The Next Big Thing in Lead Scoring: Big Data and Social Scoring


Posted: February 22, 2013 | Lead Scoring, Modern B2B Marketing

We are excited to welcome Ran Gishri as today’s guest blogger. Ran is the VP of marketing for Leadspace, a pioneer in social lead targeting. Ran has over 20 years of experience working for technology companies of all sizes and domains.

An increasing number of CMOs view lead scoring, the process of ranking leads based on their sales-readiness, as a key component in their B2B marketing strategy. And for a good reason. Lead scoring done right can lift conversion rates and remove some of the all-too-common friction between Marketing and Sales.

Most lead scoring techniques are based on a mix of demographic, firmographic and behavioral data. For example, if a site visitor reads your pricing page, signs up for a trial, and states she is an executive at a sizable company, the score would probably be high and she’d be fast-tracked to sales.

Here’s the problem, and it’s twofold:

  • Scoring “blind spot”: we’re really only looking at what people do while they are in our “store” (i.e. when they engage with our site or emails), and know very little about what they’re up to when they’re out there on the street (i.e. anywhere that is not our site)
  • Lead data quality: we trust the information shared with us through web forms, however we know most people can’t or won’t provide accurate information; and, people are constantly on the move, so data tends to be outdated

Enter Big Data.

If you’re like me, you must be getting tired of all the hype surrounding Big Data. However, lead scoring is one of the areas that stand to get most value from the new wave of Big Data analytics.

Think about it – chances are that most of your leads leave “digital footprints” online – in social networks, Twitter, blogs, press releases and corporate websites. There’s an abundance of information about your leads out there–about their true roles, what’s on top of their mind, even who they are connected to. And, the information is always fresh and typically accurate.

The problem is this data is unstructured. It does not reside in database tables, which means you can’t just import and push it into your marketing automation database. This is where Big Data analytic tools come into play, as they structure the unstructured. Armed with these nifty new technologies you will be able take lead scoring to the next level by fusing demographic, firmographic and behavioral scores with a social score.

A social score is based on all the information you can gather about your leads – individuals and businesses – by looking at the professional information that is publicly available online. A social score helps at a couple of levels:

  • Purification – verification of demographic and firmographic data you have in your marketing automation tool. For example, you can check if a person (still) holds a certain position, or if a company uses a certain technology.
  • Enhancement – adding a social data layer that helps score leads based on how closely they match your ideal buyer profile. For example, if a lead is a member in forums about cloud computing and follows cloud management experts, she might be a great target for your cloud management solution.

Figure out the social score, add it to the mix, and you have taken your scoring program to the next level, making it far more accurate and significantly more effective.

80% of the information generated daily is unstructured. Making sense of some of this data enables marketers to take a gigantic step forward. Not only in how they score leads, but also in understanding their customers, taking information-based decisions and making predictions.  Inch by inch, marketing is shifting from art to science with the help of Big Data.

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  • Anonymous

    These are all very good points, but what would you recommend in terms of process and resources to accomplish the Big Data validation/update step? I’m familiar with the integration with SFDC and Marketo. Any other good pathways?

  • Doug Kessler

    Excellent post. Now we need a follow up on how to do it

    Sounds like we’ll need some fancy algorithms to sift the signal from all that social noise.

    It’s easy to score behaviours when they happen in your own domain ( they’re relevant by definition). But only a tiny portion of a prospect’s social activity will be relevant to any one vendor.

    Provocative post. I’m sure this is the next step.

  • Ran Gishri

    Doug and jmctigue – many thanks for comments! As you noted, obtaining a clear signal and filtering out the noise is no easy task. It requires domain expertise that “old school” tool vendors don’t currently posses.

    A handful of startup companies that specialize in “structuring the unstructured” are rising to the challenge. The company I work for (Leadspace) is one of them. Our vision is a complete, seamless blending of data you have in Marketo and your CRM with the information we can extract from social networks, blogs and the open web.

    Happy to talk more about this topic – my Twitter is @rgishri.

  • Mike Bramowski

    This is great, although even having more information about a prospect doesn’t necessarily mean they will buy any faster. Chances are, they have already done the research prior to filling out the form. I would say use big data on the front end, to identify this target way before they engage with you. Try and zero in within the demographic by pulling social into your targeting strategy.

Dayna Rothman is the Sr. Content Marketing Manager at Marketo and Author of Lead Generation for Dummies. She runs the Marketo content initiatives and is the managing editor of the Marketo blog. Dayna has extensive experience in content marketing, social media, marketing automation, and inbound marketing. She has an MBA from Golden Gate University and lives in Oakland, CA.

Read Dayna's Blogs

The Next Big Thing in Lead Scoring: Big Data and Social Scoring

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