Ranga Kaliyur

HockeyStack Pricing, Overview & Comparison

December 18, 2025

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0 min read

Pixel vs Account-based LinkedIn Retargeting

December 18, 2025

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0 min read

B2B marketing teams invest significantly across campaigns and content to drive qualified website traffic. However, benchmarks find that only about 2% of this traffic actually converts, with the majority of visitors simply bouncing off or browsing anonymously on the website.

Retargeting the remaining 98% of visitors via LinkedIn has proved to be an effective strategy to recapture interest from anonymous website traffic. While we won’t cover the specific benefits of LinkedIn retargeting here, this case study summarizes how Sage successfully leveraged LI retargeting to:

Generate 700,000 impressions in 6 weeks
Improve lead generation by 4x
And reduce cost-per-lead (CPL) by 80%

Simply put, LinkedIn retargeting works.

LinkedIn retargeting relies on the LinkedIn Insight tag (aka LinkedIn Pixel) to match website visitors with LinkedIn audiences.

The LinkedIn insight tag is a simple piece of code placed on a website to help optimize campaigns. While the LinkedIn Pixel serves many functions, including conversion tracking and demographic insights, it’s challenged by shortcomings around website retargeting.

While LinkedIn Pixel works to some extent, we have found an alternate approach that can take your retargeting campaigns to the next level, also known as account-based retargeting. Account-based retargeting works by identifying, qualifying, and targeting anonymous accounts, as opposed to individual users visiting a website. Using a combination of identifiers, account-based retargeting has been shown to deliver:

Larger, account-level audiences
Improved match rate accuracy
Better segmentation and targeting

And the results? Well, they speak for themselves:

LinkedIn pixel vs account based retargeting performance

While the LinkedIn Pixel is a must-have solution given its wider functionality, we explore the limitations of Pixel-based retargeting and why Account-based retargeting is an effective alternative ⬇️

Limitation #1 - Match rates

The LinkedIn Pixel works by placing a cookie in visitors’ browsers, so when a LinkedIn user lands on your website, they may be identified and retargeted on LinkedIn. Note that this cookie-based identification takes place at a device and browser level for individual users. This means that, for the Pixel to match a website visitor to a LinkedIn user, the visitor must meet all 4 of the following criteria:

Be an active member of LinkedIn
Explicitly accept cookies on the website
Use the same device (phone/laptop/tablet) to visit the website and LinkedIn
Use the same browser (chrome/firefox/safari) to visit the website and LinkedIn

While a few visitors will probably fit this criteria, audience match rates via the Pixel are limited by the fact that the majority of traffic either doesn’t use LinkedIn, rejects cookies, or, most commonly, uses different devices/browsers for product research and LinkedIn browsing.

In fact, only about 42% of B2B product research involves mobile touch points — with the majority of B2B buyers choosing to conduct their research on desktops. On the other hand, a whopping 80% of LinkedIn engagement is via mobile. This is not surprising, given that LinkedIn is primarily a social networking app.

And so, despite the fact that LinkedIn Pixel works as designed, its match rates tend to be relatively poor, given the practical realities of B2B user behavior.

The limitation: Low match rates as a result of limited, cookie-based matching mechanisms by the LinkedIn Pixel.

How Account-based Retargeting helps

The LinkedIn Pixel relies exclusively on cookie-based tracking to create its matched audiences. Factors, on the other hand, leverages a combination of three identifiers — IP address, advertising ID, and cookies, to triangulate a data connection and match anonymous traffic to a company.

Factors connects with over 4.2B+ IP addresses and 65M+ company profiles (in addition to cookies and ad IDs) to accurately identify which accounts are visiting your website. Note that this is regardless of whether the visitor in question is a member of LinkedIn, uses different browsers, etc.

In fact, Factors can also identify remote companies by initially cookie-ing people using their corporate IP address to then re-identify them when they work remotely. To further explain how Factors achieves industry-leading match rates, here’s Viral from 6sense, one of our data partners:

“As a person moves around, their IP address changes. The platform adjusts for these changes by pulling in several additional markers to help match signals to an account. Now, with more variations in IP address data as remote working spreads across industries, our Graph deploys available secondary marker information, like cookies and mobile advertising IDs, to triangulate data connections. The Graph uses additional markers to sift through the noise so that confidence in the match rate remains consistent. Given the amount of signals we track, we don’t map every signal all the time, but we have observed accuracy over 85%.”

