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Intelligence@Scale
eTailing India Summit 2014
krishna.raghavan@flipkart.com
Handling scale is not enough…
Intelligence will be the differentiator
Problem 1: How do you sell and
merchandise your products?
● Pricing
● Promotions/Offers
● Bundling
● Ads
Would that be enough?
Gather Customer insights at every step of
the customer journey leading to
personalisation and delight
As an example: -
● Customer browse behavior
● Customer purchase history
● Inferring Product relationships
● etc…
(Do this for 18M+ customers!)
Seller Analytics and Recommendations
● Provide deep selling insights for your
portfolio
● Comparative aggregated analytics and
trends
● Recommend course of action, not just
analytics
Problem 2: Who is the best seller for the
customer?
Do this for thousands of sellers and millions
of customers
Seller Prioritisation - How?
● Seller Performance in terms of buyer
experience e.g. cancellations, returns
● Customer preferences in terms of SLA,
Price,Feedback
● Geo
● Personalisation here again…
● Self Learning
Problem 3: How do we identify bad quality
products amongst millions on the platform?
10000+ Categories
Long Tail selection
Product Insights: How?
● Customer signals - Returns, Feedback
● Conversion - Funnel analytics
● Pricing Analytics
● Power pro-active resolution
Thank You…
Q&A

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Keynote: Intelligence at Scale by Krishna Raghavan (Flipkart)

  • 1. Intelligence@Scale eTailing India Summit 2014 krishna.raghavan@flipkart.com
  • 2.
  • 3.
  • 4. Handling scale is not enough… Intelligence will be the differentiator
  • 5. Problem 1: How do you sell and merchandise your products? ● Pricing ● Promotions/Offers ● Bundling ● Ads Would that be enough?
  • 6.
  • 7. Gather Customer insights at every step of the customer journey leading to personalisation and delight
  • 8. As an example: - ● Customer browse behavior ● Customer purchase history ● Inferring Product relationships ● etc… (Do this for 18M+ customers!)
  • 9. Seller Analytics and Recommendations ● Provide deep selling insights for your portfolio ● Comparative aggregated analytics and trends ● Recommend course of action, not just analytics
  • 10.
  • 11. Problem 2: Who is the best seller for the customer? Do this for thousands of sellers and millions of customers
  • 12.
  • 13. Seller Prioritisation - How? ● Seller Performance in terms of buyer experience e.g. cancellations, returns ● Customer preferences in terms of SLA, Price,Feedback ● Geo ● Personalisation here again… ● Self Learning
  • 14. Problem 3: How do we identify bad quality products amongst millions on the platform? 10000+ Categories Long Tail selection
  • 15. Product Insights: How? ● Customer signals - Returns, Feedback ● Conversion - Funnel analytics ● Pricing Analytics ● Power pro-active resolution