How to Create a Lead Scoring System That Works

[Warning: Your email platform may not have a lead scoring functionality so before you spend any time on this, first check on whether you can implement it or not.]

Nearly every organization I speak with wants to setup lead scoring. However, many don't know where to start or their scoring setup is just not working.

So let's get into it.

Step 1: Build Your Demographic Profile

There are a couple ways to start here. The first being to look at your defined ICP (Ideal Customer Profile) and add those attributes. This may include,

• Company size (revenue or employees)

• Geographic area

• Industry

• Installed software

Now let's dive a level deeper and ask sales to validate. Who do they want to talk to? Here you may find answers like,

• Job role

• Job function

• Department

• Job title

Now put everything you learned into a table that will look like this,

Category	Details	Impact	Score Change
Demographic	Industry
Demographic	Company Size
Demographic	Job Function

​​Once you have this, we now need to assign the Impact. I like to use a rating of 1-3. The Impact is your ranking of importance. For example, if it is more important that the industry is an exact match vs. the company size, you would rank that as such.

Here is what your table now looks like where the most important characteristic is an Industry match,

Category	Details	Impact	Score Change
Demographic	Industry	1
Demographic	Company Size	2
Demographic	Job Function	3

Note that your list will be much bigger than the three I am using in my example and there can be multiple one's and multiple two's etc.

We have one more column to complete and that is the Score Change but we need to look at that later when we start building out our scenarios.

Step 2: Build Your Behavioral Profile

Now that we know what our demographic profile looks like, let's identify behaviors a person can take. This could be a form fill, attendance at a webinar, a request for demo or a high-value webpage visit like your pricing page.

Let's get this into a table like we did above.

Category	Detail	Impact	Score Change
Behavioral	Request a Demo Form
Behavioral	Whitepaper Download
Behavioral	Tradeshow Booth Scan

Now we want to assign an Impact score to each - same as above.

Category	Detail	Impact Score	Score Change
Behavioral	Request a Demo Form	1
Behavioral	Whitepaper Download	3
Behavioral	Tradeshow Booth Scan	1

Step 3: Assign Score Changes

Now let's look at how we want to assign a score to each of the categories we have identified. I like to use a model of 0-100 with 100 being the best lead to give to sales.

Before we do that, we need to consider the weight of demographic vs. behavioral. Do we want 30% of the score to be demographic based and 70% to be behavioral based?

To make this decision, weigh in on how much a demographic fit vs. an action is more important. For instance, is it more important that a CEO at a company in the Transportation Industry with 10,000 employees did something but it doesn't really matter what they did? Or is it more important that someone at a company in the Transportation Industry visited your tradeshow booth?

Take a moment to consider both and also ask your sales team for their input.

Now that we have that, we can start to assign a score to each attribute. I am going to use the 30/70 rule for weighting in this example. That means our Demographic score can be no more than 30 and our Behavioral score can be no more than 100.

We now have a table that looks like this,

Category	Detail	Impact	Score Change
Demographic	Industry	1	15
Behavioral	Request a Demo Form	1	30
Demographic	Job Function	3	5
Behavioral	Visited Tradeshow Booth	1	30
Behavioral	Whitepaper Download	3	10
Demographic	Company Size	2	10

So now I need to look at what is the ideal lead I can deliver to sales? This will be my bar for setting a MQL status which will trigger the sales team to take over (more on that in another post).

This is a bit tricky because there is a piece of information you need to gather here and that is what volume of leads are you acquiring and what can sales actually handle?

If you have a sales team of 2 people and are acquiring 100 leads a day. We need to set the bar for reaching MQL pretty high to control the lead flow and allow for proper follow-up.

Using this scenario, I will start to build a few mocks to see where I get.

Mock 1:

	Score Change
Request a Demo	30
Industry Fit	15
TOTAL	45

Mock 2:

	Score Change
Industry Fit	15
Job Function Fit	5
Visited Tradeshow Booth	30
TOTAL	50

Mock 3:

	ScoreChange
Industry Fit	15
Job Function Fit	5
Company Size Fit	10
Whitepaper Download	10
TOTAL	40

Now we have 3 mocks that range from a total lead score of 40-50. Taken aside the auto-MQL criteria (we will discuss in a future post how this works), I will set my bar at 50. This number will trigger the sales outreach to start and will also determine how I am calculating my funnel conversions.

This 50 is not set in stone. In the event you are having a slow lead period, in the summer months for example, you can adjust this down. Same goes the other way. You just returned from a tradeshow and scanned 1000 badges. You need to throttle this and jack your score up.

Step 3: The Negative Score

You absolutely need to have a negative scoring list as well. If someone breaks the bar and is not a fit, we need a safety net. Your negative scores could be,

• A generic email domain

• A geographic location

• People who visited a certain page on your site such as the Careers page

• Job titles that contain unemployed, student, etc.

• No activity for a certain period of time

Using the 0-100 scale and 30 being our Demographic fit. We want to knock all the Behavioral points out so we assign -70 to each of these. The reason we leave Demographic alone is that these values are what they are. Just because someone entered a gmail domain does not mean their Industry is no longer a fit.

There you have it. I hope this helps and you and your sales team see the benefit of putting in the work to set this up.