- CTO Viral Bajaria, 6sense, Data Partners

‍💡Build Better LinkedIn Retargeting Audiences with Factors‍

Limitation #2 - User-level targeting

B2B buying decisions are rarely made by a single person. The typical buying committee comprises almost a dozen people from multiple departments and time zones. Selling a SaaS product today might involve gaining buy-in from multiple C-suite executives, individual stakeholders from operations to sales to marketing, and a chief revenue officer – along with legal and implementation teams.

Source: Challenger

Given that the Pixel focuses on individual, single users visiting your website, it fails to capture the wider buying group from each account those users are from. This shrinks your total matched audience size considerably, but more importantly, it inhibits your marketing efforts from reaching key stakeholders and decision-makers who may not have been the ones visiting your site.

For example, if a junior marketer visits Factors.ai and is retargeted by the LinkedIn Pixel, the junior marketer alone will receive ads — with other stakeholders from the target account being ignored. As a result, this approach relies on the junior marketer being independently influential enough to convince the rest of the team to move forward with the deal. Definitely a tough sell.

The limitation: User-level targeting, as opposed to account-level targeting, results in fewer stakeholders targeted per account and smaller audience sizes.

How Account-based Retargeting Helps

While LinkedIn is best for targeting buying groups, it’s important to remember that there is no initial intent to buy on a social media platform. You need to layer in intent signals from multiple sources, such as your website and review sites like G2, to understand how you can best retarget relevant accounts.

Factors identifies intent signals and re-targets anonymous website traffic at an account level. This means that multiple decision-makers and stakeholders from the same company will be targeted on LinkedIn, regardless of which user actually visits the website. This bodes well for multiple reasons:

Increases audience size without compromising on the quality of accounts
Creates brand awareness at a company level rather than at an individual level
Improves odds of targeting the right decision-makers within each account

Even assuming that account-based targeting finds the same 100 accounts as Pixel-based targeting, the former would generate an audience size of 300-500 users (3-5 people from each account), while Pixel-based targeting would only target 100 users (1 from each account). More importantly, a larger audience will improve the odds of targeting decision-makers, ultimately resulting in more leads and conversions. Accordingly, account-based retargeting solves for the practical limitation of LinkedIn campaigns struggling to scale due to poor audience size.

Limitation #3 - Audience segmentation

The previous two points discussed the LinkedIn Pixel’s limitations in terms of audience quantity. This third limitation highlights why the Pixel tends to fall short in terms of audience quality. In reality, a significant portion of your website traffic wouldn’t make a good fit for your business. Even within the subset of ICP accounts visiting your website, only a fraction would be “sales-ready” at any given moment (with the remaining accounts having to be nurtured until they’re prepared to buy).

sales-ready ICP accounts visiting your website set diagram

As important as having a large audience is, the quality of this audience plays a key role in determining conversions and RoAS as well. In an ideal scenario, marketing teams should only retarget this subset of sales-ready “3000-pound marlin” accounts.

The LinkedIn Pixel limits audience segmentation based on intent and engagement. With the Pixel, website traffic can only be segmented based on page views. While this is definitely a good starting point, it lacks granularity.

With Pixel, filtering out accounts that don’t match your target geographies, industries, sizes, or engagement levels can be challenging. This also translates to limited personalization options, as you can only segment campaigns by page views rather than by account and engagement properties.

The limitation: Limited segmenting & filtering options resulting in subpar audience quality and limited scope for personalization.

How Account-based Retargeting helps

Account-based retargeting with Factors supports granular segmentation based on a wide range of firmographics and engagement criteria. For example, with Factors, you can identify and retarget a list of accounts that meet the following rules:

“US-based Software companies with 100-500 employees visiting our pricing page & G2 profile for at least 10 seconds with a scroll-depth of 20% or more”

Here are a few ways in which Factors helps segment traffic data (in addition to regular old page views):

Country
City
Industry
Size
Revenue range
Time spent on page
Scroll-depth
Button clicks
And a combination of all of the above

‍This level of filtering results in a list of precisely targeted ICP accounts that would make a great fit for your business. Additionally, by integrating your CRM, you may also include/exclude specific accounts, such as existing customers and competitors.

And guess what? We found the solution to fix your list-building problems once and for all!

Factors has launched Audience Builder, which allows marketers to automatically segment based on their preferred criteria, push these segmented audience lists to LinkedIn, and activate personalized, targeted advertising.

