Ranga Kaliyur

Looking to learn more about Lead Forensics pricing, features, and more? The following article provides a comprehensive overview of everything you need to know about Lead Forensics pricing. 

Lead Forensics is a popular B2B website visitor identification tool that reveals anonymous companies visiting a website and surfaces relevant contact details (Email, Phone numbers, etc) within those companies for outreach and targeting. Lead Forensics is used primarily by B2B marketers, sales folk, and agencies to leverage existing website traffic to drive sales revenue and marketing ROI. 

Lead Forensics Pricing & Plans

Lead Forensics offers two plans: Essential and Automate. Essential is designed for small to medium sized businesses to identify anonymous businesses viewing your website, unlock relevant contact data (phone numbers, mail ID, etc) and manage existing leads. Automate offers all this, plus additional features such as custom workflows, sequence actions (or as they call it, The Orchestrator), advanced CRM integrations and Fuzzy matching algorithm to maintain data hygiene. 

Here’s a detailed feature overview of how the two plans compare to each other:

Source

Note that:

• Lead Forensics offers a 7-days free trial
• Lead Forensics does not offer a free plan

Unfortunately Lead Forensics does not openly reveal its pricing details. You’ll have to reach out to their sales team for an accurate quote based on your requirements and scale. That being said, we’ve dug deep to find what we can about Lead Forensics’ pricing:

Anecdotal evidence suggests that Lead Forensics pricing runs between around $250 to several thousand per month, depending on the volume of website traffic. Multiple reviews also highlight that obtaining contact data (phone numbers, email addresses, etc) cost an additional fee on top of the monthly platform subscription fee

To be fair, the few reviews that do provide hints into Lead Forensics pricing are…well, unhappy customers. Ignoring their not-so-great opinions of the product, we can see that Lead Forensics charges these users approximately £209 + vat per month (or $260/mo) and $500 per month respectively. 

“To ensure a right sized solution for each of our clients, our pricing model is based upon relevant B2B traffic to a website or specified web pages. We offer a free trial period to ascertain the traffic volumes over a one week period. After which time, we will produce a bespoke proposal tailored to your business and your visitor traffic levels. We are committed to producing the right package and proposal for your business, which is why we don't have an off the shelf pricing model.” - Lead Forensics

Lead Forensics Reviews

Lead Forensics claims to maintain one of the world’s largest B2B IP-databases. But how do Lead Forensics customers find the platform to be on a day-to-day basis? Here’s what reviews have to say about user experience with Lead Forensics: 

In Summary 

Lead Forensics Benefits:

• Intuitive onboarding 
• Customer support

Lead Forensics Drawbacks: 

• Data inaccuracy
• Cost

Lead Forensics Rating:

• G2: 4.3/5
• Capterra: 3.4/5 
• TrustRadius: 2.6/10

Lead Forensics Alternatives

There are several account identification and intelligence solutions out there. Here are a few common Lead Forensics alternatives to consider:

• Factors.ai - for data-accuracy and advanced analytics, scoring, and attribution 
• Leadfeeder (Now Dealfront) - for EU-centric account intelligence
• Clearbit - for accounts and contact level intelligence

Factors is a leading account intelligence solution that helps B2B teams identify, qualify, and convert anonymous website traffic. Factors works with industry-standard data partners to provide accurate, cost-effective account intelligence. Why Factors over Lead Forensics? 

• Better data: Factors identifies up to 64% of anonymous traffic — that’s 27% more accounts than the closest alternatives. 
• Better intent signals: Factors stands out from alternatives in that it captures intent signals (ad views, impressions, page views) from LinkedIn and G2 in addition to website activity for holistic account engagement tracking.
• Better deals: While Lead Forensics doesn't openly reveal prices, internal demos reveal that Factors provides far more cost-effective plans. Learn more here: factors.ai/pricing
• Better analytics: Factors is built upon strong analytics and attribution foundations. As a result, it provides granular website tracking, path analysis, timelines, and more. 

Lead Forensics Pricing Plans

Lead Forensics offers flexible plans tailored to different business sizes and needs.

1. Pricing Tiers:
- Essential: For SMBs, includes visitor identification, contact details, and lead management.
- Automate: For enterprises, adds CRM integration, customizable workflows, and AI-driven sequencing.

2. Key Features:
Anonymous visitor tracking, advanced lead insights, and automated engagement workflows.

3. Pricing Estimates:
Ranges from $200 to $2,000+ per month based on traffic and feature requirements.

For accurate pricing, businesses should contact Lead Forensics directly to receive a customized quote.

FAQ

1. What does Lead Forensics do? 

Lead Forensics tracks business IPs to identify anonymous website traffic at an account-level. Once a visiting company has been identified, Lead Forensics also shares relevant contact information such as mail IDs and phone numbers to streamline outreach and targeting. 

2. What is the lead forensic code?

The Lead Forensics code is a tiny piece of code placed on a business website. It’s this code that enables users to identify websites visitors’ business IP addresses. This IP is then matched with an IP database to reveal business names and properties.

It’s no secret that the B2B SaaS funnel involves several touchpoints across campaigns, website, offline events, and CRM. Given that customer journeys are complex and nonlinear, measuring and optimizing marketing’s impact on revenue may seem like a daunting task. To solve for this, there’s been an influx of plug and play B2B marketing attribution and analytics tools in recent years. 

While there’s no shortage of marketing attribution tools out there, each solution has its own unique set of features, strengths, and limitations. This blog compares two popular B2B marketing attribution tools — Dreamdata and Hockeystack — to help readers decide which solution may be better suited to their needs.

Note that this blog won’t cover the basics of what marketing attribution is. Instead, you can find a wide range of resources on marketing attribution here:

• A Comprehensive Guide To Marketing Attribution
• B2B Marketing Attribution
• Challenges With B2B Attribution (And How To Get Over Them)

About Dreamdata

Dreamdata is a Denmark-based B2B revenue attribution platform that works to connect and crunch revenue related data across the customer journey.  At a high level, much like any other competent marketing analytics tool, Dreamdata helps teams identify what GTM effort drives revenue, where to cut costs, and how to scale the right campaigns. 

As following sections highlight, Dreamdata provides a robust analytics suite, a wide-range of integrations, and a strong customer success experience. That being said, the platform seems to fall short when it comes to implementation, custom reporting and dashboarding, and ease of use. Each of these features and limitations are covered in detail below. 

