Keys to B2B Lead Scoring Using Buyer Intent Signals

September 16, 2021
Contributor: Aaron Henckler

Lead scoring for your B2B business helps prioritize your top sales opportunities, accelerate your funnel and convert prospects into high-value customers.

Your B2B software company is more successful when you focus on selling to organizations of a certain size, type, or industry. But beyond those basic targeting metrics, how do you determine which leads are the most valuable to your business and the most likely to become winning sales opportunities?

Most marketing and sales teams know what their best lead sources are, but without any system for qualified lead management, sales reps spread their efforts equally across all prospects. Lead scoring for your B2B business prioritizes top sales opportunities in order to improve your lead management process and accelerate your sales funnel.

A lead scoring system will set quantifiable parameters to determine which leads to prioritize and invest time and effort into, so you can convert them into high-value customers.

What is lead scoring and why is it important?

A lead scoring model ranks prospects according to the perceived value they represent to your company — in terms of the revenue opportunity and the likelihood of a purchase.

You score leads by assigning fit and behavior scores that separate sales-ready leads from others. To do so, your marketing and sales teams use buyer intent data to identify traits or actions that indicate a lead’s profile fit, funnel stage and willingness to buy.

Why should you care about lead scoring?

Ensuring leads are properly qualified before handing them off to sales is critical for developing a healthy pipeline. Effective lead scoring is one of the best ways to achieve these high pass-through rates and to close deals on a higher proportion of opportunities. Using buyer intent data, you can see which leads are ready to buy and which still need nurturing down the funnel.

To use lead scoring models, your organization needs data on account histories and activity logs to identify a prospect’s characteristics and behaviors that can be used for scoring. Then, you assign points to each trait and action, and define the follow-up process for marketing and sales reps based on the lead scores.

According to Gartner, companies with a high conversion rate use an average of four criteria to score leads. That means you don’t need dozens of factors weighing into a lead’s ranking, but instead should look at past conversions to establish specific criteria that identify the best leads to pass on to sales. (Full report available to Gartner clients).

Cutting through the noise, knowing what data to use and analyzing the right intent signals is key to scoring leads effectively and converting customers.

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How to calculate a lead score based on intent signals

The first step to calculating a lead score is understanding key demographic and firmographic characteristics of target customer segments. As a B2B software provider, you should know which prospects have the attributes and behaviors that make them high-quality leads. You should also qualify leads based on their potential lifetime value as a future customer.

With that data, assign points to each lead based on their demographics, behavior, funnel stage and potential deal size. Distribute weights to lead scoring categories based on your marketing and sales teams’ definition of a high-quality lead.

What type of behavior is important for lead scoring?

A prospect’s behaviors and actions should be weighted based on the extent to which they indicate their buying journey maturity, along with their readiness to change.

Assign points to a prospect’s engagement based on the type of content and its alignment to their progression through the sales funnel. For example, downloading an implementation guide would receive more points than a blog article about industry trends.

To complement lead scoring models, software providers can leverage third-party intent data, first-party engagement data, and marketing automation platforms to better understand which prospects are further down the funnel and more ready to buy.

High-conversion-rate companies also heavily weigh the prospect’s willingness to advocate as one of the most important criteria for scoring leads, according to Gartner. The most valuable contacts are prospects who are ready to move along in the sales cycle (full report available to Gartner clients).

What signals do you need to score SaaS leads?

You can tap various data from your website, content engagement, CRM system and third-party intent data providers to create a lead scoring system that works for your business.

The two main lead qualification categories are for profile fit and behavioral fit, according to Gartner (full report available to Gartner clients):

Profile Fit Scoring

  • Demographics. Basic demographic information, including job level and experience level.
  • Firmographics. Company information such as revenue and location.
  • Technographics. The mix of technologies used by the organization.
  • Relationship-based. Online behavior such as content engagement and sales conversations.

Behavioral Fit Scoring

  • Openness to change. Indicates the lead’s interest in the product.
  • Group readiness to change. Behavior that indicates intent to create a group consensus on purchase.
  • Buying job completion. Signals the lead’s progress through the buying journey.

A crucial part of both profile fit and behavioral fit is a prospect’s engagement with your company. This can include several data points:

  • Site visits. Prospects that are visiting your website and your high-value pages.
  • Frequency and recency. Prospects that return to your website and view your offerings
  • Content consumption. This includes event and webinar attendance.
  • Third-party intent data. Prospects that visit other sites to research products or services
  • Engagement. With sales development reps.

When measuring intent signals, favor lead scoring toward content that correlates with previous conversions and reflects a lead’s willingness to advocate for your software within their organization. Likewise, intent signals from software reviews sites are especially useful for B2B businesses, by attracting only audiences that are highly likely to make a technology purchase.

Measure and improve your lead scoring model

Lead scoring is not a “set it and forget it” process. Software providers must continually score incoming leads’ actions and regularly update the scoring model.

Additionally, for each score threshold, organizations should refine follow-up actions for marketing and sales based on leading indicators of conversion. Sales outreach related to previous interactions or website traffic is the most effective for improving lead acceptance, according to Gartner.

With ongoing collaboration between your sales and marketing team, consistently monitor sales’ follow-up rates and win rates on each marketing qualified lead (MQL).

Here are questions that can influence your lead scoring model, according to Gartner:

  • What type of campaigns or content drive top prospects into the sales funnel?
  • Where are the biggest mismatches between the lead scoring system and marketing campaigns?
  • What are the most common reasons for sellers to reject marketing-qualified leads?
  • Do the qualified leads lack any critical characteristics or have undesirable traits?
  • What are the most common challenges sellers face in winning deals from qualified leads?
  • Where does the scoring method fail in tracking a prospect’s interest in the product?

With a data-driven, constantly evolving lead management process, your B2B organization will find higher productivity for your team and more opportunities to engage high-value prospects.


Learn more about collecting and using intent signals in our webinar, “Launch Your ABM Strategy with Buyer Intent Data.” Register Now.

Aaron Henckler

Aaron Henckler is the Managing Vice President of New Market Programs for Gartner Digital Markets. He is an experienced strategy consultant and proven operations leader with a track record of establishing scalable capabilities in product development and insights generation. When not at work, Aaron likes to spend time with his family and break it down on the dance floor. Connect with Aaron on LinkedIn.

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