sales and marketing teams to ensure that lead tracking efforts are aligned with overall business objectives and strategies.

• Utilize Technology

Leverage technology solutions such as CRM software, marketing automation platforms, and communication tools to facilitate real-time collaboration and information sharing among team members.

• Monitor and Measure Performance

Track and measure key performance indicators (KPIs) related to lead tracking, such as lead response time, follow-up frequency, and conversion rates, to identify any deviations from established processes and address them promptly.

Lead Tracking: Enhancing Sales Efficiency

Lead tracking systematically monitors and records interactions between potential customers and a business throughout the sales process.

- Core Process: Captures every touchpoint from initial contact to final sale, offering insights into lead behavior and preferences.

- Key Benefits: Improves lead nurturing, enhances sales forecasting, and optimizes resource allocation.

- Strategic Impact: Enables personalized marketing and sales efforts, increasing conversion rates and overall efficiency.

Implementing effective lead tracking strategies helps businesses streamline their sales processes, improve decision-making, and drive sustainable growth.

Conclusion

As you can tell, lead tracking is all about understanding your audience, anticipating their needs, and delivering value every step of the way. It’s an indispensable tool for sales and marketing teams, enabling them to understand customer behavior, optimize lead generation efforts, personalize communication, and drive revenue growth. 

By using different methods of lead tracking, capturing relevant lead information, qualifying leads effectively, and integrating call tracking into the lead tracking process, businesses can maximize the value of their leads and achieve sustainable growth in today's competitive marketplace.

We hope this article helped you understand lead tracking and become an ally in your sales and marketing journey.

Happy Tracking!

With a market share of 83% and its brand name officially a verb in the dictionary, it's no secret that Google is the most dominant search engine on the planet. This, in turn, makes search ads or PPC one of the most popular marketing channels for marketers as well. In fact, as much as 65% of SME businesses run PPC search ad campaigns on Google — with nearly 80% of teams claiming it's a necessity for success.

That being said, Google ad campaigns are not without their drawbacks, especially for B2B marketers. Google ads primarily rely on keywords and searcher intent in deciding when and where to display ads. Account-based marketers, however, would rather have a say in who to display their ads too as well. 

For example, rather than blowing through budgets by displaying ads to everyone that looks up “CRM software”, an ABM marketer may prefer showing their ads only to a list of 1,000 specific target accounts. This way, wasted spends may be eliminated and bids may be raised, given the narrow target audiences. As it stands, however, Google supports a rudimentary and largely ineffective approach to audience building and segmentation for its ads. The following blog explores these limitations and highlights a better way to build audience segments with Factors.ai.

Let’s dive in.

As it stands: Google Ads audience targeting

Google Ads supports the ability to to reach people based on who they are, their interests and habits, what they’re actively researching, or how they've interacted with your business via Audience Segments.

How Audience Segments works

Google’s audiences are made up of segments of people with specific interests, intents, and demographic information based on Google’s database. Advertisers may choose from a wide range of segments such as “music fans”, “people shopping for bicycles”, or “people that have visited your website”. This data is estimated based on people’s engagement with Google’s own products and third-party websites. Specifically to Search ads, Google supports 4 types of Audience Segments:

1. Affinity segments: Reach users based on their passions, habits, and interests
2. Detailed demographics:  Reach users based on long-term life facts.
3. In-market: Reach users based on their recent purchase intent
4. Your data: Reach users that have interacted with your business.some text
   1. Website and app visitors: Reach people who have visited either your website or apps.
   2. Customer Match: Reach your existing customers based on your CRM data.‍
   3. Similar segments: Reach new users with similar interests to your website visitors or existing customers.

In addition to this, Google also supports Custom Segments and Life Events as segment types for it’s other ad channels (Display, Videos, etc).

Limitations with Audience Segments

In theory, Audience Segments sound super valuable. Based on your selection of Audience segments, Google’s AI models will automatically choose the right audience to best fit the needs of your campaign. However, a closer inspection reveals inherent limitations with each of the four approaches: 

• Affinity segments, detailed demographics and in-market segments are primarily tailored for B2C and D2C use-cases. That is, they’re built to cater to audiences based on individual interests, as opposed to account-level buying intent. They may work well to identify and target “skiing enthusiasts”, these audience segments often struggle with “B2B SaaS teams looking for a CRM”.
• Your data audiences segments do a slightly better job in that they attempt to target audiences based on existing brand engagement. Still, it’s fraught with limitations. According to Google’s advertising policy, Google advertisers may only upload customer data, not prospecting data from their CRM. This is of course, extremely limiting given that the majority of your total addressable market may not be actively engaging with your brand. Furthermore, Google’s own retargeting capabilities are limited to a vague set of website visitors (via Google Analytics) as opposed to comprehensively enriched audiences across website traffic, LinkedIn ads, and other channels. 