About HockeyStack

HockeyStack is a B2B analytics and attribution platform that helps teams track data across campaigns, website, and CRM to measure marketing ROI, view account-based intent signals, and improve budget allocation. 

HockeyStack claims a rapid implementation process and customizable dashboards. That being said, HockeyStack offers fewer integrations and limited granularity when it comes to reporting. Again, each of these features and shortcomings are highlighted in detail below.

Dreamdata vs. HockeyStack: Key Features

Both Dreamdata and HockeyStack are effective marketing attribution tools in their own right — but no product is perfect. The next couple of sections examine key features, strengths and limitations of each solution. Naturally, there’s bound to be significant overlap; but the devil is in the details. After covering a few key common features, we explore where each platform outperforms the other.

#1 Tracking & Analytics: 

As most analytics solutions do, both Dreamdata and Hockeystack unify marketing and revenue data under one roof. Both tools also provide a wide range of analytics capabilities to help teams make well-informed decisions across campaigns, website, content, and more. 

Both solutions employ javascript codes that are added to a website to track visitor interactions and engagement. They can measure standard website performance metrics like pageviews, scroll depth, clicks, form submissions, and more at an account and user level. In turn, teams can gauge customer behavior and learn how different content and webpages influence pipeline by cohort. 

Dreamdata and HockeyStack also integrate with ad platforms, marketing automation platforms, and CRMs to consolidate campaign metrics, offline events, and revenue metrics. This helps marketing teams monitor their efforts and understand what’s helping or hurting bottom line conversions. Note that Dreamdata currently provides a wider range of integrations than HockeyStack — more on this later. 

#2 Multi-touch attribution

Attribution analysis is at the core of Dreamdata and Hockeystack. Unsurprisingly, both solutions do a good job of measuring performance across marketing activities and attributing each touchpoint back to revenue.  

They can stitch and credit measurable touchpoints across channels, campaigns, website, and offline events (from CRM) based on their influence on pipeline. Using a range of multi-touch attribution models, marketing teams can quantify their impact on revenue from first-touch to deal won at an account level. Here are a few use-cases multi-touch attribution on Dreamdata and Hockeystack can solve for:

• Measuring ROAS across ad campaigns
• Attributing revenue back to marketing channels 
• Tracking the impact of organic social and SEO efforts
• Learning which content and channels drive bottom-line metrics

#3 Journeys

Journeys analytics is a relatively recent feature that’s not as common amongst other marketing analytics and attribution tools. That being said, both Dreamdata and HockeyStack offer variants of journey analytics.

In short, journey analytics helps teams visualize complex, non-linear customer journeys by mapping each stakeholder’s touch-points at an account level. Why is this helpful? It provides an intuitive timeline of profiles, behavior, and intent across each account within the pipeline. This information may in turn be used to personalize further marketing efforts, optimize retargeting campaigns, customize sales pitches, and identify buying patterns. 

HockeyStack and Dreamdata work well for all three features covered above. Still, both tools have their own strengths and limitations. The following section highlights stand-out reasons why users may prefer one over the other. 

What Dreamdata Does Better

1. Out-of-the-box Integrations

Dreamdata offers a wider range of out-of-the-box integrations as compared to HockeyStack. While both solutions provide integrations with the most popular ad platforms, CRMs, MAPs, and CDPs, Dreamdata goes the extra mile to cater to relatively niche platforms and data warehouses as well. 

Key integrations supported by Dreamdata and HockeyStack*: HubSpot, SalesForce, Google Ads, Facebook Ads, Linkedin Ads, Marketo, Pardot, Intercom, Segment

Key integrations supported by Dreamdata but not HockeyStack*:  Zoho, G2, Zapier, Outreach, AdRoll, Google Data Studio, BigQuery 

*based on HockeyStack website

Pro Tip: Note that in case Dreamdata and HockeyStack doesn’t support an integration for a specific platform, both tools offer custom integrations as per demand. 

2. Detailed & Granular Reporting 

Although this isn’t necessarily a drawback with HockeyStack, users have complained about its lack of granularity. Reviews compare HockeyStack’s reporting capabilities to that of Google Analytics (GA4) — decent, but not detailed enough. Given that Dreamdata is a relatively mature product, their reporting capabilities provide deeper insights across conversion rates, customer lifetime value, and revenue attribution, and more. 

3. Customer Success

B2B analytics and attributions platforms are complex. While tools are becoming increasingly intuitive, it’s important for non-technical users to have easy access to timely, effective CSM. Fortunately, Dreamdata seems to support robust customer success servicing. This is especially valuable since Dreamdata’s implementation is reportedly an involved process. 

4. Templatized Reporting + UI

This is a double edged sword. Dreamdata delivers a structured, non-customizable dashboard and event framework that offers little room for flexibility. Dashboards are broadly grouped into the following categories: Engagement, Content, Performance, Journeys and Revenue. 

On one hand, this may be beneficial to smaller SaaS teams with limited technical resources as it’s likely to cater to most of their analytics and reporting needs. 

However, as the business starts to scale, its requirements may include custom dashboards and events that are company-specific. At this point, Dreamdata’s templatized reporting may be a drawback.

Although reviews suggest that Dreamdata involves a steep learning curve, it’s fair to assume that its UI is a step ahead of HockeyStack. HockeyStack is a relatively younger product and users tend to find the platform a little rough around the edges. That being said, reviews also suggest that they’re showing quick improvement. It’s likely only a matter of time before both platforms are on par with each other.

What HockeyStack Does Better

1. Implementation

HockeyStack makes strong claims about its rapid implementation process, suggesting that users can onboard and get started in a matter of minutes. This is in stark contrast to Dreamdata, which, as a more sophisticated tool, requires an involved, drawn-out implementation process. HockeyStack’s intuitive onboarding is a big advantage to smaller teams that don’t have the resources for dedicated onboarding or maintenance support. 

2. Custom Dashboards

Dreamdata’s platform focuses on solving the most common SaaS use-cases. As a result, the platform tends to be relatively less flexible. HockeyStack, on the other hand, promotes far more customizations across events, reports, dashboards, and visualizations. HockeyStack provides the option of preconfigured templates, but lets users build reports from scratch as well. While granularity may be lacking when compared to Dreamdata, this ability for flexible dashboarding may be helpful for teams looking for tailor-made, high-level reports. 

