Does Your Social Listening Tool Comprehend Sector-specific Context?
Context is everything they say. And it should be no different w.r.t. drawing social listening insights from the buzz around your topic of interest. While it intuitively makes sense, CMOs and the marketing function in general have been using a variety of insights platforms which are generic, off-the-shelf products – delivering the same goods regardless of whether the brand belongs to the FMCG sector or to hospitality. That is the status-quo, which we believe should change. But, is there a real need for context?
For those asking this question, the reasons are not far to seek. Here are a few of the important ones to drive home the point.
- The drivers of customer sentiment vary by sector. The telecom industry values customer service most. The consumer electronics goods sector is all about product features and functionality. In contrast, FMCG customers look for availability and product attributes such as fragrance or flavors. Adding this context while tracking customer sentiment allows one to derive insights which are strategic.
- Today’s social listening tools use artificial intelligence and deep learning methods to train their algorithms to deliver insights automatically. Making this training sector-specific, helps improve the model’s predictive capabilities and precision.
- ‘Old’ or ‘vintage’ may be complimentary words when referring to wine or high-end cars. When referring to FMCG products or political leaders, not very much so.
- Words like ‘capital’, ‘tire’, ‘mine’ etc. could mean different things to different sectors and training an algorithm to discern them by context would prove nearly impossible.
- How would a typical AI classifier tag this comment: “The patient came in to the emergency bleeding and unconscious. A lot of blood was already lost. The trauma center administered care immediately.” You’ve guessed it right!
- A sector-specific approach involves listening to platforms which are specific to the sector. For example, RateMDs is a forum you’d listen into if you are into healthcare, whereas you’d be concerned about negative reviews on TripAdvisor if you are into hospitality. Sector specificity also implies selecting the sources of data which are more relevant.
- Root cause analysis works better when your data enrichment is specific to the sector your brand belongs to. Else, the analysis stops at sentiment charts.
- Find more people who need your product or services and convert them faster, by responding in time and meeting customer expectations while gaining visibility in the process.
Sector specificity helps you draw out insights which would get lost in sentiment charts. It helps you draw out inferences which can be translated into action. Adding context makes a big difference.