That being said, if you provide Google enough data about your target audience members via Customer Match lists, it can spot your target accounts and serve them, and them alone, your ads.

‍Long story short, Google’s native targeting mechanisms exist by the name of Audience Segments. However, this isn't, in its current form, very helpful to B2B marketers. In the following section let’s explore how Audience Segments may be used as a jumping off point in tandem with an account intelligence and activation tool such as Factors.ai to make the most of your targeted ads.

Better Google audiences & targeting with Factors.ai

What if you could retarget existing customers with personalized ads on upselling opportunities? Or vary your bids based on buying stage and ICP fitment? Or re-engage with long gone MQLs and lost opportunities with YouTube ads or GDN? These are a few examples of the powerful use-cases supported by Factors.ai for your Google Ads. Here’s how it works:

1. Identify and enrich: Factors identifies and enriches anonymous companies engaging with your website, LinkedIn ads, and G2 pages. These companies may be segmented via a combination of granular engagement and firmographic criteria within Factors. These segments may be as straightforward or involved as you’d like. A straightforward segment may look like: “US-based software companies” while involved segments may look like: “US-based software companies with 100-999 employees that have viewed at least one LinkedIn ad and visited the pricing page”. Create as many segments as you’d like depending on your intended objectives and granularity. 
2. Fire into Google Analytics: The next step involves firing relevant events (in this case, an event is an engaged company that matches your segment criteria) into Google Analytics. As you might recall, Google Ads will only retarget website visitors and contacts that have been recorded in GA or your CRM. Pushing these audience segments from Factors into GA acts as proxy to this. 
3. Push from GA into Google Ads: Now that you have built up segments in Google Analytics, it’s a simple matter to push said accounts into Google Ads for further targeting across search ads, videos ads, display ads, and more. Here are a few more ways in which you can use this flow:

How you can use Factors.ai + Google Ads

In addition to the aforementioned use-cases, here are a few more ways to leverage Factors.ai:

Variable RSA

Regardless of the size of your business, your marketing team is working with a budget. Accordingly, most marketers focus their efforts on specific, relatively low-volume keywords so as to not blow their budgets on irrelevant clicks from high-volume keywords. With Factors, however, you can have the best of both worlds by bidding on broader keywords and response search ads only for the companies you care about. For example, you may bid $2 for the long tail keyword “CRM software for US-based SMEs” but bid $6 for the short tail keyword “CRM software” only for the Audience Segment you care about. This way, the higher bid ads will be displayed only when your target accounts are searching for it — as opposed to the entire internet.

Granular targeting 

Given marketing’s limited budgets, you could choose to focus your ad spend only on companies that meet a super specific engagement and ICP criteria as the one highlighted earlier (“US-based software companies with 100-999 employees that have viewed at least one LinkedIn ad and visited the pricing page”). This way, you know that your ads will be served only to highly engaged accounts with explicit buying intent. This smaller pool of target accounts also enables you to raise bids more aggressively given the focused scope of audiences.

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Cross-channel targeting

A key aspect of the account-based market is targeting (and retargeting) accounts across channels. At the moment, Google Ads only supports the ability to target accounts visiting your website or in your CRM. With Factors, this reach may be expanded to companies viewing your LinkedIn ads, engaging with your G2 pages, or simply part of your ABM target accounts list. These segmented accounts may then be automatically targeted across your search ads, display ads, videos ads, LinkedIn ads, mail outreach, and more with Factors’ code-free workflow automations. 

Google Ads' native audience segmentation offers basic targeting options like affinity, in-market, and demographic segments. However, these can be limiting for B2B marketers aiming for precision.

Here's how Factors enhances Google Ads targeting:
1. Custom Audience Segments: Factors.ai enables the creation of custom audience segments based on firmographic data, buyer intent signals, and CRM insights.
2. Benefits: This approach allows for more effective targeting of high-intent accounts, reducing ad spend waste and improving ROI.
3. Advanced Segmentation: Integrating Factors.ai with Google Ads facilitates advanced audience segmentation, aligning marketing efforts more closely with sales objectives and enhancing overall campaign performance.

If you’re part of a sales team, chances are you’ve considered paying for LinkedIn Sales Navigator at some point. LinkedIn Sales Navigator seemingly ticks all the boxes– whether it's accurate data, intuitive, time-saving prospecting, or effortless sales outreach". But do its features justify its steep pricing? 

In this blog, we take a close look at LinkedIn Sales Navigator, its pricing, features, benefits, and limitations to see if you should invest in the platform.

What is Linkedin Sales Navigator?

LinkedIn Sales Navigator is a valuable tool for sales professionals and businesses, It facilitates lead generation and relationship management on LinkedIn. 

