Combining Website Traffic and Product Usage to Identify the Best Leads using Segment and Correlated
Combining Website Traffic and Product Usage to Identify the Best Leads using Segment and Correlated
Diana Hsieh
Product News

Combining Website Traffic and Product Usage to Identify the Best Leads using Segment and Correlated

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If you’re a growth marketer at a B2B SaaS company, you’re going to want to listen up! Correlated just released built-in support for Segment Page events so that you can leverage even more information to build the best lead scoring models. Perhaps you’re already sending MQLs to SDRs, and maybe you’ve set up some PQLs that get directly routed to AEs. Well, I’m here to share how you can further level up that strategy by combining the two to truly develop the best lead score that can help you prioritize and route leads. 

Combining website traffic and product usage results in better leads

MQL vs PQL… at the end of the day, all leads are leads, and in some ways we’ve nitpicked how we define these leads in a way that isn’t entirely actionable. One of the reasons why many companies split up MQLs and PQLs is because the data that flows into these two scores come from different sources, and it’s hard to combine the two. But let’s ignore that challenge for now and imagine a world where website traffic is combined with product usage to identify buying intent. In this world, you’ll be able to:

  • Use a more complete picture of customer behavior to score leads
  • Filter out highly active users who aren’t good prospects

The more complete your customer behavior tracking is, the better your score will be

As we all know, what goes into a scoring model determines what comes out. If you aren’t tracking the right data points about your customer, your scoring model won’t have enough to work off of when building out a score. By combining website traffic with product usage, you’re allowing your scoring model to develop a complete picture of how buyers are not only using your product, but also how they are researching your product as they make their buying decision. 

Not all active users are good prospects

In PLG land, we all know that some of the most avid users of your product will actually be free users forever. They might be great advocates for your product, but they don’t have the use case (or buying power) to merit needing sales involvement. By combining website data with product usage, you can identify which users are more likely to be buyers. Perhaps it’s the person who requested the demo, or it’s the person who keeps visiting the pricing page. Perhaps your champion is the one who keeps visiting your docs. Website behavior can help filter out those who are using the product vs those who are displaying buying intent. 

Combining website traffic and product usage results in more actionable leads

Website traffic provides an additional lens into understanding the buyer journey

Product usage, although critical, isn’t always tied to buying intent. Let’s say, for example, that a user opens a modal to integrate Hubspot then closes it without connecting it. The user has a high propensity to buy given all the factors used in the lead scoring model, so a salesperson gets sent this info. Now, a salesperson might take action with an email mentioning that they noticed the user tried to connect to Hubspot. What if the user just accidentally clicked the wrong button? If you pair product usage with website traffic, you can further augment that outreach with documentation views. For example, maybe the customer actually viewed the Salesforce integration docs. Now the salesperson can reach out with a more generic offer to help with CRM integrations!

Website traffic offers real-time intent triggers that can guide outreach

Beyond just providing more information about a user and how they are interacting with your various assets, website traffic can also be used to trigger real-time outreach. Scores are often defined as a weighting of a variety of different factors. No one trigger defines when an account becomes a “high scoring” account. That means that high scoring accounts simply get dumped onto sales with no actionable feedback on how to reach out. By combining website traffic and product usage, you can now layer real-time intent signals onto scores. For example, a high scoring account visits your pricing page, but doesn’t sign up for a demo. Reach out! Or, a high scoring user tries to use an upsell feature but fails to convert. Reach out! Your outreach can now be based on exactly how the user is experiencing your product at that moment and will be significantly more personalized and relevant. 

How Correlated makes it possible to combine product usage, website traffic, and scores to act on the best leads

With our newest launch of built-in support for Segment Page Events, it just got a lot easier to combine product usage with website traffic to both score leads and act on them. 

How to get started with Correlated and Segment

Connecting to Segment is incredibly easy - all you have to do is authenticate into Segment and send us events. We recommend sending us events from both your website and your product. We leverage emails and domains to identify users and accounts, or you can provide us with userIds and accountIds that uniquely identify users and accounts. Once Segment is connected, we automatically start tracking the events that are coming in, and we also automatically parse URLs. You can easily find users who viewed your pricing page and signed up in the last week. 

Creating Lead Scores using Segment Data

Once your data is connected from Segment, you can pop into our self-serve Scoring tab to build your own scoring models. These models score intent across the entire lifecycle, from conversion to expansion and everywhere in between. Correlated will use AI to figure out which users and accounts are most likely to achieve a customer lifecycle goal, and you’ll be able to use these scores to build prioritized account lists for your sales teams. 

Acting on the best Leads

Correlated makes it incredibly easy to act on the best leads, either in a manual or automated fashion. For manual outreach, sales reps can view explanations in Correlated on why an account or user is a good lead, as well as see the most recent events tied to the account or user. This combination of information allows sales reps to craft a personalized outreach based on both real-time intent and overall score. For automated outreach, you can build automated Playbooks that can route leads to downstream marketing automation tools or CRMs. 

You can see how Correlated makes it incredibly easy for you to combine all the data you have about a customer, build lead scores, and actually deploy outreach campaigns. If you found this post helpful, I’d recommend you take a look at our 2023 Guide to Lead Scoring.

Interested in learning about how Correlated can help your PLG company uncover expansion and upsell opportunities?

Sales and revenue leaders at PLG companies, like yourself, are faced with unique challenges. Using tools like Correlated can help sales and marketing teams identify new accounts that are ready to convert, or can help to notify your team for expansion and upsell opportunities.

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