The Value of Digital Body Language Segmentation

Digital Body Language_v2Steven Woods, the former CTO at Eloqua, wrote the book Digital Body Language in 2011. The concept makes good sense, however I’ve been seeking to estimate the value of tracking and responding to perceived digital body language. If you think that digital body language is placing a smiley face or frown at the end of your tweet, then read on and let me provide some background, however if you’re already quite familiar with digital tags and query strings, then you can skip down to the end of this post to read my findings.

Campaign managers want to know

Who should you send your email offers to for white papers, promotions, webinars and other offers? I get this question asked of me multiple times a week and it’s never a simple answer. Who are the groups of “people” that are interested in my marketing mix offer? Of course, your email open, click through and form submit rates are going to be far above any average if you hit the right target audience with a message that aligns and resonates well with your targeted audience. However, your subscriber opt-out rates will potentially go through the roof if you miss your target.

Traditional segmentation doesn’t answer the question

The traditional segmentation of firmographic criteria that includes industries, size of company, geography, and other organizational characteristics can help with your aim towards the right target, but doesn’t answer the question of who is actually interested in your marketing mix offer. You can further segment your targeted audience by competitive and complementary installed base products, but you still can’t answer the question of who is actually interested in your message and the value proposition that you have to offer. Add segmentation of your customers previous purchase history and you still don’t know with a high degree of predictability who wants to hear from you although your aim may be getting a bit better. Add contact data segmentation to allow you to segment by job functions and keywords in titles and that’s an awful lot of good segmentation but no still no cigar.

A segment of a social network: Who are the influencers and decision makers?


Source: Screenshot take by Darwin Peacock

Digital Body Language can answer the question

Digital body language (DBL) can be a clear expression of interest and intent at the organizational and individual level. It’s the individual and groups of individuals within an organization who are on your website and other third party websites researching and making the majority of their purchase decisions before they engage with you that can tell a marketer which individual or a group of individuals are interested in hearing from you. The types of content being viewed and downloaded as well as the keyword searches performed can tell a lot about:

  • What offers are of interest
  • What product or service characteristics are important in the research and purchase consideration
  • Where the customer is within the purchase buying cycle

If used well, this digital body language can even be used to predict your prospects persona. Given the level of information digital body language can tell a marketer, it is the most impactful segmentation that a marketer can leverage today to maximize the effectiveness of one’s marketing mix.

With respect to the customer buying cycle consideration, you can break this out into very granular categories. I prefer to keep it simple and to define three categories that include awareness, interest and purchase decision. Awareness assets include thought leadership content while interest assets include solution briefs and brochures and purchase considerations content assets may include case studies and data sheets.


In a recent Oracle webinar, “Digital Body Language: What can we be doing with it?” Oracle surveyed their audience to find the following results which indicate a majority of the audience was using DBL for Lead Scoring and Advanced Lead Nurture, yet a minority have embraced this insightful data for sales enablement and business intelligence. Most had deployed digital body language monitoring on web and email, yet there is still significant room for growth in monitoring DBL on social, webinar, display banner ads and video content.

Survey Results

In this webinar, Dan Allis, a Marketing Operations Manager at Thomson Reuters shared that in efforts to better align sales and marketing, digital body language played a significant role in lead management improvements. This contributed towards an increase in 23% of leads sent to sales, reduced lead conversion times by 70% and increased marketing sourced pipeline contribution by 175%. It appeared clear to Dan that the measurement and actions based upon digital body language contributed significantly to the improvement in demand generation.

Are we getting too complex?

With results like those referenced by Mr. Allis at Thomson Reuters, it’s no surprise that the use of digital tags is skyrocketing for both B2C and B2B marketing. According to DG MediaMind, “In Q2 2013, advertisers implemented an average of 21 conversion tags and recorded approximately 550,000 conversion events, increases of 37% and 277% over Q2 2010”. This increase accelerates the complexity of marketing demand generation campaigns as acknowledged by DG MediaMind. More important than the accelerated use of digital tags is the proper implementation and execution to identify DBL and respond accordingly.

Index of Conversion Tags

Source: DG MediaMind Research

Ad Age asked the question: Is Online Advertising Getting Too Complex? There is a fine line as to where the digital tags improve conversions to grow pipeline and where it becomes overly complex to diminish returns. Understanding where this line exists will allow marketers to maximize the return on investment in using digital body language for segmentation and targeting for demand generation. Finding this balance between use of digital tags and complexity is a new and unknown challenge for most marketing professionals.

What do you think about digital body language? Using it today? Experiencing a similar improvement in demand generation with digital body language segmentation and targeting? Have you found the balancing act between usage and complexity? I’d enjoy reading your thoughts on the use of digital body language for demand generation.

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