For example, you may choose to show accounts that visit high-intent pages such as factors.ai/pricing an ad creative offering a free trial. On the other hand, you can show accounts reading your competitor comparison blogs a “comparative” ad creative. The possibilities are endless.

free trial based LinkedIn retargeting ad

Real-life comparison: Pixel vs Account-based retargeting

We’ve talked the talk - now we’ve got the numbers to back it up. Here’s how two campaigns, one that’s Pixel-based and another that’s Account-based, compare to each other. Note that all else (duration, budgets, creatives, copies) has remained the same through the course of this experiment.

Over the same period, we find that CTR is higher under Pixel-based retargeting, likely because this approach targets exact users visiting the website. That being said, Account-based remarketing significantly outperforms Pixel-based retargeting in every other key metric, including leads generated.

And there you have it.

Solve your ad targeting woes with AdPilot

If you want to maximise ROI for your LinkedIn ads, look no further than our latest offering: LinkedIn AdPilot! We offer a wide range of features that allow you to segment audiences based on intent data, implement exposure control for your campaigns and determine the true ROI for your ads.

Speak to our team today to understand how you can use AdPilot to improve your LinkedIn retargeting efforts.

LinkedIn's Pixel-based retargeting and account-based retargeting differ in their targeting approach and benefits. The LinkedIn Pixel, a code snippet placed on websites, tracks visitor interactions using browser cookies to retarget individuals. However, its effectiveness can be limited by users not accepting cookies, using different devices, or being logged out of LinkedIn. On the other hand, account-based retargeting targets entire organizations, identifying anonymous accounts visiting your site, which allows for better audience segmentation and higher match accuracy. While the Pixel is useful for general retargeting, account-based retargeting is more effective in B2B contexts, offering precise targeting and engaging multiple stakeholders in decision-making processes.

The Complete Guide To Customer Journey Mapping

December 18, 2025

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0 min read

Customers are complex. What drives them? What bothers them? What encourages them? And what convinces them to choose you over your competitors? Without a clear framework in place, answers to these questions remain nuanced and theoretical.

Here’s where customer journey mapping can help.

A customer journey map visualizes the entire customer experience with your company — from awareness to deal won, and sheds light onto why your customers behave the way they do at every stage of the sales cycle.

As we will see, customer journey mapping proves to be beneficial in acquiring more customers, faster — and retaining them for longer durations of time.

Here’s what this guide to customer journey mapping covers:

What is customer journey mapping?
How does customer journey mapping work?
Why do B2B companies need to map out their customer journeys?
What should you include in your customer journey map?
Steps to create a customer journey map
Customer journey map vs user experience map: what’s the difference?
How does Factors.ai help with customer journey maps?

What is customer journey mapping?

Especially in B2B deals, customers rarely make purchase decisions on an impulse. Instead, they spend significant time identifying pain-points, researching solutions, comparing alternatives, and freeing up budgets before finally becoming paying customers.

Customer journey mapping can be defined as the visualization of interactions that a buyer has with a company across the entire sales cycle — from awareness to deal won to retention. Customer journey mapping provides valuable insights to refine the overall customer experience, drive conversions, and improve customer retention rates.

In short, the customer journey map encapsulates this buyer experience. This journey can be broadly divided into: pre-conversion, onboarding, and post-conversion.

Each of these segments can be further broken down into granular customer touchpoints that the marketing, sales, customer success, and product team are responsible for.

How does customer journey mapping work?

There’s no one right way to go about customer journey mapping. But at its core, customer journey mapping works by consolidating and visualizing an otherwise complex, non-linear sales cycle.

With this framework, go-to-market teams can identify how customers behave, what their preferences are at each stage of the sales cycle, and what helps or hurts conversions.

As you might have guessed, plotting this customer journey map involves compiling data from a wide range of touch points across the sales cycle.

Without the right tools and techniques, tracking these touch-points across channels, campaigns, offline events, website, CRM and more can be a daunting task. More on how Factors.ai can ease this process later.

What should you include in your customer journey map?

While every business involves its own unique customer journey, a few key elements remain constant across the board. Here’s a breakdown of what you should look to include in your customer journey map.

1. Sales Cycle

Firstly, connect the dots between relevant data sources across campaigns, website, MAPs and CRM. This is to understand where your customers are coming from and how they’re engaging with your brand across the sales cycle.

The average B2B sales cycle can be broken down into the following stages:

Awareness (ToFu marketing, branding, etc)
Consideration (BoFu marketing, sales discovery, trials, etc)
Decision (Effective sales and customer success)

2. Customer Behavior

Based on the data collected from the previous point, gauge how customers behave at different stages of the sales cycle.

Let’s say that the data suggests that during the awareness stage, buyers look to learn more about the problem they’re facing. At this stage, educational material such as ebooks or webinars may be more relevant to customers as compared to bottom of the funnel material such as comparison articles or case-studies.

