Leading retailer exchanges 4-day old analysis for live BI on Hadoop

Posted by Robert Noakes
Monday April 10, 2017

One of America’s oldest and leading retailer generates close to 60% of its yearly revenue during the 6-week holiday season. Its digital business, worth $4 billion and growing 11% annually, depends heavily on a strong paid search presence between October 30 and December 31. Paid search over this 6-week period involves hundreds of thousands of keywords for online advertising, costs $100 – $1000 per term, and generates millions to billions of rows of online activity data.

A digital pioneer, this retail giant saw the value of big data early, and funneled ad and paid keyword data into a Hadoop cluster to help inform the keyword bidding process. Traditional analytics tools didn’t perform as hoped directly on the big data, and so their process began. They would ETL (extract, transform and load) the data into a data mart that tools like Tableau, Excel and Cognos were faster at querying.  Analysts would analyze keyword performance and adjust bidding decisions based on the results.

This multi-step process slowed analysts from quickly acting on expense saving and revenue generating opportunities. It could take hours to learn a $100 term was performing better than a $2,000 term, losing millions to wasted expense and missed revenue. The issue wasn’t the data, but delays in access due to data movement. They saw a potential competitive advantage if their BI professionals could analyze data as it landed in Hadoop; leading them to consider the AtScale Intelligence Platform.

With AtScale they eliminated the need to ETL data out of Hadoop for analysis. Analysts query and analyze paid keyword activity in Tableau, Excel or Cognos, as the data lands in their big data cluster. Despite querying against massive and growing data generated by keywords clicked (or not) by would-be online buyers, analysts get insights as fast, or faster, than the old data warehouse. AtScale’s machine-learning smart-aggregates, which self-adjust based on query activity, mean marketing analysts identify key word opportunities and make bidding changes within minutes, not hours, of the keyword being clicked.

This leading retailer, coupled with AtScale, their big data investments and existing BI tools, is able to deliver better online customer experiences and drive value for the company.