Showing posts with label Text mining. Show all posts
Showing posts with label Text mining. Show all posts

Saturday, August 15, 2009

Co-relating shopper sentiments to footfall and basket size


Statistics collected by Media agencies suggest that Teenagers are spending more time on the Web than watching TV. This is a huge inflection point as web has replaced TV as a more engaging channel. And within Online channel , Blogging and Online videos ( youtube etc ) seem to be most engaging activity. What that means is that it is important for retailers to track if shoppers express sentiment about the instore experience or product attributes online ? There are 2 kinds of scenarios which can be envisioned here.
Scenario-1 : When shoppers are expressing about their instore experience on http://www.yelp.com/ or http://www.mouthshut.com/ or http://www.eopinions.com/. But the sentiment volume has not reached a threshold where it has started influencing footfall, basket size and revenue per shopper.
Scenario-2 : The volume of sentiment expressed on online platform has reached a critical stage where more shoppers are coming to the store or the number of shoppers / basket size has decreased.
What this means is to that the retailer needs to have a framework which can keep track of the buzz velocity online and track in real time the effect of buzz velocity on instore footfall and basket size.

Customer sentiment analysis using Unstructured Text mining


There are 6 steps to mining consumer sentiments from the blog they. They are
2. Indexing
3. Filtering 'noise' words
4. Stemming
5. Geneating themes and summary gists
6. Analysis of sentiments