3. Sentiment

B2B deals tend to be perceived as unemotional, objective transactions. However, at the end of the day, B2B businesses still sell to people — buyers and users — within a business. Accordingly, it’s important to consider the sentiment of leads and buyers during every stage of the customer journey.

For instance, the problem-awareness stage may involve frustration or confusion that we should look to minimize with useful content and personalized outreach. The solution-decision stage may involve feelings of relief or happiness which should be maximized with reliable customer support and relevant documentation.

4. Problems

Carrying on from the previous point: For any negative sentiment, there’s probably a pain-point or problem behind it. Identifying these pain-points at various stages of the customer journey will help create pointed, relevant customer experiences that look to solve user problems.

5. Solutions

As previously mentioned, we can look to solve challenges and paint-points along the customer journey to reduce or eliminate any points of friction. This will ensure smooth sales conversions.

Why do B2B companies need to map out their customer journeys?

Creating a customer journey map, especially without the right tools, can be an unintuitive and daunting task. Why then should businesses care to go through all this effort?

The overarching reason for B2B teams to create customer journey maps is because of its positive impact on customer experience, conversion, and retention. Breaking down the customer journey into broad stages with individual objectives simplifies, and ultimately improves, an otherwise convoluted customer journey.

Here are a few specific ways in which customer journey mapping benefits the customer experience, which in turn benefits your businesses’ bottom line metrics.

1. Identify what resonates with your audience

Customer journey mapping helps identify how different messaging, content, topics and themes resonate with your target audience. While marketers tend to have a hunch about this, qualifying a hypothesis with data helps scale efforts confidently.

2. Refine personas and improve targeting

Targeting a broad audience isn’t effective or scalable in the long run. Customer journey mapping sheds light onto which customers are actually interested in the value of your product. This helps refine the characteristics of ideal customer profiles and allows marketing teams to go after targeted, high-intent audiences.

3. Improve customer retention rate

The customer journey map charts a course all the way into the product and its end-users. This provides valuable insights into who the product is helping most, and how it’s helping them.

With this end-to-end view of the customer journey, it’s clear to see where to improve the customer experience, even within the product. This is invaluable information given that a third of Americans consider switching to an alternative after a single poor experience.

Ultimately, improving the customer experience means improving customer retention. Which in turn lends itself to stronger pipeline and up-selling opportunities.

Steps to Create a Customer Journey Map

Here’s a step-by-step breakdown of creating a customer journey map from scratch.

1. Define customer journey objectives

The first step is to determine why you’re constructing a customer journey map. What’s the objective? Whose customer experience are you looking to improve? Based on this information, define 1-3 hypothetical buyer personas that represent your ideal customer profile.

Buyer personas should be based on a combination of firmographic features like industry, revenue, and headcount as well as user-specific characteristics like role, department, tech-stack, etc.

2. Survey prospects and customers

After defining your hypothetical “perfect customer”, it’s time to survey your actual prospects and buyers. This is mainly to close the gap, if any, between how you believe your customers think and how they actually think.

Here are a few questions to ask prospects and customers:

How did you hear about us?
What are you looking to solve for? What’s your biggest pain-point?
How would you rate our onboarding process on a scale from 1-10?
How do you think we can improve our website content?

3. Track customer journey touchpoints

While asking customers where they found us and how they like our product is all well and good — it’s rarely sufficient. For one, B2B sales cycles last several weeks, if not months. It’s hardly fair to expect customers to remember the exact social media post that drove them to your website.

For another, subjective interviews are often riddled with bias and leading questions. To avoid inaccuracies in data, it's crucial to independently track touch-points across campaigns, websites, MAPs, CRM, and other relevant sources for objective analytics. With this, we can find answers to questions like:

Which channel is driving the most traffic to my website?
Which blog topics lead to the most conversions?
What percentage of the pricing page are visitors scrolling through?
How are customers progressing from an ad campaign, to website, to demo, to deal won?

Consider the sentiment, pain-points, and solutions that are associated with every customer action in order to understand motivations and tailor marketing efforts efficiently.

For example, if a page on “Identifying website visitors” seems to be driving a lot of conversions, this may be a pressing pain-point or use-case to your audience. In this case, tailoring outbound efforts and organic social with more content on visitor identification may be fruitful.

4. Allocate resources across the customer journey

So far, we’ve defined who we want to sell to, identified what current customers are thinking, and tracked how these customers are interacting with our brand.

