Big Data Analytics Use Cases | Business Analytics 3.0
E-tailing – E-Commerce – Online Retailing Use Cases
e-tailers are constantly creating target offers to boost customer lifetime value (CLV); deliver consistent cross-channel customer experiences; harvest customer leads from sales, marketing, and other sources; and continuously optimize back-end process orchestrations.

Recommendation engines — increase average order size by recommending complementary products based on predictive analysis for cross-selling.
Cross-channel analytics — sales attribution, average order value, lifetime value (e.g., how many in-store purchases resulted from a particular recommendation, advertisement or promotion).
Event analytics — what series of steps (golden path) led to a desired outcome (e.g., purchase, registration).
Right offer at the right time
Next best offer  - deploying predictive models in combination with recommendation engines that drive automated next best offers and tailored interactions across multiple interaction channels.
Interesting Use Case – Amazon Will Pay Shoppers $5 to Walk Out of Stores Empty-Handed
Interesting use of consumer data entry to power next generation retail price competition…. Amazon is offering consumers up to $5 off on purchases if they compare prices using their mobile phone application in a store.  The promotion will serve as a way for Amazon to increase usage of its bar-code-scanning application, while also collecting intelligence on prices in the stores.

Amazon’s Price Check app, which is available for iPhone and Android, allows shoppers to scan a bar code, take a picture of an item or conduct a text search to find the lowest prices. Amazon is also asking consumers to submit the prices of items with the app, so Amazon knows if it is still offering the best prices.  A great way to feed data into its learning engine from brick-and-mortar retailers.

This is an interesting trend that should terrify brick-and-mortar retailers. While the real-time “Everyday Low Price” information empowers consumers, it terrifies retailers, who increasingly are feeling like showrooms — shoppers come to to check out the merchandise but ultimately decide to walk out and buy online instead.  See Multi-channel to Omni-channel Retail Analytics: A Big Data Use Case

Retail/Consumer Use Cases
Merchandizing and market basket analysis.
Campaign management and customer loyalty programs.
Supply-chain management and analytics.
Event- and behavior-based targeting.
Market and consumer segmentations.
Big Data Analytics History: In the 1980’s, the CPG / Retail industry transition from bi-monthly audit data to scanner data changed the dynamics of the industry.  RFID is transforming the supply chain.  Combining data from a diverse set of data resources—  adding customer sentiment data, geolocation data, customer preference analysis, and market trending information based on contextual text analytics, all add up to provide a level of sophistication previously unavailable to the industry.
Predictive analytics is well understood by the retail industry.  Retailers want to predict factors that might be important for a buyer to make a purchasing decision before that product ever was stocked on shelves.  What if retailers could know exactly what market dynamics were modifying demand curves before they occurred? Imagine the impact on operational efficiencies in terms of inventory cost control, intelligent distribution and routing, and demand projection.  The retail Use Cases are quite varied.
use-cases  bigdata 
june 2012
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