Lead scoring is a system designed to assign points to each prospect in the marketing automation database. Points are incremented (or decremented) based on the business rules and specific criteria for the company in which the scoring matrix was built for. These unique attributes are identified by the sales force as being frequently associated with leads that have converted into a sale or as the ideal target prospect. The higher the lead score, the more likely that prospect is ready to engage in the buying process and should be routed to the sales database (CRM) as a lead. Prospects that do not meet the score required to be a sales-ready lead are retained in the marketing database for further nurturing.

The most accurate lead scoring models calculate both explicit criteria and implicit behavior patterns. Explicit scores are based on information provided by or about the prospect, for example -job title, company size, buying horizon and geography. Implicit scores are derived from the prospect's online behavior by monitoring their engagement with the company (unbeknownst by the prospect) via website visits, email opens and email click-throughs and downloads of vital assets like white papers, case studies and/or videos.

Research shows that self-supplied explicit data can be overinflated or understated, but the prospect's behavior without the knowledge they are being monitored does not lie. Calculating both profile fit (explicit) and level of engagement (implicit) will result in the most accurate lead score.

Why is Lead Scoring a Best Practice?

  • It qualifies a prospect's conversion into a sales-ready lead on an automated basis, efficiently saving the salesperson time to build relationships with existing leads
  • It prevents the sales team from receiving poor or premature leads
  • Lead Scoring helps prioritize leads so a salesperson can follow up with the best ones first