Based on this goldmine of information, we receive a rough idea as to how we can better allocate resources. For instance, maybe mapping out this data reveals that webinars seem to perform disproportionately better than paid social at driving high-intent visitors.

Alternatively, this customer mapping exercise may also reveal a dearth in specific tools that could help accelerate sales velocity – email automation, customer service management, etc.

The reallocation of resources that follows these insights will ultimately result in the first iteration of the customer journey map. A design that encapsulates who your ideal buyers are and the ideal path they’ll take to become paying customers.

5. Analyze the customer journey

At this stage, we’ve crunched a whole lot of customer data and allocated resources to optimize the customer journey. But this is just one half of the puzzle. Analyzing and iterating based on real-life results is crucial to the success of a customer journey map.

Look to answer questions like:

Where are customers dropping off disproportionately?
Which touch-points are driving higher-than-average conversions?
How does the quality of leads differ from one channel to another?

This is where the customer journey map graduates from theory to practice.

6. Iterate. Iterate. Iterate.

Using learnings from the analyses of the customer journey, run a wide range of experiments to test specific hypotheses at every stage of the sales cycle.

Perhaps reworking ad copies, repositioning CTAs on the website, investing in a customer service tool, updating the onboarding flow result in improved customer experience and conversions.

Rather than relying on intuition or guesswork, use the customer journey map to identify and iterate on strengths and limitations with data-driven insights.

Ideally, the customer journey map should be revised every month or quarter to stay aligned with every-changing customer behavior.

Customer Journey map vs User Experience map: What’s the difference?

In short, a customer journey map considers every measurable interaction that a customer has with your business from awareness to consumption. A user experience map, on the other hand, only considers how customers use the actual end product.

It’s important to distinguish between the two because, especially in B2B deals, the buyer is often different from the end-user. While there’s generally significant overlap between the two concepts, user experience is a subset of customer experience.

For example, a CMO reads a blog and attends a demo through a website before purchasing your software for her content marketing team. While the CMO might be thoroughly impressed with the material she’s interacted with, the content marketing team may actually be disappointed with the software.

While a customer journey map will consider this case end-to-end, a user experience map will only highlight the limited usage of the software by this content marketing team.

How does Factors.ai help with customer journey mapping?

Here are four ways in which Factors.ai can help map out your customer journey:

1. Account and User timelines

Factors unifies customer journey data across campaigns, website, and CRM to present an interactive timeline of touchpoints at a user and account level. This is an especially powerful tool for account-based marketing teams to track how users from their target accounts are progressing through the sales cycle.

2. Account Identification

Factors uses industry-leading IP-look up technology to identify up to 64% of anonymous website traffic.. This provides valuable insights into which accounts are visiting your website and how they’re interacting with pages and content.

This firmographic and intent-data helps shape the buyer personas for your customer journey map as it sheds lights onto how different types of companies interact differently with your brand.

3. Attribution

As previously mentioned, measuring the right touchpoints and tying it back to revenue manually is, to say the least, a chore. Multi-touch attribution on Factors helps connect the dots between conversions and pre-conversion touchpoints. Compare a range of attribution models based on the nature of your business to quantify the impact of marketing effort on pipeline and revenue.

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4. Path analysis

Path analysis is similar to timelines in that it provides an intuitive visualization of various accounts and users traveling through different paths along the customer journey. The difference is that path analysis reflects aggregated user behavior rather than a specific account’s journey.

This is helpful when testing hypotheses, running experiments, or gauging customer behavior on a larger scale.

And there you have it! A complete guide to customer journey mapping — and how Factors.ai can help construct your customer journey map.

This guide emphasizes the importance of understanding the customer journey for effective marketing. It explains how to visualize and analyze buyer interactions from awareness to post-purchase. By mapping these touchpoints, businesses can pinpoint areas for improvement, enhance customer experiences, and boost retention rates.

6sense & Factors.ai Partnership Announcement

December 18, 2025

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0 min read

We’re thrilled to announce our partnership with industry-leading account-based marketing platform, 6sense.

With this deep-rooted collaboration, Factors.ai now delivers state-of-the-art account identification, firmographics, and intent data along with our existing ABM analytics and attribution capabilities.

Users can expect to tap into 6sense’s extensive databases with Factors.ai to discover upto 64% of anonymous companies visiting the website — including account-level website behavior, purchase intent, and timelines.

Account Identification + Account Analytics = ABM Magic

This article highlights what the partnership means for our users, along with a few use-cases and testimonials. If you can’t already tell, we’re really excited for the immense value this collaboration brings to our customers.

