#Big weather pattern change software#

even before the shoppers know they're going to need those particular items,' he added. This allows businesses enough time to create promotional campaigns 'to educate shoppers. 'Anything with more than 20% or greater increase in sales, over sale-day previous year, gives us the opportunity to identify those categories, and have enough time to communicate with retailers and manufacturers,' DeMeo said. Here's what the data analysis found: A day prior to statistically similar weather events, sales in 28 product categories jumped from 20% to 261% over the same day a year earlier. They factored in a wide variety of data sources, including geographic location, time of day, day of the week and a retailer's proximity to competitors' locations. Interactions' analysts uncovered which products had the most significant sales increases and decreases during specific weather events, and how shoppers' behaviors changed. 'What we identify as significant is somewhat arbitrary, but it's based on our history of knowing how we can impact sales,' said DeMeo.

#Big weather pattern change software#

It also tracked new sales patterns and shopper activity that potentially could help retailers and makers of consumer product goods (CPGs) plan in-store promotions before these events occur.īy using BigQuery and Tableau's visualization software to analyze 'hundreds of millions' of rows of data in a very short time, Interactions found it could quickly share significant findings with its retailing and manufacturing customers. The Interactions study identified repetitive weather events (e.g., snowstorms), classified them by severity, and measured their effects on sales before, during and after the events. them for retailers and manufacturers that we work with.' 'We were looking for a query that would demonstrate not just the existence of patterns, but also (how) to monetize. 'We analyzed the data to find out what patterns existed, and identify what those patterns were,' DeMeo told InformationWeek in a phone interview. This combination of tools allowed Interactions to slash data-analysis times from about week to just hours or even minutes, says Giovanni DeMeo, VP of global marketing and analytics for Interactions. The test case used Google BigQuery, a Web service for interactive analysis of very large datasets, and visual analytics tools from Tableau Software to quickly examine massive quantities of information. Interactions Marketing, a consumer engagement marketing firm, has conducted a big data test case using point-of-sale transactional data and regional weather information data from multiple sources to gain fast insights into shopper behaviors, the company said.