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Predictive Lead Scoring: Discovering High Quality Leads Using Data

5 min

You get two leads, each from a different source. The first one read a blog post on your website. The second one went through multiple pages on your site and proceeded to fill out a web form as well. 

Clearly, the latter is more interested, and so, you focus more of your efforts on them.

But what if you’re handling a CRM with thousands of leads? 

How do you know who reached your site through organic search? How do you know who spent the most time on your site? How do you know which leads show maximum engagement over the others?

The answer lies in predictive lead scoring.

What is Predictive Lead Scoring?

Predictive lead scoring is the lead scoring process that uses predictive machine learning algorithms to analyze data from historical and existing customer base to predict the best prospective customers in the future.

How does predictive lead scoring work?

How does predictive lead scoring work?

Basically, the predictive lead scoring method creates an ideal customer profile (ICP) for you based on your past customers. This ICP is then used as a model to evaluate new leads such that the closer to the ICP a lead is, the higher the lead score, and vice versa. 

To understand predictive lead scoring better, let’s compare it to its predecessor, the traditional lead scoring model.

Lead Scoring Models: Traditional vs Predictive

What is a lead scoring model?

A lead scoring model, as the name suggests, is a model designed for the purpose of evaluating leads. A lead is assigned points based on several factors varying from the industry they work in, to their engagement with your website.

Past customer behavior is the key to lead scoring models. If your previous customers have always shown a high level of engagement with your content, it is assumed that fresh leads showing similar levels of engagement are more likely to convert into customers as well. These leads are thus, assigned more points than leads that do not meet this criterion.

What is a lead scoring model?

1. The Traditional Lead Scoring Model

In the traditional lead scoring model, marketers manually select a few key actions based on their own idea of what caused leads to turn into customers in the past. These actions are then used to assess the potential of future leads.

However, marketers rely on their own interpretation and judgment in the traditional lead scoring model. And this might leave space for human error, misinterpretation, and miscalculations. They may end up assigning too much weightage to an action that may not be relevant, or assign too little to key actions.

That’s why the traditional lead scoring model is mostly replaced by the predictive lead scoring model today.

2. The Predictive Lead Scoring Model

The predictive lead scoring model fixes the shortcomings of the traditional lead scoring model by leaving no space for human error and automating the entire process. 

It employs machine learning algorithms and predictive modeling techniques to predict future customers based on the behaviors of past customers. 

But how exactly does this happen? That’s precisely what we’re about to discuss next.

How Do You Automate Lead Scores?

Machine learning algorithms recognize trends from customer databases by analyzing historical and existing customer data. This may include various customer touchpoints like visiting landing pages, filling web forms, watching webinars, opening emails, etc. It uses these trends to establish patterns and creates an ICP to assess future leads.

In B2B sales, each lead requires extensive nurturing. The solution needs to be tailored depending on their needs. Copious amounts of time and energy get wasted if all this effort goes to a lead with poor potential. But machine learning in predictive lead scoring makes sure that these efforts are directed toward the leads that are most likely to convert.

How Do You Automate Lead Scores?

How Slintel Provides Enhanced Data For Your Lead Scoring Needs

Unlimited Lead Insights

Slintel provides you with fresh, updated, and accurate lead insights for your lead scoring needs. For this, we regularly keep track of over 286 million leads from over 14.5 million companies. 

In addition, Slintel provides you with just the right technographic, firmographic, and demographic info you’ll need to accurately score your leads. Once you have access to our accurate lead insights, you’re free to score leads as per your criteria and prioritize the right accounts for your business.

Unlimited Lead Insights


“Lead Scoring might sound simple. However, if you’d want your Sales Dev team to crack more qualified meetings, you’d need strong insights on “Fit vs Interest” and that’s what you get from Slintels Lead Insights!”

—Jason Dsouza, Sr. Associate, Rev Ops at 6sense

Buying Intent Scores for Your Leads

The buying intent of an individual or organization can be defined as their likelihood to purchase a product or service. An entity’s buying intent can be inferred by examining and evaluating behavior such as webpage visits, media consumption, demo or meeting requests, collateral downloads, event participation, and form submissions.

Buying Intent Scores for Your Leads


For every organization that you wish to prospect, Slintel shows you a buying intent score. Your customers’ buying intent score can be used to determine the lead behavior. Your predictive lead scoring model can then compare this behavior to the behavior of your previous or existing customers and thus, determine your lead score.

Accurate Lead Data and Lead Enrichment

Inaccurate lead data in your CRM has the potential to severely derail your lead scores. This can cause your reps to misinterpret leads with immense buying potential as pointless leads, leading to several missed opportunities.

To prevent you from missing out, Slintel has the most accurate, updated lead info to fill up your CRM. You get to not only update your existing lead info with more accurate info but also fill in the blanks on missing data fields with correct information. 

More accurate lead data, undeniably, translates to better lead scores and lesser missed opportunities.

Accurate Lead Data and Lead Enrichment


Alternate Leads to Keep Your Options Open

Sometimes, a lead may not be the best choice for you even if they’re from an organization with immense buying potential. This could be for a variety of reasons ranging from their lack of decision-making authority to their unresponsiveness despite your attempts to reach out. In such scenarios, it’s always better to have alternate lead choices from the same account. 

As a Slintel user, you get access to several leads from a single account, all of which come with the required contact details. That way, you know you’re equipped with everything you need to contact your highest-scoring leads.

Check out Slintel today!

The 6sense Team

6sense helps B2B organizations achieve predictable revenue growth by putting the power of AI, big data, and machine learning behind every member of the revenue team.

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