With Sales Navigator’s features, users can efficiently target promising prospects and stay informed about their activities and organizational changes. As compared to the basic/free plan, sales navigator is far more robust. It provides additional data that helps optimize sales strategies as and when the opportunity presents itself:

LinkedIn Sales Navigator Features:

1. Personalized lead recommendations: Sales Navigator offers tailored lead suggestions based on criteria like industry, company size, and job title preferences.

2. Advanced search functionality: Conduct detailed searches using filters such as location, job title, and company size to pinpoint prospects matching your ideal customer profile.

3. Account and lead insights: It provides valuable insights into prospects, including recent LinkedIn activity, company news, and job changes, aiding in better understanding and engagement.

4. InMail messaging: It helps you reach out to prospects via InMail, even without prior LinkedIn connections, expanding your outreach capabilities.

5. Sales Navigator Pages: Utilize customizable pages to track, save, and receive real-time insights on leads and accounts, optimizing your sales strategies.

You’re probably thinking “But this sounds suspiciously similar to LinkedIn Premium”. Well, you’re not entirely wrong. While they do aim to provide similar benefits such as access to InMail etc, they do have some differences:

What is the difference between LinkedIn Premium and LinkedIn Sales Navigator?

LinkedIn Premium is a whole lot cheaper and seemingly offers similar benefits. Considering you can get LinkedIn Premium at 1/3rd the price, LinkedIn Sales Navigator cost sure seems a bit much. But when it comes to prospecting and outreach in particular, Sales Navigator has so much more to offer. 

LinkedIn Premium is designed for a broader audience, including job seekers and recruiters, and offers features such as increased InMail credits, the ability to see who viewed your profile, and access to valuable training courses. 

On the other hand, LinkedIn Sales Navigator is designed specifically for salespeople. Accordingly, it offers advanced search filters, lead recommendations, and granular analytics. So, while LinkedIn Premium may be a good choice for job seekers and recruiters, LinkedIn Sales Navigator is certainly the better choice for salespeople.

Let's pit these two against each other:

Why choose LinkedIn Sales Navigator? 

Given its reputation and popularity, LinkedIn has to be one of the best social selling tools for B2B businesses. 134.5 million people use LinkedIn daily. It's the first place you go to when you want to post a career update, look for new teammates, or simply post company news. Social selling is a great way to supplement traditional channels. Social selling cannot replace these channels. 

The community and trust are certainly the primary appeal of the platform. Here are some other benefits of using LinkedIn Sales Navigator:

Advanced Filters

LinkedIn Sales Navigator has more than 40 advanced search filters. You can filter your search based on company, role, workflow, and keywords. What's unique about this feature is its spotlight filter option. Here are some of them: 

1. The Job Changes spotlight identifies prospects who have changed jobs within the last three months.

2. The Shared Experiences spotlight uncovers prospects who attended the same schools, worked at the same companies, or belong to the same LinkedIn Groups as you.

3. The LinkedIn Activity spotlight shows prospects who have posted or shared content on LinkedIn in the past 30 days.

4. The Mentioned in the News spotlight uncovers prospects who have been mentioned in the news in the past 30 days.

5. The Leads that Follow Your Company spotlight uncovers prospects who follow your company on LinkedIn.

6. The TeamLink spotlight finds prospects who are already connected to your colleagues. (not available on all plans)

This feature establishes Sales Navigator as a great “social” selling tool, taking searches a step further and helping sales teams establish connections with leads. 

Recommended Leads  

LinkedIn recommends leads on Sales Navigator through three methods: on specific company pages, at the top of a lead's profile, and via a recommended leads list.

The Recommend Leads list in Sales Navigator offers an auto-generated list of up to 100 recommended leads based on past user activity, such as searches and saved leads. 

Note: This feature relies on AI and functions optimally with increased data input. Therefore, you need to save relevant leads to your lists manually. The more interactions and saved profiles, the more refined your recommended section becomes on Sales Navigator.

Intent Identification and Alerts

LinkedIn Sales Navigator helps sales teams identify buyer intent by monitoring their company interactions– if the prospect has connected with you or your team or if they’ve engaged with your LinkedIn Ads. It sends real-time alerts for each of these activities and helps you make the most of an opportunity. 

Note: you need to manually save prospects in a list to ensure you get alerts for activities on their account.

Smart Links

One of the best features of Sales Navigator is the smart link. It allows you to simply create their deck online using this feature on LinkedIn Sales Navigator or even upload an existing PPT. A smart link is shareable and trackable for opens and clicks so you won’t need to switch to your CRM or another software for analytics. 

This brings us to the final benefit of the tool: 

Performance Analytics

Sales navigator allows you to track user groups and performance trends– you can analyze usage patterns to pinpoint areas of improvement, such as low InMail acceptance rates. Your training programs can be tailored to address these gaps and enhance sales team proficiency.

