Make a Better Lead Scoring Model with Better Data

Make a Better Lead Scoring Model with Better Data

2.21.2017 | IT Sales | IT Marketing | Strategy | by RainKing

Gathering the correct data for effective lead scoring is a struggle for the vast majority of companies selling B2B products and services. In our blog last week, we discussed progressive profiling which helps Marketers gather that information to help identify and further nurture prospects. Moreover, incorporating progressive profiling into your marketing strategy also makes lead scoring easier.

By definition, lead scoring is a method which ranks and prioritizes prospects for sales engagement. Marketers often struggle with lead management because it involves trying to find and reach your ideal buyer persona in a sea of millions. Reaching that persona can be especially difficult if you don’t take the time to learn about your prospects. Lead scoring is a key component to an efficient marketing and sales strategy. It can help distinguish between tire-kickers, leads, and those ready to enter into the sales process.

Define your lead types

The first step you should take in creating your lead scoring model is defining what a ‘lead’ means within your organization. Typically, Marketing and Sales think of leads in terms of three dimensions:

  • Leads - A potential customer or client qualified on the basis of his or her financial capacity and/or willingness to buy. These contacts will need to be nurtured with marketing content to discover if they are a qualified lead that can be moved to a MQL or SQL. This is done by further nurturing them with educational marketing content.
  • Marketing Qualified Leads (MQLs) –  A lead that has received nurturing from marketing and has moved further down the sales funnel. Your organization has collected information from this lead via the forms they have filled out and is viewed as a lead that is a directional fit and has the potential to become a customer.
  • Sales Qualified Leads (SQLs) – A MQL that has been passed along to Sales who has further vetted and verified that they are a definite fit, ready to enter the sales cycle. From there, they will hopefully become a customer.

As you define your leads, MQLs, and SQLs as an organization, make sure you involve both the Marketing and Sales teams and there is a general consensus reached.

Sales and Marketing must define lead types and lead scores together

Lead scoring uses a value-based system to help surface high-quality prospects. Use your ideal buyer personas as your guide for discussing your lead scoring numbers. Activities that your persona would usually engage in or demographic/firmographic information that you want your personas to possess should have higher point values than “nice to have” information.

Before you start plotting the X- and Y-axis and assigning numbers to leads, sit down with Sales and Marketing to and discuss what characteristics comprise a qualified lead. Give stakeholders on both teams access to the data and come to a smart conclusion. No numbers without consensus!

As an example, we have parameters listed below that could make a lead a MQL or SQL. The numbers below are based on a total MQL score of 25 and a SQL score of 50. Remember, this point system is just an example, you will want to come up with your own based on your organization’s needs.

Scoring mechanisms prioritizing leads can include giving points for:

  • Decision makers/points of contact (10 points)
  • Ideal industries (10 points)
  • Downloading educational content (5 points)
  • Subscribing to your blog (3 points)
  • Opening and clicking through emails (2 points)
  • Downloading sales specific content (10 points)
  • Ideal company size (5 points)
  • Ideal company revenue band (5 points)
  • Requesting contact from your organization—e.g. a quote or demo (50 points—automatic SQL)

To further distinguish between those you should and should not take the time to nurture or call, you can implement more in-depth lead scoring by applying leads negative scores. These scores could include:

  • No engagement for a specific amount of time (-10 points)
  • If you don’t sell to certain industries (-15 points)
  • Lower-level employee—no decision making capability (-10 points)

For lead scoring to be successful, open dialog between Sales and Marketing is imperative. The point values are never static figures and making changes as time goes on is necessary.  Are the SQLs you’re sending to Sales qualified enough or do they need more nurturing? Or are they overqualified and probably could have been called sooner? Evaluating MQLs and SQLs which have successfully completed the sales cycle will help you adjust point values as well. Do they all have something in common? For example, are those who download multiple high-value content pieces more likely to become a customer down the line? If so, boost the point value for your ebooks and whitepapers. Also, know that how your company measures MQLs and SQLs can—and probably should—be different from other companies. Your qualified leads are just that, yours, and thus, unique.   

Lead scoring helps save time for both Sales and Marketing. It allows Marketing to be more strategic in messaging to different contacts. Leads will now receive relevant and educational content, which helps nurture them from lead, to MQL, to SQL. Now, when Sales is given a SQL, they know more about the prospect based on the information gathered from form fills and MQL vetting, which makes for warmer sales calls. And warmer calls typically mean more closed deals and finally, a more happily-aligned Sales and Marketing team.  


To learn more about how RainKing's sales intelligence can improve your lead scoring efforts, request a demo today.

Lead scoring save time for both sales & marketing