Many organizations have a two-tiered sales process. One team is focused on qualifying inbound leads from marketing (MQLs), and the other team is focused on closing business (revenue). This structure exists to maximize pipeline creation and increase sales team productivity.

While some companies aggressively pursue every lead that is created, others are leveraging lead scoring to work smarter. If you can programmatically spot your good leads, chances are you’ll be able to increase win rates and conversion.

So what makes a good sales lead? 

A good lead has two key ingredients:

1. Fit Score (also referred to as an explicit score) 

The Fit Score is intended to capture how much an incoming prospect resembles a likely buyer. For example you might look at the lead’s company size, geographic location, industry, and job title, to determine if it is a fit. A quick look at the employer’s website might give you other clues regarding their business model and online presence.

2. Activity Score (also referred to as an implicit score)

The Activity Score is intended to capture how much a prospect is engaged with your company. This could include the lead’s website visits, form completes, email clicks, and maybe even application usage data.

While both ingredients provide valuable data points, the first question to ask about any lead is fit -- does it look like your existing customers? If the prospect is not a fit for your product, it doesn’t matter how engaged they are; they’re not likely to buy. Quite a few companies use robust activity-scoring today, but very few have a fit-first approach to lead assessment. That’s because doing it well requires large amounts of data and advanced data science.

A fit-first approach gets you a step ahead

If you can tell whether a prospect is a good fit right from that first form they fill out, you can route them down the right path more quickly.

• Certain leads are simply junk. One extreme is spam (i.e. people who put in fake info, like spongebob@squarepants.com), but sometimes a lead is junk because the prospect’s company just isn’t a fit for your product. For these leads, activity is irrelevant. No amount of white paper downloading is going to turn them into a lead you should pursue.

• Certain leads need to be fast tracked. If a lead has a terrific fit score (because they look like your existing customers), you should send him or her straight to sales. Don’t take a wait-and-see attitude if you know from the outset that you’ve got a great fit. If you can get in touch with that prospect a week before your competitor, you’re at a competitive advantage.

The impact of a “fit-first” approach is enormous. In many organizations, 50% of sales energy is spent on prospects who never convert. By implementing an automated predictive lead scoring approach to determining fit, you can lift your lead conversion rates upwards of twice your previous average and ensure your reps are always swinging at strikes.