LinkedIn Sales Navigator Cost

LinkedIn Sales Navigator has a tiered pricing structure. It has three plans: Core, Advanced, and Advance Plus. At the time of writing, the prices for each plan are as follows:

Here are the additional features you get with each of the pricing plans:

Limitations of LinkedIn Sales Navigator

While there are numerous benefits of using Sales Navigator, users have reported some issues with the following:

1. Steep Learning Curve

Some users may find Sales Navigator to have a steep learning curve, especially if they are new to LinkedIn or CRM tools. It may require significant time and effort to fully grasp and utilize all the platform's features effectively, and the complex user interface needs to do more to help. It potentially delays the realization of its benefits apart from taking a lot of resources to set up.

2. Limited InMail Credits

While Sales Navigator provides InMail credits, users are allocated a limited number of Inmail credits each month. 

Once you exhaust these credits you need to purchase additional ones or upgrade your plan, adding to the overall cost of using the platform and potentially constraining outreach efforts.

3. Data Inaccuracy

LinkedIn's data, including contact information and job titles, is user-generated, leading to potential inaccuracies or outdated information in profiles. This can undermine the effectiveness of outreach campaigns and result in wasted time and resources.

4. Integration Challenges

Despite offering integration with popular CRM systems like Salesforce and Hubspot, some users encounter difficulties in setting up and maintaining these integrations. Sales Navigator's inability to expert lead or account lists is another challenge for users. These challenges can disrupt workflow efficiency and hinder seamless data management between platforms.

LinkedIn Sales Navigator Cost: Final Verdict

LinkedIn Sales Navigator is a premium service, which can be expensive for individual users or small businesses. This cost may pose a barrier to entry for some potential users, impacting adoption rates and accessibility.

When it comes to social selling, LinkedIn has a unique proposition that can’t be matched by other tools. It is an extension of a professional networking platform and provides insights on “shared experiences” and “commonalities” allowing you to build a rapport with your leads. So if you already have a prospecting or sales intelligence tool and you’re looking to add a social selling tool to your tech stack- we highly recommend LinkedIn Sales Navigator. 

Having said that, LinkedIn Sales Navigator leaves you wanting more in terms of data accuracy and lead generation. Anecdotal evidence suggests it's clunky and has surface-level integrations with CRMs. So if you’re building your sales tech from scratch, we recommend you steer clear of LinkedIn Sales Navigator. Here are some tools we recommend instead- 

1. Factors.ai 

Factors.ai is a tool that facilitates account-based selling. It not only delivers industry-leading enrichment rates of up to 64% but also helps qualify and target the right accounts based on intent data. Factors.ai takes into account website engagement, intent signals, and firmographic information to qualify leads and expedite the sales process. 

In comparison, LinkedIn provides a detailed however limiting view of the customer journey, due to its primary focus on LinkedIn activity. Most of the decisions are made based on interactions with the product’s website, its social channels, G2 reviews, etc. Factors.ai (due to its partnership with Clearbit) provides an extensive database and accurate intent identification as well. 

If you want more than a primary database and prospecting solution, Factors.ai is a great tool that provides analytical insights that help you identify target and close leads. 

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2. Cognism 

Cognism serves as a sales intelligence solution and data provider, offering cell phone numbers, direct dials, and emails across multiple regions. Its browser extension operates seamlessly across various corporate websites, including LinkedIn.

In contrast,  LinkedIn Sales Navigator is effective for targeting prospects active on the LinkedIn platform, aiding in the identification and connection with decision-makers within an Ideal Customer Profile (ICP). It provides access to public emails and phone numbers of these prospects.

Moreover, Cognism boasts phone-verified mobile numbers, ensuring an 87% connection rate with listed contacts. This surpasses LinkedIn's reliance on user-provided data, which, as indicated by Sales Navigator reviews, may lead to data inaccuracies and user frustration.

If you are looking for a global database and want to reach out to decision-makers through the same solution, Cognism is a great choice for you.

3. Zoominfo

Zoominfo is a leading B2B data provider and is a suitable alternative to Sales Navigator- 

LinkedIn Sales Navigator is specialized for targeting known prospects, while ZoomInfo excels at identifying decision-makers within targeted accounts. Sales Navigator emphasizes specific personal details, sourced from user updates, whereas ZoomInfo offers more up-to-date macro-level data, collected from web scraping.

Sales Navigator enhances contact targeting with network tools and professional news updates, while ZoomInfo facilitates bulk contact list exports and offers additional tools like ZoomInfo Engage, Chorus, and Chat for comprehensive sales support. If you are looking for a tool that puts equal emphasis on collaboration along with sales prospecting and lead generation- Zoominfo is the way to go. Competitors like Factors.ai are more powerful account intelligence solutions that can make your lead generation cycle seamless. Know more about Factors.ai here.

