The Rise And Stall Of Social Media Listening - InformationWeek

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Software // Information Management
10:19 AM
Seth Grimes
Seth Grimes
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The Rise And Stall Of Social Media Listening

These 5 research-oriented steps help you select the right social listening measures and design analyses that link data to desired outcomes.

Listen first.

It's sound advice -- the social media (and enterprise feedback) version of "Look before you leap."

However, it doesn't address what happens next. Say you've implemented a social media listening program. How do you advance your use of social/customer insights distilled from the voice of the customer and other sources?

Unfortunately, companies really don't know what to do, according to Stephen Rappaport, author of Listen First!: Turning Social Media Conversations Into Business Advantage (Wiley, 2011).

Rappaport wrote the book in 2011, when, he says, listening was at its peak. Since then? We have experienced the rise and stall of social media listening.

Listening builds on social media monitoring and on traditional methods such as surveys. Unlike 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 elements in social chatter. (You can 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.)

[ Want more on social business decision-making? Read Twitter Helps Build Social Data Ecosystem. ]

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 to be 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. From a series of conversations over the last month I gleaned five intertwined, research-oriented steps to help you advance your listening efforts:

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.

A bit of misguided management wisdom says "you can't manage what you don't measure," which has an unfortunate corollary. "The assumption is that what's measured is meaningful," says 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. People are trained in using software. They're not really trained in listening."

Attensity CEO Kirsten Bay echoes this concern, saying her company's role is to "teach customers how to make decisions." One of the goals, she says, is to "create the intersection" of data and action, which Attensity accomplishes via an analytics platform with rich workflow management capabilities.

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

"Measurement must be very specific, by client," said Nan Dawkins, founder and CEO of SocialSnap, a social media analytics startup. 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. "Advocacy correlates with sales and share," he said. That is, it's not enough to identify someone as an influencer. The message matters. Rabjohns recently ran a number of case studies by me. In one telecomm example, the key was to understand how 12 distinct categories of people talk about great customer service.

So add people-understanding to the mix. MotiveQuest's approach seeks to distinguish rational, emotional and social responses. "Each matters in a different way for different [product and consumer] categories," said Rabjohns.

Becky Wang, head of analytical strategy at agency Droga5, offers a similar message. "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," Wang said of the ability to predict. Even with the right data, she asked, "How do I actually tie social and digital metrics to a purchase? How do I know that I've moved the needle?"

"Emotion is important," Rappaport said. He cited 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. "Rises and falls in emotion are opportunities for brands to intervene," he said. In particular, at the final point before a 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 concluded.

(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 including automated natural-language processing, crowd-sourcing and expert evaluation. The aim is to discern and aggregate attitudes, mood and emotion in the array of available information sources. Do the analysis not in isolation but instead link it to other appropriate measures, including psychographic profiles, behaviors, social contexts and, ultimately, 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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