A few common questions

Why partner with 6sense over other alternatives?

Rigorous comparative testing with over 20,000 IPs reveals that 6sense is far ahead of the game in terms of data quality, volume, consistency, and pricing. The infographic below highlights 6sense's ability to identify up to 27% more accounts than the closest alternative. Also, it doesn't hurt that 6sense is one of the leading ABM platforms in the market today.

Do users need a separate 6sense account to use account identification with Factors?

Nope! you do not have to be a 6sense customer to use account identification with Factors. Simply reach out to our team to enable this integration within your Factors project — without signing up or paying independently for a 6sense account.

If you are an existing 6sense customer, simply integrate your 6sense account to Factors using the API key.

Can Factors identify email IDs or phone numbers of anonymous website visitors?

No. Factors is a privacy-first, GDPR compliant solution. It only discovers IP-to-Company-level data. Factors does not identify individual website visitors or personal information like phone numbers or mail IDs unless the user chooses to share this information through form submissions.

How does pricing work?

Read more about our pricing details here: factors.ai/pricing

6sense & Factors.ai: What’s in it for you?

As B2B go-to-market teams continue to adopt account-based marketing strategies, there’s a growing demand for both account analytics and account intelligence. Here’s how the 6sense x Factors.ai partnership helps with both:

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Factors's real-time Slack Alerts for accounts identified via 6sense's visitor identification technology have helped our Sales Team be proactive. Roughly 25% of last month's new revenue for Clearfeed is due to the outbound outreach done by the SDRs based on Factors data.

1. Account Identification

B2B companies invest significant resources towards driving high-intent website traffic. Unfortunately, only about 4% of this traffic comes to light through forms or signups. With 6sense, Factors.ai can identify up to 64% of anonymous companies using industry-standard IP-lookup technology!

As we’ll cover in following sections, this provides sales and marketing teams with the ability to identify and target the right opportunities, personalize the customer experience, and measure the impact of campaigns.

2. Firmographics + Advanced Analytics

In addition to identifying company names, 6sense enriches visitor data with detailed firmographics such as domain, industry, headcount, location, and more. This information is continually optimized with proprietary machine learning and human QA. Firmographic data, in conjunction with Factors.ai’s advanced website analytics — button auto captures, page time spent, scroll percent, etc — helps effectively identify high-intent accounts, well-resonating website content, and points of friction along the customer journey.

The cherry on top: configure real-time Slack alerts when target accounts land on specific web pages to reach out to leads while the iron’s still hot. Research finds that contacting leads quickly significantly improves the odds of conversion. Our early adopters have been seeing real value delivered to their sales reps and ABM marketers.

3. Account Journeys & Timelines

A crucial element of account-based marketing is tracking how target accounts are progressing along the customer journey. Upon identifying companies visiting your site, Factors.ai creates an intuitive account-level timeline of the journey in real-time — across campaigns, website, and CRM.

On one hand, this provides retrospective insight into what campaigns and assets drive conversions. On the other hand, it provides forward looking inputs to optimize retargeting efforts and personalize sales pitches based on the account’s previous interactions.

Struggling to identify more than 5% of your anonymous traffic? See how Factors.ai can help your business reveal upto 64% of website traffic over a personalized demo.

Use-cases: Account Identification, Firmographics, and Intent Data

1. For Demand Gen

With this partnership, demand gen teams can see which marketing initiatives and assets are driving high-intent accounts to their website. Rather than relying on expensive spray and pray tactics, teams can reallocate resources to targeted efforts that bring in the right kind of buyers.

On the flip side, demand gen folk can reveal companies visiting the website and retarget the right, ICP accounts based on firmographic and intent. In a time when teams are asked to do more with less, Factors offers to optimize marketing ROI and make tight budgets go a long way.

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A game changer for B2B Marketers for Account Analytics. Factors' advanced analytics combined with 6sense visitor identification allows us to build a complete understanding of the Account Journey including the dark funnel. We are now able to plan our marketing campaigns and content efforts with clear visibility into what is driving conversions and pipeline.

2. For Content Marketers

B2B companies tend to invest heavily in content without actually knowing who the end consumers are. With Factors, content marketers can pin-point who’s reading ungated assets such as blogs and case studies.

For one, this helps discern what content resonates with different audiences. Content teams can guide their strategy based on what resonates best with their target personas. For another, content marketers can tie their efforts back to bottom line metrics like pipeline by showcasing timelines as buyers progress from blogs, to demos, to trials, and finally, to deals.

