Based in Springdale, Arkansas., Harps Food Stores, Inc. is an 87-store supermarket chain with stores in Arkansas, Oklahoma, Missouri, and Kansas. It is the largest employee-owned company in Arkansas and the 30th largest in the United States.
Despite the retail industry’s competitive landscape and thin margins, most grocers have, until recently, made promotional decisions mainly based on three things: the amount of vendor marketing fees available, history and tradition, and “gut instinct”. These approaches are understandable given that measuring grocery and retail data is a complex and labor-intensive endeavour.
The changing and dynamic relationships between products and customers, in addition to the effects of pricing and promotions, make it humanly impossible to understand and leverage all this data.1
At the same time, promotion decisions are complicated by something called the “ripple effect”, which includes halo sales, cannibalization, and forward-buying. For example, promoting “Brand A” of soda may boost the sales of related products such as salty snacks. But it’s also likely to cannibalize “Brand B” soda sales that week and probably next week’s “Brand A” soda sales due to forward buying.
Promotional Product Selection
Daisy’s AI enables us to analyze Harp’s transaction data on a giant scale, and as a result, this significant improvement in promotional effectiveness supports our ability to meet the needs of our shoppers by keeping our prices competitive and enhancing our profitability.
Harps decided to deploy AI to improve and optimize its chain-wide pricing and promotional efforts. Citing the weekly print circular as its largest advertising expense, the company looked to Daisy to help analyze its data to “review the products to feature in its circulars”.
With Daisy’s help,, Harps analyzed years of transaction data and then simulated a mix of previously known, new, and, untried actions to find the many different ways a promotional decision may unfold. This enabled Harps to determine an optimal sequence of actions that would help it achieve the best long-term results.
AI creates a model of the retail environment that connects a retailer’s actions to market results, factoring in the “ripple effects”. This allows AI to evaluate future outcomes, even if there is no historical precedent. In effect, AI can simulate the future.
Daisy’s AI platform enabled Harps’ merchandising and marketing personnel to rapidly analyze transaction data on a massive scale and simulate potential strategies, ultimately “supercharging” the process by which the company makes promotional planning and pricing decisions.
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