With enormous spends that FMCG has to incur on advertising, Prism could help in assessing results of campaign management through a targeted time series and attribute analysis. More importantly, Prism could track activities of multiple competitors on a real time basis, alerting one to events like price drops, new launches, etc, automatically. We could also help in social profiling of the Target group – age, gender, other likes and dislikes, etc, so that one can build a better profile of the audience and spend the advertising budget more smartly for a higher RoI.

Create customer media war rooms to analyze and measure omni channel customer experience correlate satisfaction from structured and unstructured data.

Prism helps you answer complex questions like "how many female platinum customers are unhappy about apparel?" Prism helps you

  • Collect data about customers from structured, internal and social channels
  • Resolve customer identities across internal and social channels
  • Predict customer purchasing based on social profiles from facebook and twitter
  • Get customer sentiments from internal and social channels and map this to customer lifetime value and demographics
  • Feed the above customer intelligence right back into point of sale or customer interaction to improve customer experience, cross selling and retention strategies

eCommerce

Unlike traditional retail, eCommerce companies face specific challenges - switching between providers is easy, there is no face to face and personalized interaction, and customers are a lot more net savvy, with bad reputation capable of spreading much faster. Ecommerce relies a lot more on text based interactions – these could range from customer reviews on the website itself, to customer emails and call centre logs, to customer feedback on social media. In the absence of a face to face interaction, it becomes critical for all this data to be captured and analysed for forging a competitive advantage. Prism, Prism tools and Platform allow an E Commerce portal to:

  • Integrate feedback across customer channels (emails, online reviews, social media, call centre transcripts, etc)
  • Determine what area customers like (or do not like) about the store (eg delivery times, service, damaged goods, payment issues, return or refund issues), so that they can be immediately looked into
  • Determine what customers are saying about various products so that this information can be used for better stocking decisions going forward, rather than relying purely on actual sales, which is a post-event indicator
  • Monitor competitive action (e.g. events, promotions, etc.) on a continuous basis, in an automated manner