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Combining 6sense visitor identification with Factors' advanced analytics has unlocked insightful views for our product and content marketing teams. We now have a clear view of how our content performs across key audience segments — and the opportunities to optimize user journeys and conversions further.

3. For Product Marketers

Product marketers continually iterate on messaging for core pages such as the home page, pricing page, and features page. While standard web analytics and A/B testing tools provide insight into whether a certain message is working for overall traffic, this partnership empowers product marketers to experiment and tailor messaging for known visitors.

For instance, account identification and firmographics may reveal that larger companies are more interested in privacy compliance material while smaller teams may care about transparent pricing. Based on who the PMM is looking to target, they may alter messaging accordingly.

4. For Sales

The benefits of account identification and analytics is especially apparent in the case of sales teams. For one, sales reps can tap into a net-new pool of business from existing website traffic with zero additional spend. Within this set of accounts, sales can target the right ones based on intent and engagement insights. Finally, rather than spending hours trying to contact cold prospects, sales reps can improve direct engagement by reaching out to accounts while they’re on the site through real-time Slack alerts.

Overall, the workflow encouraged by the 6sense x Factors partnership dramatically improves sales productivity.

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A dream solution for B2B marketers to unfold user journeys. When we chalk plans for a campaign, we love valuable insights. Even better when I have it diced & sliced. We get it all here & engage with our audience. The granularity of data is perfect & the mining engine of Factors with 6sense has unbelievable match rates for de-anonymizing accounts.

Curious to see 6sense and Factors.ai in action? Book a personalized demo here!

HubSpot Analytics Vs. Factors.ai – Features, Limitations, Integrations & More

December 18, 2025

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0 min read

All our homies LOVE HubSpot. No doubt, it's a reliable CRM and marketing automation platform. In fact, Factors.ai integrates seamlessly with HubSpot to deliver full-path analytics and attribution across campaigns, website, and CRM. That being said, HubSpot’s own in-platform analytics and attribution engine, is fraught with serious limitations. The following article highlights these issues with HubSpot — and how you can overcome them with Factors.ai. Ultimately, we find Factors.ai to be a far better fit for data-driven B2B marketers.

Before we jump into the limitations of HubSpot analytics and attribution, it’s only fair to address a couple of positives. Although premium reporting (advanced analytics, revenue attribution, etc) is only available on HubSpot’s enterprise plans, it delivers a robust range of multi-touch attribution models in a simple, user-friendly framework. Additionally, if your company uses HubSpot CRM, MAP, and life cycles stages religiously, HubSpot could possibly be an effective all-in-one solution for reporting. As we shall now see, however, most teams do not use HubSpot in the dedicated manner that’s required for it to function well.

Limitation #1: Rigidity & Inaccuracy

1.1. Fixed Lifecycle Stages

One glaring limitation with HubSpot’s in-platform analytics solution is its rigidity around the sales funnel — and especially its life cycle stages. HubSpot analytics only offers fixed definitions for events and stages along the customer journey — Subscriber, Lead, MQL, SQL, Opportunity, Customer, and Evangelist. Now, this set of stages may fit in perfectly with your organization’s funnel structure; but in reality, most B2B teams follow unique customer stages based on the nuance and particulars of their business model. B2B SaaS firms for example, may care about including a “Demo Done” stage to flag high intent leads. HubSpot’s analytics engine does not provide the flexibility to include, or even edit lifecycle stages to match this preferences.

If your team does not adhere to HubSpot’s predetermined structure, Factors.ai may be the right fit for you. On Factors, users have limitless flexibility to set, track, and analyze their own internal life-cycle stages.

1.2 Inaccurate Lifecycle Stage Tracking

In continuation with the previous point — not only is HubSpot’s lifecycle stage tracking rigid, it’s also blatantly inaccurate. Rather than considering the leads in lifecycle stage “B” to be a subset of the previous lifecycle stage “A”, HubSpot only counts the contacts in a particular stage at that point in time. Here’s an example to illustrate:

Say you have 50 leads tagged MQLs. 20 of them become SQLs. This, of course, does not mean that you now only have 30 MQLs. Rather, it means that the set of 20 SQLs are a subset of the total set of 50 MQLs.

This is a major issue with HubSpot analytics — leading to inaccurate readings, insights, and ultimately; marketing decisions. Rest assured, Factors.ai ensures no such fallacies in logic. You can also guarantee a far wider range of filters, breakdowns, and visualization techniques on Factors.ai as compared to HubSpot analytics.

