Big Data Insights Improve Lead ScoringBig Data is a hot topic in B2B marketing circles. Unfortunately, most of the discussion around it and its potential centers on the problem of extracting real, valuable intelligence from all the clutter.

Virtually everyone agrees that, locked away amid the terabytes of new data generated every day, lies tremendous insight into what customers are interested in, working on -- and ultimately -- how they behave. 

Marketing teams are under increasing pressure to figure out some way to surface the richest data and unlock the secrets of identifying and targeting the most valuable prospects. But often, sales and marketing can’t seem to agree on exactly who those most valuable prospects are. So rather than improving effectiveness and results through teamwork, this lack of shared direction ends up funneling poor quality leads to sales, creating tension, disagreement and finger-pointing instead.

Unlocking Big Data's Potential

Lead scoring has emerged as a way to find a common ground, and it is one area that stands to gain the most from the availability of Big Data and advancements in analytic technologies. This process of ranking leads based on their sales-readiness essentially places prospects into buckets based on certain differentiating factors: demographic data, firmographic data (industry, revenue, etc.), and behavioral data (website visits, whitepaper downloads, etc.).

While this system certainly has enough merits to make it the gold standard in the lead gen and qualification industry, it’s not without its own set of challenges, namely:

  1. People lie. Many people routinely enter inaccurate or inadequate contact data when completing web forms, essentially filling your databases with useless information.
  2. People change. Specifically, they change roles, job titles, employers or even careers. Keeping up with the dynamics is increasingly difficult, especially amid a shaky economy where employment statuses change rapidly.
  3. People are mysterious. At least when it comes to finding out what really makes them tick for sales purposes. Databases only reveal a sliver of insight, but the technologies, products and topics in which prospects are interested and other nuances shared in social networks, blog post comments, online forums and other community sites can be incredibly valuable for qualifying and scoring leads. However, this data flies completely under the radar of most traditional web analytic tools and databases.

Big Data enables marketers to dive deeper into the digital trail their target audience leaves behind by way of their social network profiles, blogs, connections, follows and followers, statuses, and more. These pieces of data serve as strong indicators a person’s interests and priorities at any given moment.

Effectively mining this massive, unstructured treasure trove seems virtually impossible. Who has the time?

But mine it you must. Taming the Big Data beast enables marketers to reveal intelligent, valuable audience insights in real time and surface actionable data from beneath the mountains of random information in the social web.

Taming the Big Data Beast

The first step is to fuse the valuable lead scoring data -- demographic, firmographic and behavioral data -- together into a single pane of glass to draw correlations and comparisons. The resulting “social score” can then be used to more accurately define your ideal buyer based on specific behaviors that are known characteristics of your customers.

For example, the ideal buyer might be someone who blogs about SaaS business applications, Tweets about attending a Gartner webinar on the topic, and shares articles covering new SaaS app developments via LinkedIn. Combining this information with a person’s demographic and firmographic data reveals a much richer depiction of their true relevance as a potential prospect and their likelihood of making a purchase.

This data-based approach transforms lead scoring into a scientific process, rather than a subjective judgment call. And, better yet, analyzing social data to score leads also enables marketers to leverage one of the greatest advantages of the system: prospects do all the hard work to keep their information up to date for you. While static databases can go out of date almost as soon as they’re produced, social data is updated and cultivated in real time by the source. Think about it: one of the first things many people do when changing jobs or job roles is to update their social network profile. Bringing this dynamic data into the fold can dramatically improve the accuracy, efficiency and efficacy of your lead scoring and related outreach efforts.

Beyond enabling marketers to better target their efforts based on prospects’ areas of interest, roles, social graphs and more, social lead scoring also creates social sales opportunities. Knowing more about a prospect’s interests, knowledge and activities gives sales teams the ability to make new social networking connections based on shared interests and activities.

With some 80% of the new data generated daily existing in unstructured form, marketers must find some way to make sense of it all to maximize lead scoring efforts. Marketing and sales teams that are able to harness this dynamic data will have a clear competitive advantage, not only when it comes to better understanding and targeting their ideal buyer, but also with the newfound ability to make proactive information-based decisions and predictions.

Title image courtesy of Imfoto (Shutterstock)

Editor's Note: To read more about unlocking the potential of big data for marketers, see Are Your Digital Analytics Action-packed or Action-less?