A solid inbound marketing strategy should generate a steady stream of web traffic and leads. However, not all of those leads are going to turn into customers – the reality is, most likely only a small percentage of them will. How do you qualify and segment these leads?
Lead scoring involves assigning a value to each lead based on a slew of criteria, which may include job title, demographics, how they’ve engaged with your website, how often they’ve interacted with your marketing emails and more. By assigning points to these attributes, marketers can help their sales teams prioritize leads.
The lead scoring tool in HubSpot lets you assign points to these attributes, but how do you decide which factors to choose and how to weigh them? This post outlines the simplest way is to calculate a basic lead score.
Your lead-to-customer conversion rate is your number of customers in HubSpot divided by the number of leads you generate. To provide a benchmark, a one percent conversion rate is considered fairly low, but not unheard of. A realistic goal to strive toward would be between two and five percent, which is entirely possible with a solid inbound strategy.
Start by looking at the contacts identified as customers and what they have in common. Next, identify similarities among your contacts that did not become customers. Once you’ve looked at your existing contact data from these two groups, you should have a much clearer picture of what lead scoring attributes should be weighted heavily, moderately, negatively or not at all.
Positive attributes may include:
Identifying the best attributes requires some thought and, ideally, conversations with your sales team. You might want to:
Say you have a form with 500 submissions. After the second step, you’ve identified this form fill as a worthy candidate for your lead scoring rubric. Of these 500 leads, 50 people became customers – a close rate of 10 percent. If your overall lead-to-customer conversion rate is 5 percent, then that means someone who converted on this form is twice as likely to become a customer.
Compare the close rate of each attribute to the overall close rate found in the first step and assign point values accordingly.
For the best results, we recommend using a 0-100 point scale and weighing the points in relation to how ready that lead would be to talk to a sales rep. A contact with a score of 0 is least likely to become a customer, while a contact with a score of 100 has the greatest chance of becoming one. So in our example in step three, it makes sense to assign 50 points to contacts that filled out the form.
If this still sounds daunting – or you don’t have enough historical data in your portal – you needn’t stress. HubSpot does offer predictive lead scoring, which uses machine learning to automate the scoring process. But even with predictive lead scoring, the less historical data you have, the less intelligent your lead scoring rubric will be. As with most things inbound, building a reliable lead scoring method takes time. Focus on attracting leads first and perfecting lead scoring second.
If you want to chat about tailoring your lead scoring rubric, get in touch with us!