3. Funnels, Surveys & Impression Tracking 

Along with the key analytics and attribution features discussed, HockeyStack provides a few features that Dreamdata doesn't.

The most valuable of these features is probably Funnels. Funnels is a powerful analytics technique that helps users graphically visualize different stages of the sales cycle. These stages can be configured by users to, for example, see how website visitors are progressing from the home page, to the pricing page, and to a blog before scheduling a demo. 

Surveys is another feature that, as the name suggests, allows users to create surveys for self attribution. Finally, Linkedin Impression Tracking is another nifty feature that enables users to identify companies viewing Linkedin campaigns.

Dreamdata vs. HockeyStack: Pricing

[December 2023 Update]: Both HockeyStack and Dreamdata have revised pricing since this article was published. While HockeyStack have increased their starting price, Dreamdata have decreased theirs. Here's an updated rundown of pricing:

• Dreamdata pricing now starts at $599/mo for up to 30,000 MTUs
• HockeyStack pricing now starts at $1399/mo for up to 10,000 monthly visitors

‍

[Pricing as of February 2023]

• Dreamdata’s paid plans start at $999/month for 10 seats and up to 10,000 MTUs
• HockeyStack’s paid plans start at $949/month for 10 seats and up to 10,000 monthly visitors
• HockeyStack offers a 14-day free trial 
• Dreamdata offers a free web analytics tool as an alternative to Google Analytics

Still On The Fence About What B2B Attribution Tool To Go With?

And there you have it. A breakdown of Dreamdata and HockeyStack, and the reasons why one could be a better fit for you over the other. Still On The Fence About What B2B Attribution Tool To Go With? Here are a few reasons why you might want to consider Factors as well:

• Rapid, no-code integrations across ad platforms, CRM, MAP, and more 
• Granular, end-to-end analytics, attribution, and journeys across ad campaigns, website content, offline events, organic content, and more 
• Fully customizable events, properties, dimensions, and dashboard
• Dedicated customer success management 
• Funnels, path analysis and website tracking

And…

• Website visitor identification
• AI-fueled conversion insights
• Real-time Slack alerts
• Cost-effective analytics pricing plans starting at $399/month

Amplitude Vs. Factors.ai: What’s The Right Tool For You In 2025

B2B go-to-market teams are increasingly relying on marketing and website analytics tools to track and optimize performance. In response to this growing demand, established product analytics tools like Amplitude and Mixpanel are attempting to introduce their own versions of website analytics, marketing funnels, and multi-touch attribution. 

There’s no doubt that Amplitude is great at what it does. In fact, it’s rated as one of best product analytics solutions in the market today. But how does a tool that specializes in product analytics fare against a purpose-built marketing analytics solution like Factors.ai? And more importantly, what’s the better choice for your use-case? 

This blog compares Amplitude vs Factors.ai. Here’s what we’ll be covering:

• Marketing Analytics vs Product Analytics
• Comparing Common Features
• What Amplitude Does, That Factors Doesn’t
• What Factors Does, That Amplitude Doesn't
• What’s The Right Tool For You? 
• Comparison Table

tl;dr:

Marketing Analytics vs Product Analytics

Before diving into the comparison between Amplitude and Factors.ai, it’s worth highlighting the difference between marketing analytics and product analytics. 

Marketing analytics tools are geared towards tracking and optimizing performance across campaigns, website, and CRM. Popular marketing analytics tools you may have heard of include Google Analytics, Factors.ai, and Adobe Analytics. Marketing analytics can help answer questions such as:

• Which marketing efforts drive the most ROI and pipeline? 
• Which campaigns should be scaled or cut to optimize budgets?
• What marketing channels attract high-quality accounts to the website?   
• How are visitors engaging with the website? What’s helping and hurting conversions?
• What is the impact of content on pipeline? Which blogs resonate most with visitors?

Product analytics tools like Amplitude, Mixpanel, and Heap are better suited to tracking event-based data within web and mobile products. These tools help understand how customers use specific features within a product. Product analytics can help answer questions like:

• Which product features are most popular? How does usage vary by customer type? 
• How long do customers spend using a specific feature every week?
• Which customers are most likely to convert to higher tier plans? 
• Which customers are most likely to churn based on engagement?
• How can the product road map be finetuned based on product usage? 

Needless to say, marketing analytics tools are better suited to marketing & sales teams while product analytics tools are more helpful to product teams. Here’s a quick brief about Amplitude and Factors. 

About Amplitude

Amplitude is an established product analytics platform that works with commercial and enterprise-level companies like Atlassian, Dropbox, and Adidas. The platform is divided into three products: 

1. Amplitude Analytics 
2. Amplitude Experiment 
3. Amplitude CDP.

About Factors

Factors is an AI-fueled marketing analytics and attribution platform that works with SME and mid-market B2B companies like Razorpay, Chargebee and Clickhouse. The platform is divided into 4 broad categories: 

1. Marketing and website analytics
2. Marketing attribution 
3. Journeys analytics 
4. Visitor identification.

As Amplitude begins to dip its toes into website analytics, it makes sense to compare the two solutions. Here's a breakdown of thei common features:

Amplitude vs Factors.ai: Comparing Common Features 

1. Website Analytics

As discussed, Amplitude is primarily a product analytics platform while Factors.ai specializes in marketing and web analytics. However, since both solutions rely on event-based analytics, a comparison makes sense.

‍

1. Data

On paper, Amplitude offers a wider range of integrations than Factors. That being said, most of these integrations are geared towards product analytics use-cases. 

As a result, Amplitude’s integration with ad platforms (Google, Linkedin, etc) and CRMs (HubSpot, SalesForce, etc) tends to be limited. In turn, Amplitude’s functionality as a website analytics platform comes into question.

For instance, Amplitude cannot stitch website data with CRM data such as lead stages (MQLs, SQLs, etc), offline events (sales calls, emails, etc), or revenue figures (deal size, LCV, etc). Instead, Amplitude users are limited to website analytics that’s in isolation to the rest of the buyer journey. As B2B marketing teams become increasingly responsible for driving bottom line metrics, siloed website data is a serious limitation. 

Factors integrates with ad platforms, CRMs, and CDPs. As a result, it’s capable of linking website touchpoints, campaign data, and CRM events for holistic analytics and reporting. 