Is LinkedIn Sales Navigator Worth the Investment for Lead Generation?

LinkedIn Sales Navigator offers advanced search filters, lead recommendations, and in-depth analytics to enhance social selling.

Key features include:

1. Spotlight Filters & Smart Links: Identify high-intent prospects and personalize outreach.

2. Advanced Search & Lead Lists: Segment and track ideal buyers efficiently.

3. Intent Data & Insights: Prioritize leads based on engagement signals.

However, challenges like a steep learning curve, data inaccuracies, and integration issues may impact usability. While Sales Navigator is a powerful tool, its high cost might not suit every business. For greater data accuracy and expanded lead generation, alternatives like Factors offer competitive solutions.

For eons—or at least what felt like it—artificial intelligence (AI) lingered on the fringes of our daily existence, hovering like a futuristic mirage that seemed always just out of reach. That is, until it bulldozed its way into the mainstream, proving to be not just a fleeting fascination but a fundamental shift in the way we approach business, technology, and, indeed, life itself.

Suddenly, AI is not just for the nerdy elite or the futuristic dreamers. It's also for the pragmatic marketer who wants to decode the enigma of customer behavior, tailor experiences to perfection, and, yes, finally figure out what B2B customers actually want before they do. This could explain why, presently, a whopping 84% of B2B marketers are either leveraging AI, planning its integration, or eyeing it with keen interest.

But despite AI's proven prowess and the buzz that surrounds it, the leap from acknowledgment to action remains a chasm many businesses are hesitant to cross. That's why, in this blog, we'll take you through the lens of AI in B2B marketing, exploring not just the "what" and the "why," but the all-important "how."

So, without further ado, let's get started!

What is AI?

At its core, AI in the B2B arena is about leveraging machine learning, natural language processing, and other sophisticated algorithms to analyze data, predict trends, automate tasks, and enhance decision-making processes. It's about transforming raw data into gold—insights that fuel smarter strategies, more engaging content, and ultimately, sales that don't just close but smash expectations.

Unpacking AI's Appeal in B2B Marketing

Why are so many B2B marketers turning to AI? Let's dive into how leveraging AI for customer insight mining can revolutionize your B2B strategy.

Real-time Feedback Monitoring

Imagine a world where your business can adapt its strategies at the speed of conversation. AI transforms this into reality, offering a continuous stream of customer feedback across various platforms. It's like having a conversation with the market itself—dynamic, ongoing, and incredibly enlightening. In turn, this agility ensures your strategies are always in lockstep with customer expectations, fostering a level of trust and loyalty that's the stuff of marketing dreams.

Effective Product Development

With AI, every customer interaction becomes a clue to unlocking the next big innovation. The AI listening tools meticulously comb through the vast expanse of digital discourse, seeking out the precious nuggets of customer insights—those unarticulated wishes that'll herald your next breakthrough. This visionary approach guarantees that your inventions transcend mere market expectations to foresee them, establishing a foundation for offerings that not only echo with your target demographic but also sculpt the contours of the industry anew.

Enhanced Sentiment Analysis

AI goes beyond mere words, delving into the finer points of customer sentiments. It reads between the lines, picking up on the subtleties of tone and context that most old-school analysis tools would totally overlook. This deep dive into the emotional undercurrents of your customer base allows for a nuanced approach to customer engagement, transforming mere interactions into genuine moments of connection.

Elevated Pricing Acumen

Pricing isn't just about covering costs and adding a markup. Thanks to the advent of AI tools, enterprises can now embrace dynamic pricing models that intelligently adapt to market fluctuations, competitive landscapes, and the ever-evolving perceptions of value among consumers. This sophisticated approach ensures that pricing is perpetually poised at the sweet spot—maximizing both sales volume and profit margins by balancing the scales of affordability with the allure of perceived value.

Continuous Improvement

AI is the perpetual motion machine of business improvement. It continuously feeds on customer data, offering fresh insights that drive ongoing refinement and innovation. This relentless pursuit of enhancement fosters a culture steeped in excellence, cascading through every stratum of your organization. It positions you not merely as a player but as a trailblazer, fostering a culture of agility, responsiveness, and forward-thinking that keeps businesses at the pinnacle of their game.

Example of AI Tools That Are Changing the Marketing Game

The AI toolbox is vast and varied, but here are five tools that are making significant inroads in the B2B marketing arena:

ChatGPT for Conversational AI

Chatbots and virtual assistants have come a long way from their humble beginnings as rigid, scripted responders. This AI-powered chatbot can engage in conversations so fluid and human-like that you might just forget you're talking to a machine. ChatGPT's proficiency in learning from and adjusting to dialogues in real time epitomizes the blend of technical sophistication and intuitive functionality that marks a new era in customer interaction.

