Can sentiment analysis improve merchandising calls?
Through a special arrangement, what follows is a summary of an article from Retail Paradox, RSR Research’s weekly analysis on emerging issues facing retailers, presented here for discussion.
Marketers have long used sentiment analysis to target offers in the digital domain, but a new generation of demand forecasting capabilities is extending its use into merchandise planning.
Sentiment analysis examines “non-transactional” data that consumers leave along their digital paths-to-purchase that can offer an early indicator of demand. A simple example is the number of positive mentions on social or e-mail streams about a new offering. Online clicks, geo-location info and other digital data can also offer clues as to whether underlying sentiment is positive, negative or neutral.
Our latest supply chain benchmark report finds retailers clearly interested in modernizing their forecasting engines to take in new data (i.e., weather, trade area, competitive pricing), but standing out on their list of “wants” was sentiment.
The findings show apparel and brand managers, who are probably both more experienced and adept at using sentiment analysis in marketing, are only slightly more interested in using that data for forecasting than grocers, drug store, and convenience stores (FMCG) – and most of those that are interested in using it already are. This no doubt is the result of both those retailers’ design-focused merchandise planning processes and long supply chains; once a product is committed to, it’s much harder to turn back than it might be in faster-moving verticals.
The “sweet spot” in sentiment analysis for forecasting is with general merchandisers. Those retailers feature a lot of seasonally sensitive and popular items. But, unlike fashion and specialty merchants, they are fast-replenishment retailers and can react relatively quickly to sudden shifts in demand (for example, if an item featured in a popular movie hit). And since they tend to be high-volume retailers, a mistake can be very costly, while successfully predicting as shift in demand is very rewarding.
The news is good for solutions providers: the desire is there, and there’s plenty of upside before the “implemented/satisfied” group is as big as the “very valuable” group of retailers.
- The Rising Importance Of Sentiment Analysis For Demand Forecasting – RSR Research
- Supply Chain Management 2018: In Service Of The Customer – RSR Research
DISCUSSION QUESTIONS: Where do you see the opportunity and limits in using sentiment analysis to help gauge demand for future product assortments? Do you see it providing just as much benefit to merchants as marketers?