The Rise and Stall of Social Media Listening

“Listen First!” is sound advice, a social-media (and enterprise feedback) analogue of “look before you leap.” It’s advice, however, that doesn’t address what comes next. Say you’ve put a listening program in place. How do you advance your use of social/customer insights distilled from Voice of the Customer and other sources? Unfortunately, “companies really don’t know what to do,” according to Stephen Rappaport, who published a book with the “Listen First!” title in 2011, when, Rappaport says, listening was at its peak. Since then?

We have experienced the rise and stall of social-media listening.

From Monitoring to Listening

Listening builds on social-media monitoring and on traditional methods such as surveys. By contrast with surveys, which we carefully design and target, social media conversations and participation are unbounded. So monitoring starts with mentions. To be useful, you must disambiguate and discern the interesting (to you) elements in social chatter. (You get a taste for the disambiguation challenge in the title of a talk, “Smoking… Cigarettes, Weed, Hot Girls & BBQ,” that Stuart Shulman from Vision Critical is slated to deliver at the May 8 Sentiment Analysis Symposium. Whether beef brisket is best smoked with hickory or oak isn’t germane if you’re studying lung cancer.)

Monitoring has delivered clear benefits in areas such as customer service (a.k.a. engagement), reputation management, and crisis early warning. Add in analysis that aggregates disparate voices, discovers patterns, and maps trends, and you have the building blocks of a listening solution, typically delivered via a dashboard interface. (Even better: apply text analytics to uncover root causes of identified issues.)

Listening is a research technique, but programs to date — based on the seemingly obvious notion that marketing, product management, and customer-support programs should respond to actual customer and market voices — have delivered limited benefit. We monitor and survey, then we analyze and report. Typical activity, influence, and engagement measures have proven inadequate predictors of business-relevant outcomes; so much of the “social intelligence” available is a poor guide to effective action. Those ubiquitous dashboards don’t help. They describe but don’t guide. We are left with a decision gap.

Listening Next Steps

Listening is a given; support for sensible action the goal. I gleaned five intertwined, research-oriented steps, intended to help you get advance your listening efforts, from a series of conversations over the last month:

  1. Get the right data for a complete picture.
  2. Learn the challenges and not just the software.
  3. Understand customer dimensions.
  4. Rethink your analyses.
  5. Create a framework for analysis and action.

I will elaborate.

A bit of (misguided) management wisdom says that “you can’t manage what you don’t measure,” which has an unfortunate corollary. “The assumption is that what’s measured is meaningful,” says Stephen Rappaport, who is knowledge solutions director at the Advertising Research Foundation (ARF). “That’s not always the case. So many measures are just useless. They relate more to the business model [baked into software] than to reality.” Rappaport elaborates, “People are trained in using software. They’re not really trained in listening.”

Attensity CEO Kirsten Bay echoed this concern when she told me that part of her company’s role is to leverage its broad experience to “teach customers how to make decisions.” Bay says that one of her company’s goals is to “create the intersection” of data and action, which Attensity accomplishes via an analytics platform with rich workflow management capabilities.

So you have to select the right measures and design analyses that link data to desired outcomes.

“Measurement must be very specific, by client,” according to Nan Dawkins, founder and CEO of SocialSnap, a social-media analytics start-up. Deep domain knowledge helps.

David Rabjohns, CEO of MotiveQuest, which specializes in strategic social market research, says his company struggled to understand which metrics matter. MotiveQuest identified that “advocacy correlates with sales and share.” That is, it’s not enough to identify someone as an influencer. The message matters. I recently visited MotiveQuest, and Rabjohns and his colleague Kirsten Recknagel ran a number of case studies by me. One telecomm example was quite interesting, where the key was to understand “how 12 [distinct] categories of people talk about great customer service.”

So add people-understanding to the mix. Rabjohns and Recknagel explained that MotiveQuest’s approach seeks to distinguish rational, emotional, and social responses, that “each matters in a different way for different [product and consumer] categories.”

I heard a similar message from Becky Wang, head of analytical strategy at agency Droga5. Wang says, regarding ability to predict, “I can do all the social listening I want, but unless I have a psychographic profile or demographic information that goes beyond gender and age, I’m really limited.” But even with the right data, Wang asks, “How do I actually tie social and digital metrics to a purchase? How do I know that I’ve moved the needle?”

Again citing Stephen Rappaport: “Emotion is important.” Rappaport described to me a study conducted by social media agency Converseon for the ARF, on the role of digital and mobile and the emotional journey that people go through when they’re shopping. According to Rappaport, “rises and falls in emotion are opportunities for brands to intervene.” In particular, at the final point pre-purchase, “in certain [brand] categories emotions are very polar. In other cases, there’s more of a range.” Individual brands should leverage their “emotional profiles,” Rappaport concludes.

(Disclosure: Converseon is a Sentiment Analysis Symposium sponsor, and I recruited Stephen Rappaport to moderate a symposium panel that will include MotiveQuest CEO David Rabjohns.)

The Listening Journey

Sentiment analysis helps you quantify the emotional journey, via analytical approaches that include automated natural language processing (NLP), crowd-sourcing, and expert evaluation. The aim is to discern and aggregate attitudes, mood, and emotion in the array of available information sources, not in isolation but instead linked to other, appropriate measures, to psychographic profiles, to behaviors and social contexts and, ultimately to outcomes.

This ensemble points to a new approach to listening. Treat listening as a process, carried out within a business-domain-appropriate framework of action-aligned measures, data linkages, and analyses, designed to guide you from data to outcome. Customer-brand interactions involve a journey, and your listening program must as well.

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