2. Metrics & KPIs

Businesses rely on a wide range of metrics to measure website performance and guide the decision-making process. Standard metrics like bounce rates and monthly visitors are available on both Factors and Amplitude. However, granular metrics like scroll depth or engagement rates become tedious to configure on the latter.

Given that Factors.ai is designed for B2B website analytics, it offers the ability to track a wide range of KPIs and metrics out-of-the-box. Furthermore, creating custom KPIs  is easier on Factors, involving zero developer dependency. 

Overall, both Amplitude and Factors do a good job of basic website analytics and reporting. But if you’re really trying to identify visitor behavior, track top-performing content, and drive BoFu conversions — Factors is probably the better choice.

2. Funnels

In short, a funnel is a sequence of steps taken by users across campaigns, website, CRM, and product. Here’s a funnel of prospects visiting the pricing page, submitting a demo form, qualifying as an SQL, creating an opportunity, and closing the deal:

Even before trying its hand at marketing and website analytics, Amplitude delivered powerful funnels for product analytics. With Amplitude, product teams can learn how to improve onboarding, see how customers progress from free plans to paid ones & more. 

Amplitude is now offering a similar, event-based funnel feature for websites. At the moment, Amplitude provides more room for funnel configurations and breakdowns as compared to Factors.

Factors is on par with Amplitude for most B2B funnel use-cases. That being said, Amplitude offers a few advanced functionalities that Factors doesn’t. For example only Amplitude can exclude specific events between funnel steps and compare multiple events at a single step.

Note that while Amplitude’s funnel capability is more flushed out than Factors, it is unable to bring in CRM data. As a result, Amplitude cannot create funnels across website and CRM events.

For instance, Amplitude and Factors can create the following funnel: 

Homepage -> Pricing page -> Features page -> Newsletter signup -> Demo request

But only Factors can create a funnel to visualize this journey:
Homepage ->  Demo request -> Opportunity created -> Deal created -> Deal won

Amplitude’s funnel is mature and better suited to product teams. Factors’ funnel showcases the wider picture and is better suited to GTM teams. 

3. Path Analysis

In short, path analysis or Pathfinder helps track aggregated customer flows across website and product. It helps map out events fired by users as well as the sequence of those events taken by users within a specific time period.

Pathfinder is a core feature in Amplitude. As a result, it's currently better than Factors’ path analysis in terms of refinement and functionality. Given that path analysis is a recent feature on Factors, it’s a matter of time before both tools are on par with each other. 

4. Marketing Attribution

In short, B2B marketing attribution is an analytics technique that measures the influence of various marketing touchpoints on desired conversion goals such as demos, pipeline, and revenue using a range of multi-touch attribution models. 

While Amplitude is a well-established brand in product analytics, it’s only just entering the marketing attribution space. Unlike Amplitude, marketing attribution has always been a cornerstone feature for Factors.ai. Given that this is Factors’ expertise, it outperforms Amplitude comprehensively when it comes to marketing attribution.  

Here are a few limitations with Amplitude’s marketing attribution that Factors solves for:

• Limited conversion milestones: As previously discussed, Amplitude cannot integrate with CRM data for marketing attribution. As a result, conversion milestones are limited to website events such as page views or form submissions. It is not possible to attribute marketing’s influence on key metrics like SQLs, pipeline, or deals using Amplitude. This makes for highly ineffective attribution for B2B marketing teams that are looking to prove their impact on revenue.

• No revenue attribution: Continuing with the previous point, Amplitude cannot attribute marketing touchpoints to revenue/spend metrics like ad spends, deals closed, deal size, etc. Given that a major use-case for B2B marketers is to measure ROI and improve resource allocation, this limitation hinders Amplitude’s attribution functionality in B2B settings. 

• No account-level attribution: Amplitude’s attribution is at a user-level as opposed to at an account-level. Unlike B2C transactions, B2B deals involve lengthy sales cycles and several stakeholders from a single buying account. Naturally, it makes sense to attribute marketing touch-points at an account level rather than by individual users. Since Amplitude does not support account-level analytics, its attribution tool remains largely ineffective for B2B teams.

• Limited granularity: At the moment, Amplitude can attribute marketing channels and campaigns to website events. No doubt, having high level data at a channel and campaign level is helpful. However, in order to really optimize marketing ROI and scale the right efforts, it’s essential to have granular attribution at an ad group and keyword level as well. Currently, this is not supported by Amplitude.

• Limited touchpoints: Currently, Amplitude’s attribution modeling  only considers paid ads and digital marketing touchpoints. Factors has the ability to attribute conversions to offline touchpoints such as events, webinars, and sales calls. This is a crucial piece of the puzzle for B2B marketers. 

Factors counters each of these limitations by delivering multi-touch attribution across keywords, ad groups, campaigns, channels, website, and CRM events at an account-level. All in all, Factors is the better choice when it comes to B2B marketing attribution.

So what’s the right tool for you? The answer depends on what you’re looking for. To break it down further, here are a few pointers on what each platform does that the other doesn’t. 

What Amplitude Does, That Factors Doesn't

• Product analytics: As discussed at the top of the article, Amplitude is a leading product analytics tool with exceptional retention analytics and cohort analytics. If these use-cases are important to you, look no further than Amplitude.‍
• Mobile analytics: Amplitude is capable of tracking event-level data on mobile (app-based) products as well. Since Factors focuses on web-based event analytics, it cannot analyze mobile events whatsoever.‍
• Experiments (A/B testing): Amplitude offers Amplitude Experiments to conduct A/B testing within the product and website. This is a valuable feature for product and design teams to test hypotheses on messaging, product features, and design.‍
• CDP: Amplitude provides a native customer data platform. The CDP helps improve data quality, identify new audiences, and connect behavioral data. At the moment, Factors can integrate with third-party CDPs like Segment for similar use-cases.

