TOFU. MOFU. BOFU.
They’re funny-looking acronyms that are fun to say and music to the ears of sales and marketing teams who focus on moving leads through the funnel – top, middle, bottom – and clinching the sale.
Encouraging your leads to take this journey is hugely dependent on knowing where they are in their buying process.
Which means assigning a lead score … which means figuring out how to calculate that score.
Enter the matrix. (The lead-scoring matrix, that is.)
But before I go there, let me back up and briefly discuss lead scoring in general.
What is Lead Scoring?
In terms of definitions, here’s what SiriusDecisions says:
“Lead scoring is a methodology used to rank prospects against a scale that represents the perceived value each lead represents to the organization. The resulting score is used to determine which leads [sales and marketing teams] will engage, in order of priority.”
Written like a true research firm: simultaneously precise and muddy.
In somewhat simpler terms, lead scoring is a way to qualify leads based on (1) who they are and (2) how they engage with your brand.
It uses a points system wherein points are assigned to key criteria, characteristics, and actions such as demographics, website visits, email clickthroughs, webinar attendance, content downloads, form completions, etc. Points accrue over a set amount of time. The sum of these points is the lead score.
Lead scoring helps sales and marketing segment and categorize leads, which makes it much quicker and easier to assess where leads are in the buying cycle, what they’re interested in, and how best to continue a meaningful conversation that keeps the momentum going and closes a sale.
Why should you care?
If the last paragraph didn’t convince you, perhaps this will: Leads get cold fast.
According to a May 2013 DemandGen study, data decays at a rate of 25% to 30% per year. An IDC study from August 2012 concluded that over 50% of leads in the average B2B contact database are obsolete.
Time is of the essence when it comes to lead management. Striking (with precision) when the iron is hot is essential to moving potential buyers down the funnel.
As mentioned, lead scoring is the method.
And a lead-scoring matrix is the foundation. Here’s how to build one.
Building Your Lead Scoring Matrix
Most likely, many of you already have basic lead scoring in place. Creating a lead-scoring matrix takes lead management to a new level by formalizing and honing your processes for optimized customer engagement and, ultimately, increased revenues from new and repeat sales.
Going back to definitions, let’s address the term “matrix”, which has a lot of special meanings depending on whether you’re talking about math, biology, or the Internet (or an awesome movie).
In the case of sales and marketing, a lead-scoring matrix is essentially a table – a graphical way to define, create, visualize, and explain your lead-scoring process. (Jump to some examples below)
It can be assembled in numerous ways; one method or model will not fit all companies. However, there are some best practices to consider.
Here are 3 of them:
1. Determine your scoring criteria
Before you can score your leads, you need to figure out the criteria that will be used to calculate the score. There are three basic types of criteria: explicit, implicit, and negative.
Explicit criteria
Explicit data is information that’s provided intentionally by the person (e.g., via a registration form or survey) and taken at face value, rather than analyzed or interpreted for further meaning.
The following are examples of explicit data you should consider:
- Company
- Location
- Business type/industry
- Revenue
- Number of employees
- Lead source
- Title/job role
- Level of responsibility
- Purchase authority
- Past purchases
Implicit criteria
Implicit data is information that’s NOT provided intentionally and; thus, can only be derived from analysis of explicit data. For example, the explicit data about a person’s physical address may yield implicit data about which store location they’re likely to visit.
The following are examples of implicit data you should consider:
- Website visits – Number and type/category of pages visited, frequency/length of visits, referral sites
- Phone calls – If your automation platform is integrated with your CRM system, custom fields can be created to categories different types of phone calls and assign points to them
- Content interactions/media downloads – Views and/or downloads of articles, press releases, white papers, videos, podcasts, infographics, etc.
- Subscriptions – Requests for newsletters, RSS feeds, other digital notifications for ongoing content
- Webinar attendance – Number of webinars registered for, number of webinars attended, topics
- Form completions – For demos, contact, surveys, questionnaires
- Offline/custom events – Trade shows attended, other types of physical events
Negative criteria
Negative criteria serve as the checks-and-balances of your lead-scoring matrix, adjusting your lead score in response to factors that might make a lead less desirable.
The following are examples of negative criteria you should consider:
- Lack of response to marketing messages
- Unsubscribing from an email list
- Requesting to be added to your do-not-contact list
- No decision-making authority
- Defined periods of inactivity
- Visits to certain pages (e.g., your Careers page)
2. Determine your scoring thresholds
To get the best results from lead scoring, you need to determine where the thresholds are for your segments; i.e., the scores that serve as dividing lines to separate sales-ready leads from those that need more nurturing.
Here’s an easy way to get started:
- After determining your full list of scoring criteria, assign a score to each. The common scale is 0–10. (Note that negative criteria uses a negative scale: -10–0.)
- Add up the highest score someone can get if they do everything you want them to do. (For example, if you’re running a nurture campaign with defined communications and desired actions, add up all of those scores to determine the maximum points possible.)
- Since it’s unlikely anyone will get the maximum score, choose a few scenarios of desirable interactions and add up those scores to get a baseline.
Using that approach, let’s say you peg 50 points as the threshold that, when reached, indicates the lead is red-hot and sales-ready. Great! Go to market with that and begin experimenting. Over time you’ll probably adjust the threshold number as you learn more about your audience and what actually contributes to a lead being categorized as “cold”, “warm”, and “hot”.
3. Automate
For most companies, manually managing all of the moving pieces involved with lead scoring is, frankly, not feasible. “Manual” doesn’t scale – there are only so many viable hours in a day and so many resources in a department.
To get the biggest bang for the buck (literally and figuratively), it’s highly recommended that a marketing automation platform be used to manage lead scoring. Here are a few reasons why:
- Eliminates cold calling by allowing teams to automatically nurture leads (and score them and get alerts when thresholds are met) to a qualified status.
- Decreases resource time spent on repetitive tasks, allowing sales to spend more time focusing on selling.
- Helps sales reps know what to say, thanks to customer-intelligence dashboards that uncover what each lead cares about, what content they’ve viewed, what actions they’ve taken, etc.
- Shortens the sales cycle by effectively nurturing leads with content that resonates with their needs and interests.
- Integrates with your CRM tools, allowing sales to use what they’re familiar with while having even more information at their fingertips.
- Aligns sales and marketing, which makes for better targeted and more effective campaigns that close more sales.
When it comes to sales, marketing, and the realities of business competition, efficiency and speed are as essential as targeted accuracy. (Because if leads don’t buy from you, they’ll probably buy from someone else.)
Creating a lead-scoring matrix is an excellent exercise in formalizing your thoughts and honing your strategies, so you can get maximum mileage from your sales and marketing efforts and keep the TOFU, MOFU, AND BOFU humming.
Examples of Lead-Scoring Matrices
Below are two examples that illustrate how lead-scoring matrices are used to define points systems. In marketing automation platforms, lead scoring values are automatically tracked and tallied, allowing you to “set-it-and-forget-it”, letting the automation platform do the work for you and then send alerts when your defined thresholds are reached.
“Neon music sign” by Nevit Dilmen, used under a Creative Commons 3.0 license.
Download Act-On’s white paper, Best Practices for Setting Up a Lead Scoring System for a more comprehensive understanding of this valuable methodology.
