How to Build a Lead Scoring Model That Works for You
Today’s B2B buyers now expect hyper-personalized experiences tailored to their unique needs. There’s only one problem — sales teams don’t have time to provide it for everyone.
It’s true that marketing automation and other technologies have made the sales process more efficient and scalable, but the challenge still remains for sales employees to prioritize the right leads with the limited time they have.
Enter: lead scoring.
Lead scoring focuses on organizing leads in the pipeline by potential so that your sales reps can focus first and foremost on the ones most likely to convert. In the sections that follow, we’ll walk through the basics of lead scoring, why it’s so important, and how to build a lead scoring model that drives results for your company (with example templates).
- Lead scoring is based on a wide range of criteria like professional attributes, demographics, online behavior, and lead source.
- Most lead scoring models combine different types of lead scoring data weighted differently by organizational priority.
- Ideal client profiles and buyer personas are foundational resources for building new lead scoring models.
- Lead scoring can be made highly automated by integrating CRM systems with other marketing and sales tools.
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 criterion depends on what’s 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 that defines the best leads — it’s a combination of factors, all assigned a value as leads move through the pipeline. The lead scoring model below is a common one, in which companies start with ideal client profile and buyer persona attributes, then move on to scoring buyer behavior as leads become more active.
How to Build a Lead Scoring Model in 7 Steps
Know what your ideal lead looks like
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 strategy.
Your ICP should describe the type(s) of organization that would best benefit from your solutions. Your buyer personas should describe the people within those organizations who make purchase decisions.
Once you have these frameworks built out, you can list out all of the attributes you included and decide which ones should be part of your lead scoring model.
Read more about developing your ICP (with templates to guide you).
Assign values to different criteria
Next, assign a value to each piece of 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 systems 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 sales reps can apply it consistently.
Don’t forget negative score criteria
Just as you assign good-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.
Automate as much as possible
Manual lead scoring processes are prone to slow execution and human error. Rather than risk leads getting lost in the pipeline, automate lead scoring in your CRM system to make it a seamless part of the sales process. Most marketing tools will integrate directly with Salesforce to centralize your lead scoring data in one place.
Make data-driven decisions beyond initial lead scores by looking at long-term trends related to your model. For example, a buyer action that has a high assigned value but earns low conversion should likely be reevaluated. Conversely, an action that’s rated lower but yields surprisingly high ROI should be adjusted to a higher value.
Improve and evolve
Thanks to the data available to you through your CRM, sales prospecting tool, marketing automation platforms, and other tools, you can continually analyze how accurate your lead scoring model is and how it can be refined for better results.
Make lead scoring a practice in continuous improvement, looking for new insights to inform your strategy and make your overall lead management process more effective.
RevBoss’s outbound email software and lead generation services are custom-built for startups, consultancies, marketing agencies, and other B2B organizations. Schedule a quick call with us and find out how we can help you win more clients.