What Factors Does, That Amplitude Doesn’t

• Integrates marketing, CRM, and revenue data: This point has been discussed multiple times in this blog but it’s worth highlighting again. Unlike Amplitude, Factors can easily integrate data across ad campaigns, website, and CRM. This empowers holistic marketing analytics, funnels, and attribution rather than siloed web and product analytics.
• Intuitive UI & low-lift implementation: Any analytics tool involves a learning curve. That being said, Factors is significantly easier to implement and use as compared to Amplitude. Onboarding takes minutes as opposed to weeks or months. The platform is far more user-friendly for non-technical GTM teams to create relevant reports and dashboards. 
• Anonymous visitor identification (IP-lookup): A stand-out feature offered by Factors.ai is anonymous visitor identification. In short, Factors uses reverse IP-lookup technology to identify companies visiting your website without requiring the visitor to submit contact information. This is especially valuable to B2B companies looking to identify, track, and convert high-intent accounts that are already visiting the site.
• Automated AI-fueled insights: Factors’ AI-algorithm works to provide intuitive automated insights into what’s helping and hurting custom conversion goals. With Explain and Weekly Insights, teams can drill down into how keywords, campaigns, channels, website content, and offline events are influencing objectives such as increasing traffic, booking demos, ramping up newsletter subscriptions, or driving pipeline. 

So What’s the Right Tool For You?

This is the primary consideration when deciding between Amplitude and Factors — are you looking to monitor and improve your product? If so, Amplitude is the better choice. Are you a B2B team looking to monitor and optimize GTM performance? If so, Factors probably makes more sense. 

In summary...

Still on the fence about which tool may be better suited to you? See Factors in action over a quick demo

Compare Factors.ai with other tools:

1. Factors vs Google Analytics
2. Factors vs Bizible
3. Factors vs Dreamdata
4. Factors vs HubSpot Analytics

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.

{{CTA_BANNER}}

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.

Customer centricity is at the heart of a successful business. Delivering value to buyers at every customer journey stage drives sales conversions and retention. This, however, is easier said than done — especially in the case of B2B customer journeys. 

Understanding the customer journey is crucial for modern marketing and sales strategies. With evolving customer behaviors and preferences, it's essential to adapt and refine approaches to address the complexities of how customers interact with brands. 

This journey is no longer a straightforward path but a complex, often non-linear process. To effectively engage with potential customers, businesses need to grasp the intricacies of each stage, especially awareness, consideration, and decision. This blog explains these stages, offering practical insights and strategies based on current industry understanding and research.

TL; DR

• Understanding the customer journey is crucial for B2B marketing and sales success due to its complexity and non-linear nature.
• Customer journeys map out various buyer interactions to track how and why prospects become paying customers. 
• The customer journey consists of 5 broad stages: Awareness, Consideration, Decision, Retention, and Advocacy. 
• Delivering relevant material along each stage ensures that prospects feel understood and valued. This, in turn, contributes to successful journeys and provides practical insights and strategies for each stage.
• Businesses can enhance engagement and build long-term relationships by addressing customer needs and behaviors throughout the journey.
• Factors.ai connects the dots across campaigns, websites, and CRM to map the customer journey using path analysis and account timelines.

The Evolution of Customer Journey Stages

The B2B sales cycle involves several stakeholders and touch points across campaigns, social media, organic efforts, offline events, and more. A customer journey maps out these interactions to track how and why prospects become paying customers. 

Since B2B sales cycles tend to be lengthy, non-linear experiences, it can be challenging to map them accurately without the right tools and frameworks. 

Learn more about customer journey mapping here: The Complete Guide To Customer Journey Mapping.

Traditionally, the customer journey was viewed as a linear process, with prospects moving through clearly defined stages: awareness, consideration, and decision. However, modern perspectives reflect a more nuanced view. Today’s customers might navigate through these stages in a circular or even chaotic manner, reflecting the complexities of contemporary decision-making.

According to Gartner, only 17% of a customer journey is spent directly conversing with the vendor. The remaining 83% takes place through independent research and internal deliberation. Hence, businesses must distribute relevant value at each journey stage — even outside discovery sessions and demo calls.‍

Understanding the Awareness Stage

The awareness stage is where the customer journey begins. At this point, potential customers become aware of a problem or need but have not started actively seeking solutions. It's crucial to recognize that potential customers need help understanding the scope or urgency of their issue during this stage. They may be exploring general trends or innovations without a clear sense of how these relate to their specific needs.

Customers in the awareness stage primarily gather information. They might browse blogs, read articles, and engage with introductory content. Marketing efforts in this stage should focus on educational content that introduces customers to new concepts or challenges. Content such as informative blog posts, eBooks, webinars, and automated AI Phone Calls can effectively capture their interest by delivering personalized voice messages that highlight relevant industry challenges, complementing email campaigns for a cohesive multi-channel engagement strategy.

Transitioning to the Consideration Stage

As customers move from awareness to consideration, they start recognizing the need for a solution. This transition is often triggered by an internal realization, such as remembering the inefficiency of current processes or the impact of emerging trends. This is a critical phase for businesses where prospects evaluate various solutions to address their identified needs.

During the consideration phase, customers will likely seek detailed information about potential solutions. They will look for case studies, ROI calculators, and in-depth product details to compare options. Effective marketing strategies during this phase should provide comprehensive resources that assist decision-making. This includes offering detailed product descriptions, customer testimonials, and interactive tools that help prospects understand the benefits and value of different solutions.

A few questions to ask here would be:

• Is the value of my product easy to grasp?
• Can people find my business without hassle?
• How does my product compare against competitors in terms of pricing and features?
• What is my unique selling point to convince buyers to pick me over the competition?

At this stage, it’s important to highlight why your product outshines the others with relevant case studies, product webinars, FAQ documentation, and more.

Navigating the Decision-Making Process

The decision stage is where customers are ready to finalize their purchase. At this point, they compare different solutions and make a final choice. However, it's important to note that the decision-making process is sometimes linear. Customers may revisit earlier stages if they encounter new information or if internal factors, such as budget constraints or organizational changes, influence their decision.

The decision stage involves evaluating competitors and making a purchase decision. Marketing efforts should be geared towards removing any final obstacles to purchase. This includes providing clear pricing information, offering competitive comparisons, and addressing any lingering objections. Strong calls to action and easy-to-navigate purchasing processes can significantly impact the final decision.

Circular and Non-Linear Customer Journeys

Modern customer journeys are often circular or iterative rather than strictly linear. Customers might revisit earlier stages as they gather more information or reassess their needs. HubSpot supports this perspective, noting that the customer journey can involve looping back to previous stages, reflecting the dynamic nature of modern decision-making.

