All leads are gold to the sales team, but some need a little polish before you can tell how much they shine.
There might be some leads, for example, that lead to a big sale with a customer who goes on to give you ongoing business. Then there are the . . . other leads. You know: the leads that turn out to be people who don’t match your target customer profile at all. Or the leads that might qualify as a sales target, but which lack enough data to be certain. Then there are the leads that will likely be customers, but not for a long while, and not without a lot of extra effort on the part of the sales and marketing team.
This is why companies turn to lead scoring: to help separate the good and the possibly great from the lacklustre.
Companies don’t always set up lead scoring right away because they haven’t completely determined the ideal customer for their product or service. When you’re casting a wide net, catching almost any lead will do. Or at least it seems that way.
It’s actually much smarter to introduce lead scoring as soon as possible so that you make the best possible use of your reps’ time and energy. The more leads that turn into closed deals, the higher their win rate. And of course, the higher their win rate, the more they’ll be motivated to repeat the process, boosting your revenues.
If you’ve come into an organization that doesn’t have lead scoring in place, it might be up to you as the sales leader to help establish it, turning it into a process the whole company can use as part of its growth strategy.
Not sure where or how to start? Try this:
The way you determine lead scores can vary, which can be the most difficult initial decision. However there are usually some hard numbers and other information you can use to determine a lead that has the propensity to turn into an actual customer.
Some of the possibilities here include demographic information, company data such as industry or size, or how a lead behaves online.
Engagement on your website — such as looking around at multiple product pages — could be a good indicator. So could a lead that’s asking questions or liking your social media content. Even email open rates and click-throughs could offer a hopeful sign.
Look back at your historical sales records and do a bit of reverse engineering. Trace the path your best leads took to becoming customers, and develop your scoring methodology accordingly.
If the people selling on the front lines don’t agree with your lead scores, you might as well not score them.
Reps don’t want bad leads, but they also don’t want to be left out of the process. Their voices are important and should be heard. Discuss the scoring methodology and how it will change the process of setting priorities for outreach and follow up. If you’re getting a lot of pushback, use the data you’re using for the basis of scoring to persuade them.
This is something of a sales pitch in itself, but when you get buy-in at this stage, everything else becomes a lot easier.
Don’t limit yourself to reps, though. You’ll also want to have the same conversion and collaboration with the marketing team. Even if a lot of what they do is more focused on brand-building than demand generation, they should be thinking about reaching the kinds of people who will most likely turn into leads at some point.
Lead scoring shouldn’t be an exercise in finding a needle in a haystack. You should be organizing sales and marketing activities so that the bulk of the leads you discover will score well.
This means looking at how data is entered into the CRM from the moment a campaign launches to when a sales rep follows up with someone. If the data being captured isn’t relevant, accurate or containing the right details to determine the score, you need to fix that first.
A similar process should happen periodically at the end of a quarter or even monthly, where you run an attribution report to look back at deals and see whether lead scoring is helping reps reach their quotas.
The more sophisticated lead scoring becomes, the less manual the process should be. Depending on the size of your company and how much data you’re gathering, it will become difficult to impossible to sort through every lead and give it the attention it deserves in order to have the most appropriate score.
This is an example of where technology can play an instrumental role in your success. Although some organizations have used predictive analytics to assist with lead scoring, that limits you to understanding what’s worked in the past.
Artificial intelligence (AI), on the other hand, can develop models that build upon the past but actually forecast the most likely scenarios that will play out in the future.
These predictive capabilities mean your reps not only get leads scored more quickly and at scale, but in such a way that reps become more confident in the score they’ve been given.
Lead scoring can become as granular and nuanced as you want. Some sales teams begin to differentiate between leads that show interest vs. whether they’re a true fit, for instance. Others look at leads that present cross-sell or upsell opportunities.
In sports, we keep track of the score because we want to get a sense of which team is heading towards victory. In sales, lead scoring does something similar: the better you get at scoring, the more often your sales team will win.