The eight advanced insight elements of social listening
The most interesting and useful insights to be gained via social listening — the best clues to consumer needs, attitudes, and intent — are linked to sentiment. Why? Because emotion drives consumer choice, which makes sentiment an important metric for consumer research, market insight, and customer engagement initiatives. Measure and understand feelings about brands, products, and services — yours and your competitors' — to derive essential customer experience, motivation, and market positioning data.
A slew of social-listening providers deliver basic-or-better sentiment analysis capabilities although tool usability, reliability, and accuracy vary widely. At the better-to-best end of the spectrum, sophisticated natural language processing (NLP) capabilities are now table stakes, whether bundled into the listening tool or delivered as an add-on. Without NLP however, and without access to the right data, no matter how slick the dashboard visualization, you won't discover the insights you need to drive business decisions.
If you're not a technologist, don't get hung up on technical detail, on machine learning versus taxonomy versus lexical rules. Best to focus on outcomes, on the computed quantities that will help you accomplish your business goals. These will often involve higher-order satisfaction, loyalty, advocacy, and intent measures, with ability to explore drivers and root cause. Choose a tool that provides data, workflow, and visualization that suit the task at hand, whether marketing, customer service, or consumer insights.
Let's deconstruct. I'll catalog eight advanced insight elements, but before that consider Rule #1:
Whatever your goals, as digital strategist Steve Rappaport says, Listen First!.
Let's class listening approaches into three categories:
- Strategic listening — for market research & consumer insights — producing aggregate views that study interests and reactions within demographic categories and market segments.
- Reactive listening — for customer engagement — aimed at resolving issues, one-on-one.
- Retroactive listening — supporting customer experience management — the study of customer perceptions at the many brand-interaction points that constitute the customer journey.
Different solution choices fit each category, but whatever solution you choose, look for ability to derive sentiment-linked people measures:
1) What do do people feel when they interact with your brand?
2) How do they talk about their experiences and feelings?
3) What factors help you understand satisfaction, motivation, and intent?
A weak or misapplied tool will simply deliver more data, so I'll suggest five more insight elements...
Look for predictive capabilities, the possibility of exploiting extracted sentiment to derive timely measures:
4) Emerging issues; early warning.
5) Leading indicators, anomalies, and trends.
And use sentiment signals as confirmatory measures, cross-checks for analytical insights discovered via behavioral analysis and traditional methods such as surveys, tracking studies, and focus groups, that is for:
6) Correlation, confirmation & determination of root causes.
Finally, use sentiment insights to better understand the spectrum of stakeholders and how they think and react. Listen and you will distinguish a variety of voices:
7) Public voices; own and competitors’ prospects, customers, lapsed customers, and employees voices.
8) Personas, market segments, affinity communities, and influence networks.
These eight insight points suggest questions, concepts, and indicators you might explore in crafting and optimizing your organization's social strategy. Match metrics to your business goals and choose software that can produce insights that will make a difference.
There's much more to sentiment analysis than dashboards, positive/negative scores, and boolean filters. To fully understand and exploit social sentiment, don't be satisfied with just more data. Insist on insight.
Seth Grimes is the leading industry analyst covering natural language processing (NLP), text analytics, and sentiment analysis technologies and their business applications. He founded Washington DC based Alta Plana Corporation, an information technology strategy consultancy, in...