Freepik AI Image Generator

Freepik AI image generator stands as a notable advancement in the realm of digital design and content creation. Leveraging cutting-edge AI image generation technology, it offers users the ability to generate unique and high-quality AI images based on textual descriptions and in different styles, including digital art, anime, vintage, AI photos. Freepik AI Image Generator is particularly beneficial for graphic designers, marketers, content creators, and anyone who seeks to produce visually compelling images without the necessity for extensive design skills or resources. 

OneUp

Keeping your social media presence vibrant and engaging is a full-time job. AI-based tool OneUp makes this task not only manageable but downright enjoyable. It automates the scheduling of posts across a plethora of platforms. From the professional plains of LinkedIn to the community-focused spaces of Facebook groups, it even allows for posting to multiple GMB locations. With OneUP, your digital presence is always buzzing, always relevant, and unbelievably streamlined.

Zapier

Zapier acts as the glue that binds different web applications together, enabling a seamless flow of information between them without the need for custom coding. Want to add new email subscribers to your CRM automatically? Or perhaps trigger a welcome email sequence upon a new lead entering your system? Zapier makes these tasks, and countless others, not just possible but effortlessly simple. 

Salesforce Einstein

Rounding off our lineup of innovative AI tools is Salesforce Einstein, a CRM assistant that uses machine learning to personalize customer interactions, run sales data analytics, and predict future behavior. Einstein's AI capabilities are integrated across the Salesforce platform, making it smarter and more predictive of your customers' needs and desires. From sales and service to marketing and commerce, Einstein ensures every customer touchpoint is informed, insightful, and impactful, elevating the customer experience to new heights.

Stroydoc

The Storydoc marketing & sales collateral management platform is set to transform the way modern marketing and sales teams create content and how this content is consumed. This tool is built on an advanced AI engine to tailor any content to the target audience to maximize its business impact. Storydoc collateral can be automated and finely personalized through advanced integrations with CRM, sales, and marketing tools. Storydoc significantly accelerates content creation, improves engagement, removes friction from the sales funnel, and gives whoever uses it a significant edge.

How to overcome the AI Integration Hurdle?

The path to AI integration is undoubtedly compelling, lit by the promise of efficiency, personalization, and insight. Yet, it's also strewn with obstacles that can trip the unwary. Here's how savvy B2B marketers are leaping over these hurdles, turning potential pitfalls into stepping stones toward innovation:

Data Privacy

As marketers, it is our duty to do no harm and respect the sanctity of the data entrusted to us. This means conducting rigorous data impact assessments to determine the necessity of every byte of data collected. Anonymizing data where possible, providing clear opt-out options, and explaining your data use policies in plain, jargon-free language are steps that demonstrate respect for privacy and autonomy. 

Another layer of safeguarding this trust involves adopting penetration or vulnerability testing platforms. Think of these platforms as the digital equivalent of a health check-up for your data security - they poke, prod, and push to uncover any weaknesses before the bad guys do. By regularly subjecting your systems to thes cyber check-ups, you can patch vulnerabilities, fortify your defenses, and ensure your data practices are as ironclad as they claim to be.

Equity and Accessibility

AI has the potential to personalize the customer experience in ways previously unimaginable. However, this promise of personalization must not come at the cost of equity. The reality of data disparities can lead to uneven benefits, concentrating advantages among certain groups while sidelining others. 

Proactively design your AI models for equity, ensuring data samples are inclusive and benchmark tests for fairness are routine. This approach not only broadens your market reach but also champions a more inclusive digital ecosystem.

Skill Gap

The world of AI can seem daunting with its jargon and complexities. But here's a secret: you don't need to be a tech wizard to harness AI's power. Many AI tools today are designed with user-friendliness in mind. 

Think of it as learning to drive; it might seem complicated at first, with all those pedals and the steering thing, but with practice, it becomes second nature. Additionally, partnering with AI providers who offer robust support and training can further smooth the learning curve, making AI integration a less Herculean task.

Accountability and Responsibility

It's essential to draw clear lines of responsibility, ensuring that there's always a human in the loop, ready to take the helm should the AI veer off course. This isn't about undermining AI's capabilities but about ensuring that its power is wielded with wisdom and oversight. 

Document models comprehensively, establish rigorous oversight procedures across departments, and ensure there are policies in place for reporting unethical AI behavior. This framework of accountability ensures that AI serves your audience's needs ethically and responsibly, reinforcing your brand's integrity.

Marketing Data and Tool Security

The responsibility of safeguarding access to your AI tools and the marketing data they hold falls squarely on the shoulders of businesses. Employ AI tools designed with privacy in mind while encrypting and authenticating your data. 

