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Behavioral Rank in Lead Scoring helps get not More but Quality Leads


At the start of the year, many analysts had predicted that 2016 would see lead scoring – the process of identifying and grading a prospective customer’s intent – come of age.

This group bet on the increasing reliance on behavior scores in the overall lead scoring business. Such a type of recording involves the use of two sets of data, each offering its own insights. The demographic count, a child of the more traditional method of lead scoring, measures how well a prospect fits your target audience. Behavior score, on the other hand, indicates sales-readiness based on a combination of activities undertaken by the prospect, beginning from his actions on your website, his/her reaction to your newsletters or emails, and other such measurable activities.

For years, companies depended largely on demographic-based scoring to pass on leads to their sales teams. But in the past two years, that seems to be changing, with an increasing reliance on behavioral patterns of a prospect. Companies, especially those in the B2B sphere, can no longer just look at lead scoring as a “strait-jacketed” activity, or worse still, depend on wild guesses made by someone in top management.

Here’s another reason why this year may eventually turn out to be a watershed year for lead scoring – the use of third-party data. All this while, Enterprises have only been using information gleaned from within the organization. But before going any further, here’s a red flag. Third-party data here must not be confused with the generally prevailing practice of “purchasing” unverified leads from online generators or affiliates. What we are talking of is the tracking of data generated by a prospect in his offsite activities. Such lesser biased inputs help marketers in their pursuit to understand who is really a buyer and who qualifies as a “junk lead”. A combination of all three above-mentioned factors is set to make lead scoring an even more accurate science in the new year.

Behavioral Scoring and Lead Scoring Intelligence

Lead intelligence is a pipeline that tries to give a 180-degree view of every prospect on his journey to buy, and marketers are the ones looking at this process through the eyeglass. The addition of the behavioral data component in lead scoring today is also part of the new thinking among marketers that the name of the game is no longer more leads but “better” or qualified leads. The effort is to hand over Marketing Qualified leads (MQLs) as “sales-ready” to the colleagues from Sales, thus saving the latter time and resources, and overall helping organizations increase their lead conversion rates. And in this, behavioral data is being seen as one that is coming to play a major role.

Keeping Behavioral Score

Here’s how lead scoring has evolved through the ages, today, coming to rest on the doorstep of a prospect’s behavior. In the past, marketers would assign a high score to a person who held a certain rank within an organization, simply because they thought he held the power of decision for purchase. A marketer based this on what’s generally defined as explicit data. That silo-type of scoring is history. Marketers then started grading prospects based on information gathered from implicit data, or the actions of a person. Clicking on a link from within an email, for example, qualifies as one.

But even such implicit-based data scoring is now being honed into a science in the drive to identify quality leads. For example, a short while ago, anyone who simply clicked on a web page says 10 times got a high score attributed against his/her name and was said to be “sales-ready”. Today, however, a prospect who has done something more concrete than mere clicking, like filling out a registration form for a webinar on your website, gets more marks than the guy who simply clicked a dozen times. Thus, a potential buyer’s intent is often revealed through their behavior. Behavior score, which essentially comes out of behavioral qualification, a set of triggers around the buying process, has a two-fold purpose – it helps measure a person’s sales readiness and provides a clue to which channels provide the best prospects.

Lead score sheet

Clearly, converting visitors into leads is a complex process, and will remain so as long as your visitors are real people with real emotions and not bots. This entire process is based on the foundation of lead scoring. Needless to state, the more accurate marketers score leads, the faster it is for the Sales team to close a deal.

A recent survey showed that 62% of sales teams did not trust the lead scoring metrics used by the marketing teams. According to an Aberdeen Group study, a sales team that did not have some kind of sales intelligence to fall back on spent an average of 200 hours per year on non-selling related activities – such as tracking down data, finding phone numbers, and planning to make sales pitches.

Express Analytics offers Catalog Modelling and Catalog Scoring techniques based on sophisticated statistical algorithms to help businesses not only identify likely customers but also to tell with a high degree of accuracy which leads are most likely to convert.

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