What Goes Into A Predictive Lead Scoring Model?

What’s the most important attribute to consider when building a lead scoring model? That depends on who you ask. Every demand gen leader has a different lead scoring system. Most rely heavily on gut instinct, with values and attributes that may or may not indicate whether a lead will actually convert.

With ineffective, guesswork-led models running rampant across the industry, it’s no surprise that most people consider lead scoring to be a joke.

Predictive Lead Scoring Algorithms Are Changing The Game

Predictive lead scoring uses artificial intelligence to analyze prospect data and build models that actually measure buying propensity, as well as fit. No guesswork, gut instinct or dumb luck is required. Instead, advanced machine learning algorithms do the work for you. No, really.

Fit and Behavioral Scoring Models 

Infer’s AI-powered predictive lead scoring software leverages data from your customer relationship management software (CRM) and marketing automation platform (MAP) along with Infer’s own proprietary database to build predictive behavioral and lead fit scoring models.

Infer’s fit scoring models measure just how well prospects match your ideal buyer profile, answering the question: which of my leads are the best fit for my business? Behavioral scoring models describe the relationship between prospects’ actions and actual purchase decisions. They’re used to predict if and when a prospect is likely to buy your products.

To create the models, Infer analyzes data in your MAP, your CRM, its own database and any third-party B2B data you may have. It explores thousands of data points and thousands or millions of correlations between them, discovering key signals that indicate a propensity to buy and the various combinations of attributes that make a prospect a good fit for your business.

Infer compares your prospects to the two models and scores them based on how well they match to generate highly accurate predictive lead scores. Infer’s lead scores empower your sales team with precise guidance on which leads to pursue aggressively, which ones to nurture further and which ones to ignore. It adds up to a clear, actionable roadmap for your sales strategy. 

Your business and marketplace aren’t static, and neither is Infer. As new data on conversions, behavior and prospects is collected by your systems, Infer’s machine learning algorithms continue to refine and improve its behavior and fit models accordingly. This enables the process to keep pace with evolving markets and the changing sales landscape. 

Building A Predictive Lead Scoring Model For Your Company

If you want predictive scores that are statistically proven to be accurate, it’s time to dump useless, outdated models and upgrade to an AI-led predictive lead scoring model. Here’s how Infer builds its industry-leading models:

1. Start With Your Existing Data

Your first-party data is packed with valuable insights. So that’s where predictive lead scoring starts. Infer builds each custom model by first tapping the existing data from your CRM and/or marketing automation system: information on companies, conversion history, marketing interactions and m2. Add Thousands Of Externals Signals

Then, new data is added. Infer matches each of your records against our proprietary dataset to expand the information base. We incorporate thousands of new data points for each record, including detailed firmographic and demographic information. 

3. Determine Which Signals Are Predictive

Not every signal we unearth will necessarily indicate interest level or fit. We use machine learning algorithms to search the data for deep patterns, highlighting the predictive signals and discarding signals that could lead our scoring rules off track.

4. Create The Optimal Formula

Once predictive patterns have been identified, we create a custom formula for your organization. This formula is then used to automatically score any leads that enter your system and assign a predictive value to each one.

5. Test The Accuracy Of The Model

Infer delivers statistically-accurate results. And we mean it. We test and retest the accuracy of your predictive model to ensure it generates lead scores your sales and marketing teams can rely on.

6. Push It Live Into Production

We will have you up and running with Infer in days, not months. And since Infer seamlessly integrates with your sales and marketing stack, you can start focusing on turning your leads to sales immediately.

7. Measure The Results

You will see a real increase in conversion rate, right away. Don’t believe us? Just ask Suresh.

“We have one set of leads that converts at 4x the baseline, and one set that’ll never convert. Infer helps us tell the difference between the two.” – Suresh Khanna, Chief Revenue Officer AdRoll

Check out some of the other stories from our many happy customers.

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See Firsthand How Infer Uses Your Own Data To Create Custom Scoring Models