7 Factors of an Effective Lead Scoring Model

    Last updated: May 15, 2024

    The explosion of new marketing platforms has made the customer journey much more fragmented and customized. While giving people more places to find you is a net positive, it makes it more difficult for marketers to reach the right people with the right message at the right time.   

    But with a good lead scoring model, you can assess each person’s readiness to buy at a glance, focus your marketing efforts on the right prospects, and personalize your outreach for their needs.

    In this post, learn how to create a lead scoring model that delivers the right leads — without demanding extra effort from your team.  

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    What is lead scoring?   

    Lead scoring uses a point-based system to assess each prospect’s potential readiness to buy your product or service. Most models award points to prospects for completing different activities that indicate their interest in buying your product or service, like opening an email and clicking through to your website, or reading a mid- or bottom-funnel resource, like a case study.   

    When the prospect reaches a specific number of points, they’re considered sales-qualified, at which point a business development team member reaches out to initiate the sales process. 

    Done right, lead scoring helps you pursue the right prospects and prioritize your resources more efficiently. But if your model weighs one kind of interaction too heavily, fails to take others into account, or deems prospects “sales-qualified” at the wrong time, you miss opportunities to earn easy wins and drive revenue.  

    Next, we’ll tell you how to create a lead scoring model that smoothes the path to sales.  

    7 Factors of an Effective Lead Scoring Model  

    A single customer view 

    Your lead scoring model will live and die by your customer data. Since lead scores are based on the totality of someone’s interactions with you, your lead scores won’t be accurate or complete if the underlying data isn’t also accurate or complete.   

    So the rest of these tips won’t get you anywhere if your data is scattered across 10+ marketing solutions. This makes your lead scoring methodology less reliable: You might overestimate someone’s level of interest or miss opportunities to engage them down the road.  

    Ensure that all your audience data is being stored and managed in one place by investing in a CDP, which collects first-party data from every marketing touchpoint, then cleans, standardizes and manages that data via automated workflows.  

    Omeda’s CDP collects first-party audience data from every marketing touchpoint — from emails and events to print, ads, website tracking and more — and collects it into one database. Then the data is standardized and cleared of duplicates according to automated workflows.   

    When it’s finished, each of your customer profiles contain that person’s full engagement history with your brand across every channel — and their lead scores are more likely to reflect their true level of interest.    

    Sales and marketing alignment  

    Once your data is clean and complete, focus on your lead scoring methodology. To ensure your model recommends the right prospects, ask your sales team for common characteristics of people that are most and least likely to complete a purchase.  

    These can be demographic in nature (e.g., specific industries, job titles, or locations) or behavioral (e.g., people that have attended the company’s conferences are more likely to convert than those who only read website content), or a combination of the two.   

    From there, you can assign points to demographic, firmographic and behavioral data points that are most predictive of a future purchase.  

    In Omeda, you can create rules and assign points right within our platform. Then you can use our Audience Search function to query anyone with a certain level of points and place them in a dedicated marketing segment — all in a few clicks.  

    Implicit actions    

    Often people who buy your product will exhibit certain behaviors indicating intent to purchase, like attending an event or signing up for your newsletter. These are called implicit actions — observed behaviors that don’t come directly from your audience, but still imply that they’re interested in learning more about you.   

    Your lead scoring model should include this information, including:  

    • Looking at someone’s actions to infer their level of interest in your product/service (e.g, signing up for your newsletter, reading a blog post) 
    • Looking at someone’s demographic profile to infer their fit for your product/service  

    To set up an implicit lead scoring model, review all of the ways that someone can interact with your company and assign point values for each one. For example, a person downloading a white paper may be worth 10 points. But if they don’t interact with the website for a month, they may lose 15 points.  

    (Note: The weighting of each action relative to the others is also incredibly important, but we’ll get to that later in the article.)  

    Explicit information  

    To contrast, explicit lead scoring is based on information that you’ve received directly from the prospect (through form submissions, event registrations, etc.).  

    Explicit information is valuable because it tell you whether your campaigns are reaching the intended group. If you’re targeting audience development managers but you keep getting form submissions from subscription teams, reconsider your targeting and campaign placement so you can attract higher-quality leads.  

    The right lead scoring weights  

    If you don’t understand which actions are most predictive of a future purchase, and their relative importance, you risk reaching out to leads too early and alienating them. (If you’ve ever gotten a series of very aggressive cold pitches from a company two days after signing up for their newsletter, you’ve seen this in action.)  

    Collaborate with your sales team to determine how many points to assign each action. We’ll go through an example below:   

    Say that someone goes from prospect to sales-qualified when they reach 50 points. Reading a blog post might be 1 or 2 points because while it does indicate interest in something your company is doing, you can’t be sure whether it was the specific topic or your product that caught their eye.  

    Subscribing to your newsletter, however, implies a broader interest in everything your company is doing — and a willingness to hear more. So this might be a 5-point activity.   

    However, neither of those activities are strong purchase signals, so it would take sustained engagement over a long period of time for that person to become a sales-qualified lead.  

    But if they download and read one of your case studies, you can reasonably assume that they’re considering making a purchase. So this might be a 25-point activity. By itself, it won’t make someone a sales-qualified lead. But if the person’s been engaging with you for a while, their case study download might catapult them over the 50-point threshold — and render them sales-qualified.    

    Negative lead scoring  

    Just as your lead scoring model needs to register positive interest, it also needs to track indicators of lost interest — like unsubscribing from a newsletter — or signs of a poor product fit, like being in the wrong industry or working for a company that has already churned. Look for lead scoring solutions that allow you to subtract points in these circumstances.  

    Different interest tiers 

    So far, we’ve been discussing lead scoring as if it’s a binary process: Either someone is 100% ready to buy this quarter or they’re off the list for good.  

    That’s not always the case, especially as buying processes become longer and more involved.   

    Chances are, many people in your audience are passively considering a purchase. But they’re not ready due to circumstances outside their immediate control, like their quarterly budget or their CTO’s approval. A good leading scoring model will account for this and allow you to create intermediary levels of interest between “ready to buy right now” and “not ready anytime ever.”  

    For instance, with Omeda, you can create Gold, Silver or Bronze tiers for prospects with different levels of readiness. This allows you to target content and strategy to each sub-group, and helps you further fine-tune your approach to their needs.  

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