To effectively manage this non-linear journey, businesses must be adaptable and responsive. Implementing tools for account scoring and path analysis can help identify where prospects are in their journey and adjust marketing strategies accordingly. For instance, if a prospect shows renewed interest in a particular product feature, it may indicate a return to the consideration phase.

Customer Journey vs. Buyer Journey

The customer and buyer journeys are both essential concepts in marketing and sales, but they refer to slightly different processes. Here’s a breakdown:

Leveraging Customer Feedback and Data

Collecting and integrating customer feedback is crucial for refining the customer journey. Feedback at various stages provides valuable insights into customer needs and preferences. By incorporating this feedback, businesses can better align their marketing strategies with customer expectations and improve overall engagement.

Implementing tools for feedback collection, such as surveys and user reviews, can help businesses understand pain points and areas for improvement. Regularly analyzing this data allows for continuous optimization of marketing efforts and enhances the overall customer experience.

Enhance Customer Experience with Personalization

Personalization plays a vital role in managing the customer journey effectively. Tailoring content and interactions based on customer behavior and preferences can significantly enhance engagement. Using data to personalize email campaigns, website content, and product recommendations can create a more relevant and engaging customer experience.

Personalization should be based on insights gained from customer interactions and feedback. Data analytics involves understanding customer behavior, preferences, and pain points. Personalized content can address specific needs and concerns, making it more likely to resonate with the target audience.

The Role of Technology in Managing the Customer Journey

Technology plays a significant role in managing and optimizing the customer journey. Customer relationship management (CRM) systems, marketing automation tools, and analytics platforms are essential for tracking and analyzing customer interactions. These tools can provide valuable insights into customer behavior, preferences, and engagement patterns.

Implementing CRM systems allows businesses to manage customer relationships more effectively by tracking interactions, managing leads, and analyzing data. Marketing automation tools can streamline communication, and nurture leads through personalized content and targeted campaigns. Analytics platforms provide insights into customer behavior, helping businesses make data-driven decisions and optimize their marketing strategies.

Integrating Omnichannel Marketing for a Seamless Journey

In today's digital age, customers interact with brands across multiple channels. Integrating an omnichannel marketing approach ensures a seamless and consistent experience throughout the customer journey. This involves unifying marketing efforts across various platforms such as social media, email, and in-store experiences.

An effective omnichannel strategy involves synchronizing marketing messages and ensuring that customer interactions are consistent regardless of the channel. This enhances the customer experience and provides a holistic view of customer behavior, enabling better decision-making and more personalized interactions.

Difference Between Customer Journey and Sales Funnels

While the customer journey and sales funnel are often used interchangeably, they represent different aspects of the purchasing process.

The sales funnel is a linear model that outlines a customer's stages, from awareness to purchase. It typically includes stages such as awareness, interest, decision, and action. The funnel model focuses on guiding customers through a sequence of steps toward a final conversion. It's a valuable tool for visualizing and managing the sales process but can oversimplify the complexity of modern customer interactions.

In contrast, the customer journey is a broader concept encompassing all customer interactions with a brand, from initial contact to post-purchase experiences. It acknowledges that customer interactions are not always linear and may involve multiple touchpoints and feedback loops. The customer journey model emphasizes the importance of understanding and optimizing the entire experience, including emotional and contextual factors, rather than just focusing on driving conversions.

The Importance of Customer Journey Mapping

Customer journey mapping is a valuable tool for visualizing the customer experience. It helps businesses understand customers' various touchpoints and interactions with the brand. By mapping out the customer journey, companies can identify potential pain points and opportunities for improvement.

Creating detailed customer journey maps is essential to gain insights into customer behavior and preferences. These maps should include all journey stages, from initial awareness to post-purchase interactions. Regularly updating and analyzing these maps allows businesses to stay attuned to evolving customer needs and optimize their marketing strategies.

Tracking Customer Journey Maps with Factors.ai

Factors.ai provides a robust platform for tracking and analyzing customer journey maps. This tool offers valuable insights into customer behavior, preferences, and interactions across various touchpoints.

With Factors.ai, you can:

1. Visualize Customer Journeys

Create detailed maps illustrating how customers interact with your brand through different stages. This visualization helps identify critical touchpoints and understand the overall customer experience.

2. Analyze Customer Behavior

Track customer actions, preferences, and engagement patterns. Factors.ai provides data-driven insights that inform your marketing and sales strategies, allowing you to tailor your approach based on actual customer behavior.

3. Optimize Touchpoints

Use the insights gained from journey maps to optimize customer touchpoints and enhance the overall experience. Factors.ai enables you to identify pain points and improvement areas, helping you refine your strategies for better results.

4. Measure Impact

Assess the impact of interactions and touchpoints on customer satisfaction and conversion rates. Factors.ai offers tools to measure the effectiveness of your efforts and make data-driven decisions to drive better outcomes.

By leveraging Factors.ai, you can better understand the customer journey and make informed decisions to enhance engagement and drive success.

Building Long-Term Customer Relationships

The end goal of managing the customer journey effectively is building long-term customer relationships. This involves facilitating a smooth journey from awareness to a decision and ensuring ongoing engagement and satisfaction post-purchase. Loyalty programs, personalized follow-ups, and excellent customer service are crucial to fostering long-term relationships.

Post-purchase engagement is crucial for maintaining customer loyalty and encouraging repeat business. This can include sending personalized thank-you emails, offering exclusive discounts, and providing excellent customer support. Companies can turn satisfied customers into brand advocates who contribute to long-term success by continuously nurturing customer relationships.

Optimize Your Customer Journey for Better Conversions

Understanding and optimizing the five stages of the customer journey - Awareness, Consideration, Decision, Retention, and Advocacy - can significantly impact customer engagement and business growth.

Here’s how:

1. Awareness: Educate potential customers with valuable content that addresses their pain points and introduces your brand.

2. Consideration: Provide in-depth solution comparisons, case studies, and testimonials to help prospects evaluate their options.

3. Decision: Ensure a seamless purchasing experience with clear pricing, demos, and a frictionless checkout process.

4. Retention: Build long-term relationships with personalized engagement, exceptional customer support, and loyalty programs.

5. Advocacy: Turn satisfied customers into brand advocates by encouraging reviews, referrals, and community engagement.

By refining each stage, businesses can enhance customer experiences, increase conversions, and drive sustainable growth.

