Copyright 2014-15 Retail Automata Analytics www.retailreco.com 1 Accurate Recommendations For Retailers of all sizes and domains A Predictive Analytics Breakthrough (This presentation contains brief disclosure of a patent pending technology) www.retailreco.com
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Breakthrough in Predictive Analytics for retailers: How our recommendation engine predicts future buys of customers?
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+Exact values present in all historical data sources,
of all different feature sets and corresponding affordability price ranges forms the structure of
data used for predictive analytics.
DATA ADAPTERS
Unify the customer preference data from all historical sources including offline and online store sales history, shopping cart, browsing history, social media etc. Each data source can have different importance or weight.
+ Affect the strength of sales record contribution to predictive analytics data structure.
All the disclosure of the invention presented in this presentation are covered under patent application “Unified Predictive Retail Eco-System” : (number: 2465/MUM/2015).
RESULT: MOST ACCURATE PREDICTIONS OF FUTURE BUYSFOR RETAILERS OF ALL SIZE AND DOMAINS
Along with the Seasonality of Products and Frugality of customers (as well as products) noted down. Which are powerful customer segmentation criteria for
RetailReco campaigning system.A Personalized Omni-Channel world of only relevant
products is automatically created for every customer.
Applies Big Data technologies to handle scalability.
Sparsity in Unified abstracted predictive analytics data structure is handled by Dimensionality reduction
techniques. Effect of frequent purchases of a small set of products
or customers buying all products is handled by normalization techniques.