Moreover, embracing innovative security measures like QR codes for access control adds an extra layer of defense, ensuring that the keys to your AI tools are well-guarded yet readily available to those authorized. However, the performance of this mechanism hinges on the reliability and integrity of the free QR code generator used. Opt for generators known for their robust security features to ensure the gateway to your marketing data remains impenetrable to invaders.

AI Tool Allocation

Ensuring that your cutting-edge AI tools don't become a cause of high-tech tug-of-war between different marketing departments requires a blend of diplomacy and strategy. The secret to avoiding a digital debacle? Transparent communication and straightforward guidelines on who gets to play with the cool tech toys and when. You can achieve this by setting up a centralized AI tool management hub, where access and allocation can be monitored and adjusted based on real-time needs and results. 

You can also use resource management tools like ResourceGuru or Float to make this process simpler. These platforms are the go-to solutions for B2B agencies and businesses craving to dish out their tech treasures without causing a booking brawl. By deploying them, you ensure that your AI goodies are spread evenly across the board, allowing every team to bask in the glow of AI enlightenment without tripping over one another's power cords.

Setting a Course for B2B Marketing Success with AI

Remember, the future belongs to those who are ready to embrace change, and in the realm of B2B marketing, that change spells A- I. Don't be left behind, wondering what happened. Jump on the AI bandwagon and watch your marketing strategies transform from bland to brilliant. After all, who doesn't want to be a part of a future where marketing is not just about selling but truly connecting?

The Challenge With Google Search Ads

Search advertising has established itself as the go-to channel for B2B marketers to capture low-hanging demand — and it’s easy to see why. As a marketer for an account intelligence product such as Factors.ai, it makes sense for me to bid on product keywords such as “ABM software” or “visitor identification tools” and competitor keywords such as “leadfeeder alternatives”, so I can attract relevant, in-market customers based on searcher intent. 

That being said, a closer look at the numbers reveals that conversions from search ads can actually be pretty disappointing (and expensive). For context, the average click-through rate (CTR) for search ads across industries is only about 3.17%. It’s even slimmer in the technology industry, at a meager 2.09% (Wordstream). Out of the few ad impressions that do translate into clicks, the average landing page conversion rate (sign-ups, demo form submissions, etc) is around 6% (HubSpot). And of the handful of visitors who do convert, only a fraction go on to become SQLs, opportunities, and ultimately, customers. 

Even the most optimistic benchmarks find that:

• Only around 30% of Leads become SQLs
• Out of which, 40% of SQLs become opportunities
• Out of which, 30% of opportunities become customers 

There are countless reasons for such significant drop-offs along the sales funnel:

• Most lead that land on your website, won’t sign-up
• Leads that do sign-up, may not schedule a meeting 
• Leads that do schedule a meeting, may not show up 
• Leads that do show up, may not be qualified (non-ICP)
• Leads that are qualified, may not be sales-ready (timing, budget, etc)
• Leads that are sales-ready, may choose to go with an alternate solution

All these factors suggest that to earn a single customer from search ads, you’d need more than 500 paid clicks (of course, this number varies widely based on category). That’s a lot of clicks…and a lot of money. 

To solve for this, marketers typically rely on three levers: 

1. Improve ad performance by optimizing keywords, budgets, etc
2. Improve website conversions with conversion rate optimization (CRO)
3. Improve quality of clicks via Google Click ID (GLCID) and conversion feedback

In this article, we’ll be exploring the latter of the three. Specifically, we’ll highlight an improved approach to training Google Ads to find the right clicks and traffic for your business via GCLID and conversion tracking. But first, let’s briefly discuss the current approach to Google conversion tracking — and its limitations. 

Google Conversion Tracking & GCLID: As It Stands

As a B2B marketer, you’re probably familiar with how conversion tracking and GCLID work to share conversion feedback with Google, but here’s a quick refresher:

Not all ad clicks are equal. A buyer that matches your ideal client profile is probably more valuable to your business than a student looking for an internship. However, to Google and other ad platforms, a paid ad click, regardless of whether it's by a buyer, a student, or a competitor, is a paid ad click.

To avoid the risk of burning through budgets on irrelevant paid engagement, Google supports the ability to digest feedback on the quality of clicks based on Google Click ID (GCLID) and preconfigured conversion actions. Via GCLID, Google assigns each click with a unique identifier. If the user behind a specific click goes on to perform a favorable action, marketers can flag that click to Google as a “high-quality lead”. Google’s algorithm then harnesses countless factors and historical records from its own database to surface your search ads to other audiences that match this criteria for a “high-quality lead”. Marketers typically tag sign-ups, MQLs, SQLs, and opportunities as favorable conversion actions. This lead-level feedback improves the quality of audience that receive your ads, which in turn, improves conversions. 