In a nutshell

Navigating the modern customer journey requires a comprehensive understanding of the various stages and an adaptable approach to marketing. The transition from awareness to consideration is a critical phase that demands targeted strategies to address evolving customer needs. Businesses can better engage with prospects and drive successful outcomes by focusing on educational content, detailed product information, and practical decision-making support.

Understanding that the customer journey is often non-linear and iterative allows businesses to remain flexible and responsive. By focusing on each stage and addressing your customers' unique needs and behaviors, you can achieve long-term success and foster a positive relationship with your audience.

Factors.ai can help track each stage, from awareness to advocacy. To see Factors.ai in action, book a personalized demo here!

‍

FAQs on 5 Stages Of Customer Journey

1. What is a customer journey, and why is it important for businesses?

The customer journey is the complete experience a customer has with a brand, from the first interaction to post-purchase. It is important because it helps businesses understand customer behaviors and needs at each stage, allowing for better engagement, sales conversions, and long-term relationships.

2. How can businesses track and improve the customer journey?

Businesses can track the customer journey using tools like Factors.ai, which provides insights into customer behavior, engagement patterns, and pain points. By analyzing this data, businesses can optimize touchpoints, improve customer experience, and enhance overall marketing strategies.

3. What are the 5 stages of a customer journey?

The 5 stages of a customer journey are:

1. Awareness: The customer recognizes a problem or need.
2. Consideration: The customer explores potential solutions.
3. Decision: The customer chooses a solution and makes a purchase.
4. Retention: The business focuses on keeping the customer satisfied and engaged.
5. Advocacy: Satisfied customers recommend the brand to others.

ZoomInfo is an industry-leading B2B go-to-market platform that helps teams identify and connect with their target audience through account and contact-level data, but that’s not all. They are actively working on changing their position in the market from a data provider to an end-to-end market software company. Hence, it’s essential to understand the details of ZoomInfo’s latest offerings, prices, and updates. But that raises the question: how do ZoomInfo pricing plans work? What does ZoomInfo cost? And is ZoomInfo really worth it? 

This article highlights everything you need to know about ZoomInfo, including ZoomInfo pricing, overview, alternatives, and more.

ZoomInfo Overview: What is ZoomInfo? 

ZoomInfo is an end-to-end go-to-market software company that is one of the most extensive contact and company-level intelligence databases for sales marketing use cases. ZoomInfo is divided into four broad products:

• SalesOS: Contact & company search, sales automation, conversation intelligence, workflows
• MarketingOS: Cross-channel advertising, buyer intent insights, website chat, form enrichment
• OperationsOS: Data cleansing, data enrichment, lead routing
• TalentOS: Talent search, candidate outreach, employer branding

SalesOS is the most popular product in the ZoomInfo lineup, and with good reason: ZoomInfo's impressive database spans 321 million active professionals at 104 million companies. This, in combination with its advanced search filters, real-time alerts, and integration capabilities, makes ZoomInfo an attractive platform for sales marketing teams. However, it is generally considered a premium product, often out of reach for smaller teams seeking cost-effective intelligence solutions.

ZoomInfo Pricing

ZoomInfo's pricing is complex and varies based on several factors. Pricing is not publicly disclosed and is offered through a custom, quote-based structure, making it necessary to engage directly with the company to estimate costs.

Key factors influencing ZoomInfo pricing include 

• features, 
• licenses, 
• credit usage, and 
• contract length and terms. 

The number of features required, credit usage, and contract length significantly impact the overall cost.

Credits in ZoomInfo are consumed whenever an action is performed, such as viewing or exporting contact information—higher credit usage results in higher costs, requiring effective credit management to avoid unexpected expenses.

Comparing ZoomInfo pricing with competitors like SalesOS reveals a custom quote-based structure with an average annual expenditure of around $30,000. SalesOS offers more transparent pricing tiers with lower entry points, but higher-level plans can approach the costs of ZoomInfo's mid-tier offerings.

Use cases have shown that the high costs, sometimes upwards of $30,000 annually, are justified by significant ROI through improved lead generation, data enrichment, and overall sales performance.

How Much Does ZoomInfo Cost?

ZoomInfo's pricing is tailored to specific user requirements and usage, focusing on providing high-quality data and sales intelligence functionalities. Businesses should explore different pricing plans, utilize free trials, compare costs with alternatives, and use diverse data providers to optimize cost and performance in their sales intelligence efforts.

Our teams also spent a considerable amount of time talking to some existing ZoomInfo customers, and we found that the pricing was majorly based on:

• Seat-based minimum pricing
• Consumables or credits which can be bought on an ad-hoc basis

Some customers pay approximately $25,000 annually for about eight seats, while others pay $58,000 for about 21 to 23 seats. We also found that customers usually achieve a 50% discount after negotiations.

ZoomInfo Credits

ZoomInfo offers various pricing plans, each with a specific number of credits under each plan. If you need more credits, you can purchase them as needed. This credit-based system allows users to access particular contact and company information from its database for lead enrichment. Users can collect specific data with each credit, such as work email address, phone number, job title, etc. However, the credits required may vary depending on the type of information requested. 

For example, basic contact details may consume fewer credits, while more comprehensive data, like technographic information, requires additional credits.

Limitations of ZoomInfo Credit-Based Model

1. Purchasing Credits Can Increase Costs

Each credit opens a set of specific information needed for lead enrichment. Once the credits are exhausted, users have to purchase additional credits. This can be expensive for certain companies with extensive data requirements or budget constraints. 

2. Missed Opportunities

Limited credits may restrict the number of leads and opportunities a company can pursue. This affects growth, which is particularly challenging for expanding organizations or those in competitive markets.

3. Impact on Sales Engagement

Sales reps usually engage with multiple decision-makers and influencers within a target account. Each contact’s information requires additional credits, and sales reps might be unable to reach out to multiple people in the same organization. This restriction can limit the depth of engagement and reduce the chances of sales influencing the purchase decision.

New Launch: ZoomInfo Copilot

ZoomInfo has launched Copilot, an AI-powered solution designed to assist sales teams in closing deals more efficiently and effectively. Copilot leverages AI technology to provide valuable insights from ZoomInfo's B2B data, aiding sales professionals in making informed decisions and taking prompt actions. The platform aims to transform sales operations by enhancing productivity and accuracy in engaging with qualified leads at the right moment.

