How to Build a Lead Scoring Model That Works for You
There’s no question that lead scoring is an essential component of every modern B2B marketing and sales strategy. But smart marketers know it’s not a plug-and-play kind of strategy. To effectively evaluate and pursue the leads most likely to convert for your organization, you need to know how to build a lead scoring model that works for you.
That means understanding the traits, behaviors, and other indicators that your unique high-potential prospects possess, and building a solid lead scoring framework to identify them reliably.
In this guide, we’ll walk step-by-step through the process. We’ll cover how to build your buyer personas and ideal customer profiles, assign values to different criteria, automate the lead scoring process, leverage data insights, and more.
When you’re done reading, you’ll be equipped to develop a lead scoring strategy that can quickly identify the best leads in your sales pipeline so your sales reps can engage them effectively and close more deals.
Quick Takeaways
- Lead scoring is a data-driven method for prioritizing leads, central to modern B2B marketing and sales strategies.
- Knowing how to build a lead scoring model that works for you and your unique target audience is essential for maximizing lead scoring ROI.
- Building an effective lead scoring framework requires developing solid buyer personas and ICPs, leveraging data, and automating the scoring process.
- Regular evaluation and refinement of your lead scoring model ensure that it remains aligned with changing market trends and customer behaviors.
- Using a test-and-learn approach with your lead scoring model can help you effectively implement incremental improvements over time.
First Thing’s First: What Is Lead Scoring?
Lead scoring is a data-driven method for ranking and prioritizing leads in your pipeline. It’s an important practice for every company now that lead generation and sales prospecting efforts can be performed at scale using technology tools.
Leads can be scored based on a wide range of criteria:
- Professional Traits: Can describe individuals (i.e. job role or level of experience) or company (i.e. industry or company size)
- Demographic Data: Attributes like age, gender, and location
- Online Activities: Informed by web tracking analytics to understand how leads interact with online pages and content
- Lead Source: Where the lead came from (for example, a direct referral vs. an online ad click)
The weight you give each item depends on what criteria are most important to your organization. In some cases, the job role of the purchase decision maker takes precedence over all other criteria (for example, if you’re selling a financial solution designed for CFOs).
In other cases, it may be company size and budget that play the biggest role (like if you’re selling an ERP designed for large corporations).
In most situations, there’s no single factor defining the best leads. It’s a combination of factors, all assigned a value as leads move down the pipeline. The lead scoring framework below is a common one, in which companies start with ideal client profile and buyer persona attributes, then move on to buyer behaviors later on.
How to Build a Lead Scoring Model That Works for You: 5 Essential Steps
1. Define Your Ideal Lead
Have you developed your ideal client profiles (ICP) and buyer personas? If not, this is the place to start. Knowing what your ideal lead (and thus, ideal client) looks like is the foundation of your lead scoring framework.
Your ICP should describe the type(s) of organization that are best-fit for your solutions. Buyer personas should describe the individuals within those organizations who make purchase decisions.
Once you have ICPs and personas developed, you can list all of the attributes you included and decide which ones should be part of your lead scoring model.
2. Assign Values Across Your Lead Scoring Framework
Next, assign a value to each criteria that’s part of your lead scoring model. You can do this using a numerical value (most common), or you can use another rating method that works for you.
Many CRM tools have built-in lead scoring methodologies to choose from. For example, in Salesforce you can leave a lead score between 1-10 to indicate level of interest, and a lead grade between A-F based on ICP fit.
Whichever method you choose, be sure it’s clearly defined so that your sales reps can apply it consistently.
3. Don’t Forget Negative Score Criteria
Just as you assign high-fit attributes and high-intent behaviors with a positive lead score, you can and should assign negative scores to leads that are moving in the opposite direction.
For example, a motivated buyer may receive a negative score if your solutions are out of their budget range. A buyer that fits your ICP may receive a negative score if they unsubscribe from your emails or skip scheduled demo meetings.
The image below shows a sample lead scoring model with both positive and negative values incorporated.
4. Automate Wherever Possible
Manual lead scoring isn’t practical in a business landscape where speed and scale take prominence. It’s prone to slow execution and human error. Rather than risk leads getting lost in the pipeline or taking too long to engage, automate lead scoring in your CRM system so that it’s a more seamless part of your sales process.
Most marketing tools, like email marketing or paid ad platforms, are now designed to integrate easily with your other tools to make automation easy.
5. Look for Trends (and Adapt Accordingly)
Lead scoring is an inherently data-driven process, but it’s important to look beyond initial lead scores and see trends that can help optimize your lead scoring framework. This is one of the reasons that data-driven systems like your CRM are so important.
For example: You might have a buyer action on your lead scoring model that has a high value assigned to it, but you notice buyers taking that action convert at a low rate. In this case, that criterion should be reevaluated to determine if it warrants the value it’s been given.
On the other hand, you may have a specific buyer trait, like a job title or specific pain point, that isn’t prioritized in your lead scoring framework but is proving common across your converted buyers. This criterion must be added to your model to ensure you engage these prospects effectively when they enter your pipeline.
Evaluating and Refining Your Lead Scoring Model Over Time
To ensure your lead scoring model remains effective and aligned with your evolving business needs, it’s crucial to regularly evaluate and refine it. This process helps in adapting to changes in market trends, customer behaviors, and your organization’s strategic goals. Here are key actions to consider:
Set Up Regular Review Cycles
Establish a schedule for periodic reviews of your lead scoring model. This could be quarterly, bi-annually, or annually, depending on your sales cycles and market dynamics. These reviews allow you to assess the model’s performance and identify areas for improvement.
Leverage Analytics for Insights
Utilize the built-in predictive analytics capabilities of your CRM and marketing automation tools to gather insights on the model’s effectiveness. Look at conversion rates, engagement levels, and the accuracy of lead prioritization.
Analyzing this data helps pinpoint which criteria are strong predictors of lead quality and which may need adjustment.
Incorporate Feedback from Sales and Marketing Teams
Your sales and marketing teams are on the front lines, interacting with leads and observing their behaviors. Gather their feedback on your lead scoring framework’s accuracy and usability.
They can provide valuable insights into which criteria are most indicative of a lead’s readiness to buy or potential fit for your solutions.
Adjust for Market and Behavioral Changes
As your market and customer behaviors evolve, so should your lead scoring model. If new trends emerge or product offerings change, update your model to reflect these developments. This ensures that your lead scoring criteria remain relevant and effective in identifying high-quality leads.
Test and Learn
When making adjustments to your lead scoring model, adopt a test-and-learn approach. Implement changes on a small scale initially, then monitor their impact on lead quality and conversion rates.
This iterative process allows you to refine your model with minimal risk and optimize its effectiveness over time.
By regularly evaluating and refining your lead scoring model, you can ensure it continues to serve as a powerful tool for identifying and prioritizing the leads most likely to convert, maximizing the impact of your sales and marketing efforts.
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Schedule a quick call with us and find out how we can help you win more clients.