How Big Data Facilitates Lead Scoring

Lead scoring is an integral part of the marketing lifecycle. Since lead scoring determines which prospects are sales-ready, getting this right is important to ensure the success of the entire marketing effort.

There are many ways and approaches to score leads, but regardless of the approach, there are certain blind spots. For instance, a marketer may assume that the prospect is sales-ready when they sign up for a free trial. However, the prospect may actually be comparing various options, and they might have signed up for other similar services. The marketer needs to engage with the prospect at a more proactive level before they become ready to purchase. Simply passing over the prospect to sales when the prospect signs up for the free trial may result in a competitor taking the prospect away.

Similarly, the marketer may strive to engage a prospect who has downloaded a product information brochure or requested a price quote, oblivious to the fact that the prospect has since then changed jobs and now no longer requires the product.

The solution is to track the prospect relentlessly.

All prospects leave behind “digital footprints” of their online activities. Twitter posts, Facebook shares, website visits, forum postings, network or connections – all give away a prospect’s online activity. The job of the marketer is to collect all disparate data from various sources, integrate everything in a common platform, and apply analytics. This offers a comprehensive picture of the prospect, offering the marketer a clear-cut idea of where the prospect stands.

Big data facilitates exactly this. It integrates and collates various streams of information, be it demographic data or lead intelligence to provide marketers with meaningful and actionable insights. Marketers may already have access to all the data independently, but without the ability to collate and the capability to apply analytics, they would fail to capture any significant insights.