Key Features of ZoomInfo Copilot:

• Buying Groups: Copilot creates buying groups of individuals aligned with ideal customer profiles based on real-time signals from various sources like websites and case studies. This feature streamlines lead prioritization and ensures efficient engagement with prospects.
• Account Summaries: By aggregating first- and third-party data, Copilot provides detailed overviews of specific accounts, including pain points, upcoming deals, and key contacts. These summaries equip sales professionals with a comprehensive understanding of prospective customers, enhancing their preparation for interactions.
• Copilot Chat: This conversational AI system offers instant answers about specific accounts, enhancing the speed and accuracy of decision-making during customer interactions.
• AI Email Generator: This tool assists users in creating personalized and targeted emails at scale, optimizing the outreach process and saving time for sales professionals.

These features collectively empower users to work smarter, predict leads more accurately, streamline processes, and enhance customer engagement. ZoomInfo Copilot represents a significant advancement in sales technology, offering a comprehensive AI-driven solution to help businesses thrive in competitive markets.

Read more about Copilot from ZoomInfo’s CEO, Henry Schuck:

https://www.linkedin.com/pulse/future-gtm-ai-introducing-zoominfo-copilot-zoominfo-ef91c/

‍

Why Do Businesses Use ZoomInfo?

ZoomInfo is one of the most popular B2B sales intelligence and GTM tools today — and with good reason. Albeit not without its limitations, ZoomInfo delivers certain unequivocal advantages over its competitors. Here’s why people use ZoomInfo over alternatives:

1. Robust North America sales intelligence data

With over 320 million business contacts and 100 million companies in its database, ZoomInfo provides one of the most comprehensive sales intelligence platforms today. This holds especially true for data on companies and professionals in North American geographies. Here’s how ZoomInfo’s volume of data breaks down as of Oct 2023:Rest of the World (Excluding North America):

• 104 million email addresses
• 45 million mobile numbers
• 27 million direct phone numbers

North America:

• 70 million email addresses
• 49 million mobile numbers
• 43 million direct phone numbers

Given that approximately half of ZoomInfo’s large data is North America-focused, this is a key plus point for GTM teams with primary audiences in the US, Canada, and other North American regions.

2. Comprehensive go-to-market ecosystem

1. Comprehensive go-to-market ecosystem 

ZoomInfo is an all-encompassing GTM ecosystem catering to a broader range of sales and marketing cases. In addition to providing company and contact data, ZoomInfo offers:

• Sales (Email) Automation
• Conversation Intelligence
• Cross-channel Advertising
• Buyer Intent Insights
• Website Chat
• Web Form Enrichment
• Data Deduplication, enrichment, and cleaning
• Lead Routing
• Talent Search
• Candidate Outreach
• Employee Branding

All in all, this means that unlike other growth-stage sales intelligence platforms, Zoominfo is an all-encompassing GTM ecosystem to cater to a wider range of sales and marketing use-cases. 

3. Industry-leaders and product maturity 

ZoomInfo has been an industry leader in sales intelligence for several years, consistently improving its offering by refining its database, expanding its functionality, and enhancing customer experience. In 2023 alone, ZoomInfo achieved 100+ #1 rankings and 254 Leader Ratings in G2’s Fall Report. For the 11th quarter in a row, ZoomInfo has led the Enterprise grids for Marketing Account Intelligence, Account Data Management, and Lead Intelligence.

Is ZoomInfo Worth It?

There’s no doubt that even ZoomInfo’s basic plans are relatively steep. And given the several add-on options, the cost can quickly spiral. Whether ZoomInfo is worth it for you or your organization depends on your needs, goals, and budget. Here are a few things to consider:

1. Data requirements: Do you need contact-level data or account-level data? Do you need high-level firmographics or more granular data? Depending on your requirements, there may be better choices than ZoomInfo.
   ‍
2. Data accuracy: ZoomInfo is known for providing relatively accurate and up-to-date data. However, evaluating the data quality in your specific industry and target market is still essential.
   ‍
3. Features and Functionality: Consider whether the features ZoomInfo offers align with your goals and if they provide a competitive advantage for your sales marketing efforts.
   ‍
4. Cost: ZoomInfo's pricing can vary widely depending on your organization's size, the access level, and the specific features you require. Consider your budget and whether the potential benefits outweigh the costs.
   ‍
5. UX & CX: Ease of use and user experience are important factors. An intuitive and easy-to-navigate platform can increase efficiency and user adoption. Additionally, consider ZoomInfo's level of customer support.
   ‍

To determine if ZoomInfo is worth it for your organization, it's recommended that you request a demo, explore their free trial (if available), and gather feedback from current users in your industry. Additionally, consider your specific goals and how well ZoomInfo aligns with your strategies for lead generation, sales outreach, and business growth.

Also, read Factors vs ZoomInfo: Pros and Cons.

ZoomInfo Competitors and Alternatives

ZoomInfo is definitely in the forefront of B2B data solutions. That being said, there are several ZoomInfo alternatives worth considering — each with their own pros and coZoomInfo is definitely at the forefront of B2B data solutions. However, several ZoomInfo alternatives are worth considering, each with pros and cons. Here’s a quick rundown:

• Lead411
• Apollo
• Seamless
• LeadIQ
• Cognism

Here’s how their prices compare per account and per seat:

Zoominfo customer ratings comparison

Here’s a breakdown of how ZoomInfo customer ratings compare to its competitors (As of April 2024).

FAQs on ZoomInfo Pricing and Alternatives

1. Is ZoomInfo free or paid? 

ZoomInfo is a paid product, but they offer a free trial if you’d like to try it out before finalizing your purchase.

2. How much does ZoomInfo cost? 

ZoomInfo’s pricing is largely based on:

• Seat-based minimum pricing
• Consumables or credits which can be bought on an ad-hoc basis

3. How do ZoomInfo Credits work?

Each search or data access action consumes a specific number of credits based on the depth of the information requested. Basic details may cost fewer credits, while more detailed or enriched data can use more credits.

4. How much does ZoomInfo cost for one person?

ZoomInfo's pricing is not mentioned upfront on its website. However, users have reported on a Reddit thread that the pricing plans are primarily structured for teams. A minimum of $14,995 can be paid annually for up to three users with 5,000 credits. 

‍

5. Can I use ZoomInfo for free?

ZoomInfo does not offer a free version of its platform. Access to its database requires purchasing a subscription.