Limitation #2: Attribution Troubles

2.1 Campaign Attribution

It’s impossible to create attribution reports on HubSpot at a keyword level across campaigns and ad groups. If you want to look at keyword level attribution reports on HubSpot, you’ll need to examine keywords within a specific ad group from a specific campaign. Why is this an issue? Well because a specific keyword can (and usually does) belong to multiple campaigns

On Factors, you can do what HubSpot attribution does AND look at keyword attribution reports across campaigns and ad groups for granular, and more importantly, accurate insights.

2.2 Attributing Offline Events

Offline touchpoints are those touchpoints along the customer journey that cannot be tracked digitally. These include outbound emails, webinars, in-person events, corporate gifts, etc. While HubSpot does enable you to document these “events”, it is not possible to analyze or visualize them within HubSpot analytics. As a company scales, it’s likely to have a good combination of digital and offline touchpoints, making it imperative to account and analyze for both in union.

Factors.ai makes it possible to track, analyze, and attribute offline touchpoints by fetching contact tags and UTMs. These touchpoints are also completely customizable with no-code. Needless to say, unlike Factors.ai, HubSpot does not enable users to attribute custom properties, events, or KPIs.

2.3 Comparing Attribution Models

Factors.ai is one of the few attribution solutions that allows users to compare attribution models against each other. B2B sales cycles can be complex, and the ability to compare results across first-touch and multi-touch models gives marketers an unequivocal advantage in identifying trends accurately. Unlike Factors.ai, HubSpot does not offer the ability to compare attribution models.

Limitation #3: Lack of Granularity

Another major drawback with HubSpot analytics & attribution is that it considers lead source only at a channel level. That is, lead sources may be viewed as “Organic”, “Paid ads”, “Social” and so on. We all know that the devil’s in the details — and channel level data simply will not cut it in this day and age. How is one to know which campaigns or content to scale, if they are unable to view performance data for the same? Factors.ai is all about granularity. We ensure detailed analytics at a channel, campaign, ad group and keyword level to help you make the best possible marketing decisions. Our extensive line of no-code integrations across the most popular ad platforms guarantees a proper data-driven marketing experience.

Limitation #4: Data Integration Woes

So here’s the thing: you can integrate HubSpot with third-party data-sources, including other CRMs like Salesforce — but it’s no easy task. It requires tedious onboarding, strict vigilance, and developer dependency. You need to make sure all your sales data is either on or linked to HubSpot. If you use a combination of HubSpot and Salesforce or LeadSquared or Marketo, a platform like Factors.ai would make your life a lot easier. IF, however, you religiously use HubSpot exclusive products — CRM, MAP, Website, etc, then HubSpot may be a more convenient option for you.

Limitation #5: It’s The Little Things…

By design, Factors.ai is a robust, intuitive marketing analytics, attribution, and journey mapping platform. Above all, we pride ourselves on delivering the best possible experience to our users. This entails end-to-end onboarding support, sustained customer success management, and smooth, reliable performance. The same, unfortunately, cannot be said about HubSpot analytics.

Here’s why Factors.ai has the edge over HubSpot when it comes to user experience:

HubSpot imposes limited users or seats per hub. Factors grants unlimited seats, free of charge.
HubSpot requires tedious, developer dependent onboarding and training over several weeks, if not months. You can get started with Factors.ai in 30 minutes.
HubSpot charges an independent fee for tech support. Factors.ai is an extension of your team — with dedicated customer success management guaranteed.
HubSpot aggressively up-sells its features to nickel and dime existing customers. Factors.ai recommends tailor-made plans based on the scale and growth of your team.

And there you have it. Still curious to learn why Factors.ai would be better suited for your B2B team over HubSpot Marketing Hub? Book a personalized demo here to see our work in action.

HubSpot Analytics is known for its user-friendly interface and basic multi-touch attribution, making it a solid option for teams already embedded within the HubSpot ecosystem. It’s especially helpful for straightforward reporting and marketing workflows.

However, several limitations can hinder scalability for data-driven B2B teams:
- Rigid lifecycle stages that don’t always align with nuanced buyer journeys
- Limited customization options for reports and dashboards
- Difficulties integrating external data sources, leading to siloed insights

Factors.ai steps in to fill these gaps with:
- Customizable lifecycle stages tailored to your sales funnel
- Seamless integrations across diverse CRM, ad, and marketing tools
- Advanced analytics and attribution features that go beyond surface-level reporting

For B2B marketers seeking deeper insights, greater flexibility, and a holistic view of the customer journey, Factors.ai offers a more robust and scalable alternative to HubSpot Analytics.