2. Lead scoring

It isn’t the fault of MQLs. It’s a data visibility problem.

The state of the marketing qualified lead

As we just mentioned, the MQL has become a serious point of contention between marketing and sales functions in recent years. But if you want to resolve those tensions and “fix” the MQL, you first need to understand what’s driven the lack of faith in marketing qualified leads.

The biggest contributor to poor perceptions of MQLs is that they’re typically built on assumed engagement, driven by a lack of first-party engagement data. Marketers have built lead scoring models based on the interactions and insights available to them—clicks on emails and links leading to PDF documents—giving them a shallow view of what’s really going on.

This lack of insight into prospect engagement has made lead scoring models unreliable and has misled businesses about which prospects are showing genuine intent. As revenue targets have grown and expectations on marketing to deliver have increased, most marketing functions have refused to acknowledge that the leads marketers provide aren’t at the level of qualification needed to be passed over to sales.

To close the gap, marketers must transform how they score leads, refocus their content to make engagement metrics more visible, and shift how they design their nurture programs.

If you’ve lost faith in MQLs, why?

We don't have the insight to generate a true view of intent
Qualification processes are rushed or incomplete
Marketing and sales aren’t aligned on what makes a prospect “qualified”

Thresholds and setting score values

One of the most important and often overlooked components of a lead scoring model is the threshold value.

It’s important to align the threshold value with the individual scores for each interaction. If your threshold value is too low, you risk qualifying prospects too early and perpetuating the broken MQL model. If you set the threshold too high, you may miss out on prospects with enough education and intent to be interested in your offering.

To start, define how many touchpoints are needed to qualify a lead—and be realistic. If a prospect has only had two interactions with your brand, they’re unlikely to reply to direct communications. Is interacting with a case study a stronger indicator of a prospect with a more urgent need than someone visiting the website homepage? Once you’ve determined what actually represents high intent, you can set your scoring criteria accordingly.

The secrets to better lead scoring models

See what it takes to deliver exceptional, accurate, and impactful lead scoring models in our deep-dive blog.

Read now

The secrets to better lead scoring models

See what it takes to deliver exceptional, accurate, and impactful
lead scoring models in our deep-dive blog.

Read now

What is a lead scoring model?

Lead scoring models enable the systematic measurement of prospect interactions, giving you a numerical figure that can be used to judge engagement and act as a basis for contact routing between marketing and sales. It’s the ultimate foundation for the marketing qualified lead and provides one of the main leading indicators for the pipeline.

Before you can build an effective lead scoring model, there are a few things you need to establish:

01

A threshold value that you want your prospects to hit that represents the level of interaction needed for qualification

02

A nurture program that communicates with your prospects and drives their continued engagement with your content

03

A tracking method for the various engagement points available to your prospects

Don’t forget to test

Very rarely are lead scoring models perfect from their inception. Testing and iterating on your model are an important part of the process. Make sure you take the time to:

Check whether high lead scores are leading to high pipeline conversion
Ensure your model isn’t missing valuable leads
Manually validate the true strength of the leads being given high scores by your model

Don’t forget to test

Very rarely are lead scoring models perfect from their inception. Testing and iterating on your model are an important part of the process. Make sure you take the time to:

Check whether high lead scores are leading to high pipeline conversion
Ensure your model isn’t missing valuable leads
Manually validate the true strength of the leads being given high scores by your model

Using firmographic data
in lead scoring

Marketing teams with a greater level of maturity also commonly use firmographic data to assist in prospect qualification.

Applying firmographic data (also known as propensity scoring) as part of your scoring model can help you accelerate prospects that are a good fit for your business across characteristics such as industry, persona, company size or even region. If executed correctly, leads with a higher chance of converting into customers will be prioritized and qualified quickly.

Suboptimal prospects must show higher engagement and intent before being passed to sales.

However, it must be handled with care. If you don’t have a strong understanding of your ideal customer profile and which characteristics lead to stronger win rates, you risk prioritizing the wrong attributes, which can undermine the performance of your entire lead scoring model.

The practical guide to
long-form lead generation

Discover how to create engaging long-form content for lead generation that gives you the insights you need to understand the impact of your campaigns and continuously improve performance.

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Lead scoring with engagement data

For a lead scoring model to work, it’s critical that leads are scored using first-party engagement data that you can trust.

That’s where a lot of models fall down. Teams simply don’t have access to enough visible engagement data to draw reliable conclusions about engagement, so they end up filling the gaps with assumptions—undermining the entire model.

The solution is to simply make more engagement data visible and accessible to marketing teams. But that isn’t always easy.

If you’re operating with limited engagement data, here are a few tips that can help you optimize lead scoring:

If you’re operating with limited engagement data, here are a few
tips that can help you optimize lead scoring:

01

If you’re limited to using PDFs or website scoring, understanding which content or web pages are associated with higher intent can help you quickly qualify prospects.

02

Focus your attention on the point of conversion and take a detailed look at the final steps buyers have taken before reaching the point of purchase. That can help you isolate extremely high-intent actions that demand immediate sales intervention.

03

Weight engagement interactions according to their recency, frequency, and value. In other words, take into consideration how recently the interaction occurred, how often the prospect has engaged, and the value of the content read.

04

Ensure that scores are degraded over time. A prospect’s intent is likely to fall—or completely disappear—as time passes following their engagement. So, scores should be updated to reflect that and ensure sales can focus on prospects that are close to conversion today.

Online documents and
their role in scoring

While using firmographic data or scoring your content by journey stage can improve the performance of your scoring model, it doesn’t offer a solution to the “assumed intent” problem.

There is no substitute for reliable first-party engagement data. The more you gather, the stronger your lead scoring models will be. And your ability to gather it depends on the types of content you publish.

Static formats like PDFs offer little opportunity to gather meaningful engagement data beyond link clicks. So, marketers need to try something different—and interactive online documents are a great place to start.

Interactive online documents enable marketers to not only design their content for stronger engagement, but also accurately measure and model against real interactions.

The introduction of interactive elements such as embedded video, polls, or audio has been shown to significantly boost engagement with long-form documents.

Those interactive elements function as engagement triggers, enabling marketers to visualize engagement at a granular level, and use that insight to significantly improve the performance of their lead scoring models.

If you use PDFs rather than
interactive online document
formats like Turtl,
you’re missing out on

90% of reader engagement¹.

Just how much does interactivity
impact engagement?

See how interactive online document
formats like Turtl stack up against static PDFs in this report by Lumen Research.

Read now

¹Lumen research: https://team.turtl.co/story/lumen-research-engagement-perception/page/1