In theory, ad optimization with conversion tracking and GCLID sounds fantastic — a feedback loop between advertiser and advertising platform to continually improve ad performance and conversions. That being said, there are two challenges with Google Conversion Tracking and GCLID as it stands today:

1. Limited data: Google Ads recommends at least 30 conversions in 30 days for its algorithms to take effect in understanding what’s valuable and what’s not. In fact, for minimum CPA fluctuation and a quick learning period, Google suggests a whopping 500 conversions in 30 days. For early and mid-stage companies that are yet to hit these volumes of conversions, this lack of data can be a limiting factor. 
2. Lagging metrics: B2B sales cycles are notoriously lengthy and non-linear. After a visitor submits a demo form, for example, it might be a couple of days before their demo call, a few weeks before they become an opportunity, and more than a month before the deal is closed. Given that most marketers prefer quick iterations and experiments to squeeze the most ROI out of their campaigns, these extended periods between conversions lengthens the feedback loop when sending lead-level data back to Google. This lagging lead metrics is another limiting factor. 

With bids and cost per clicks becoming increasingly expensive as a result of growing competition, we need a fresh approach to overcome limitations with lead-level conversion tracking. Our hypothesis? Leverage traffic-level conversions to ensure sufficient, leading data availability for Google to work with.

Traffic-level Conversion Tracking: A Better Approach

Most marketers typically use sign-ups, M/SQLs, or other lead-level conversions as their conversion action goals. However, as noted earlier, only about 6% of visitors typically submit a form, with fewer still converting down funnel, after a delay. This results in small, lagging data sets for Google to work with. 

Rather than sending back lagging conversion data for 6 out of a 100 visitors on your paid landing pages, what if you could send leading data for 60? This is exactly what Traffic-level conversion tracking seeks to achieve via IP-based account enrichment, engagement tracking, workflow automations, and GCLID.  

Here’s how it works

Even though only a fraction of the traffic on your paid landing pages will sign-up, there’s still variable value in the remaining ninety something percent of visitors that are yet to convert. Say that 10 visitors land on your website from a search ad. Out of these 10, 2 are in-market ICP buyers that immediately sign up. 5 are ICP buyers that would make a good fit for your business, but decide that now is not the best time for a demo, so they drop off without submitting a form. And 3 are non-ICP visitors: a student, a job seeker, and a competitor — who also drop off without submitting a form.

The typical approach suggests sending the 2 ICP visitors that converted back to Google Ads as feedback. While this is helpful, it doesn’t encapsulate the full extent of data collected here. It fails to acknowledge the 5 clicks (50%!)  that albeit didn’t convert but matched our ideal client profile. While these clicks may not be as valuable as the 2 ICP clicks that converted, they’re certainly more valuable than the Non-ICP clicks. If ICP converted is worth $20, ICP not converted could be worth $10, while Non-ICP could be worth $2. This is valuable data for Google to make sense of ad clicks, even in cases where an explicit “conversion action" may not have taken place. By supplying Google with a larger set of relevant data, its algorithms will have a better understanding of what kind of visitors you value most. This data needn’t be limited to ICP data (firmographic) alone; it may be based on engagement (time-spent, scroll%) as well. 

Accordingly, traffic-level conversion tracking seeks to identify, qualify, and feed Google with a larger volume of granular, leading data by de-anonymizing website traffic and engagement at an account-level. This is where an account intelligence tool (*ahem* Factors.ai) comes into the picture.

How Factors Fits In: Your Data + Our Data = Ad Magic

The process we’re exploring here involves identifying website traffic, qualifying that traffic based on their firmographics (for ICP fit) and engagement (for intent fit), and pushing that data back to Google as feedback to attract better, more relevant audiences that *we hope* improves conversions and pipeline. Accordingly, we’ll need the following:

1. An IP-based intelligence tool to identify and enrich landing page traffic at an account-level 
2. Assign conversion value to incoming traffic based on your ICP and engagement criteria 
3. Automate a workflow that pushes this traffic-level conversion data to Google

As luck would have it, Factors.ai supports all three requirements with industry-leading account identification, engagement scoring, and workflow automations. Here’s an example of what a Factors-powered Search ads conversion tracking process could look like:

1. Identify up to 64% of anonymous companies landing on your website via search ads but are yet to convert 
2. Qualify and segment identified companies based on firmographics (industry, size, etc) and engagement (time-spent, scroll-depth, etc)
3. Push traffic-level conversion action data (along with lead-level data) back to Google automatically with the likes of Make, Zapier etc 
4. Google leverages a larger set of leading data to improve the quality of clicks and traffic
5. Improved audience quality results in better conversions and cost-effectiveness

Interested to see it in action? We’d be more than happy to set up a similar process for you over a trail with Factors.ai.