But still, you have trouble knowing why some leads are good, and others only seem to be a waste of time. How can you know if a lead is worth pursuing ahead of time?
Enter lead scoring.
In this article, we’ll define the method, give examples of lead scoring strategies, and hopefully help you learn a valuable technique for improving sales.
What is Lead Scoring?
Lead scoring is a process that helps you focus on the most important leads first. The score in “scoring” is a number calculated based on several parameters. The higher the number, the higher chance a lead has of turning into a conversion.
What About Predictive Lead Scoring?
The process is the same as traditional lead scoring, but it relies on automatically aggregated data to calculate the score. This is an advanced scoring method that works best with huge amounts of data from your CRM for past interactions, website usage, and personal information. Because it’s such a complex process, it’s not usually suited for small businesses with small amounts of leads and data.
Do you Need a Lead Scoring Strategy?
That’s a good question because not all businesses will need lead scoring. In fact, scoring leads tends to work best for sales teams who have too many leads, and need to refine their filtering.
However, lead scoring can also be useful for nurturing campaigns. If you find that you trigger key messages too often and without much success, it’s worth giving scoring a try.
A Concrete Example of Lead Scoring
Let’s now dive into real-life models. This one, like most models, is based on a scale from 0 to 100, where a lead who scores 100 is the best one to pursue for your company.
We’ll keep it simple for the first example. You are a B2B business trying to reach out to accountants at small startups.
A user visits your website.
As you know nothing about them, the initial lead score is 0.
The user clicks a link to download your free ebook.
This is a valuable measure of interaction, so we’ll give that action +10 points.
You extract info about them from the form they filled.
There is interesting information in there, such as their job title (Accounting Manager+20 points), and the company where they work (a small startup +20 points)
The accounting manager is now on your email list, and you send them weekly newsletters.
They open the email and click a link (+5 points). They visit the blog (+5 points) and spend time reading it. Finally, they visit your site’s Pricing page (+10)
At this stage, your lead has a score of 70 out of 100. This is a great time for your sales team to get in touch and see if they can inquire about their needs or push their buying decision.
If they manage to convert a sale, great! If not, the user remains in your CRM or lead management software, and you can update their score as needed, maybe deducting points for the failed sale.
Other Parameters to Use in Scoring
Of course, lead scoring models can be as complex or simple as you need them to be. But there are still a few recurring parameters everyone should use. They are the same ones you will find in basic segmentation for marketing purposes.
Age: Age group is a quick and easy way to see if someone will be interested in your business or not.
Gender: More useful for B2C companies than B2Cs.
Location: If you only cater to certain markets, or offer your products/services in set languages.
Income: Another metric for B2C companies, where you can gauge if the person is likely to be able to afford your offer or not.
Then, there are B2B details pertaining to purchasing authority. You can add or deduce points depending on:
Job title: will the user have the final say on the purchase? Or will they need to speak to someone else at the company?
Company size: Is it too small? Or too big to need your offer?
Industry: is it relevant to your product or service?
Assigning Points and Weight
This is where lead scoring models can become extremely complex and require a lot of iterations and testing to yield successful results.
In essence, you need to run scenarios with branching solutions, where each outcome can be scored positively or negatively.
So going back to the example above, let’s say your lead score is 50 points. You now want to assign a score based on their job position.
Their job title gives them direct purchasing power. Great! You can assign an extra 20 points.
They need to refer to someone else: maybe you should deduce 20 points instead, and add 20 points to that other lead.
A good rule of thumb is to start each model with the same amount of points for each step, and they balance them according to importance. You might find you’ll need to increase or decrease values when certain parameters skew results too heavily.
Buying Cycle Benchmarks
Another useful exercise is to use the lead scoring points as benchmarks to understand at what stage the buyer is in your sales funnel. For instance, it could look as follows:
1 – 25 points = The awareness stage
25 – 45 = Interest stage
46 – 70 = Consideration stage
71 – 100 = Decision stage
Deploying and Testing Your Lead Scoring Models
Once you’re happy with your model, it can be useful to test it with historical data. Go over the info you have for customers who purchased your product or service, and see if the scores are close to the maximum.
For real-life deployment, it’s also possible to leverage lead scoring directly from your CRM and lead management software.
At Act! 365, our solution includes an integrated lead scoring system so you can automatically assign points based on factors like email open rates and other engagement metrics. This is a great way to get started with real-life examples and see how well the models help focus on the right leads and boost sales in the long run.