Measuring the Impact of Change in Retail Strategies

Data about transactions and inventory turns can help retail leaders identify which combinations of products and store locations are working well together.

This can be particularly critical for retailers of time-sensitive products such as fashion where an excess inventory (e.g., flannel shirts as part of a winter collection) could force a retailer to incur heavy markdowns to move products in preparation for new seasonal offerings.

Meanwhile, store managers for limited assortment supermarkets are under tremendous pressure to ensure that stores that carry restricted selections of items across narrow shelf space are positioned and optimized effectively for sales.

Still, it’s not always easy for regional and individual store managers to see how strategic changes have fared or what the optimal combinations may be.

For instance, while point of sale systems generate large volumes of data, it can be extremely difficult for store managers and other decision-makers to comb through this information to determine how individual products are doing or to detect trends in customer behavior (e.g., the revenue impact of placing laundry detergent at the end of an aisle at a 15-percent discount).

Predictive analytics, combined with the use of data visualization tools, can help retail leaders quickly identify product placement strategies that are working – or aren’t – that can then aid them in making strategic shifts.

For example, a regional food market is within close proximity to a local college and several businesses. The owner/operator is able to determine based on customer requests that there is a high demand for fresh fruits.

The owner stocks up on a variety of ready-to-eat fruits (apples, bananas, grapes, mixed dried fruits) targeted at local office workers and college students who are on the go. She then uses data visualization tools to see which fruits sell best at certain times or days of the week. She’s also able to determine which fruits offer the highest profit margins.

Through her analysis, the owner of the market is able to determine that while apples are the top-selling fruit, grapes carry the highest profit margin.

She also discovers through her use of data visualization tools and analytics that the highest volume of fruit sales is generated on Mondays and Wednesdays and that the sales of different fruits drop off by 35 percent from Fridays through Sundays when office workers and college students are less likely to shop at the market.

Next Steps:

  • Please join us on Wednesday, June 4, at 12:00 p.m. EDT, for our complimentary webcast: “Exploiting Digital Data to Relate Brand Awareness and Store Performance.” In the final event of this webcast series, InfomatiX will introduce techniques for connecting digital data sources such as Twitter, Google, and online stores, with classic retail data to find potential correlations between brand awareness and store performance. Join us and learn how CPG&R executives use these strategies to enable strategic decision making.
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