Data-Led Alerts Transform Retail Execution

How Acosta redefined retail efficiency and boosted sales at Kroger.

HOW WE DID IT

Acosta wanted to improve our client’s retail success by deploying the right services and people to the right place at the right time. We tapped into our robust data and technology capabilities to create a solution that would directly impact our retail modeling and in-store approach.

Acosta’s business intelligence team deployed a cutting-edge predictive forecasting engine that uses historical point of sale (POS) data to anticipate store conditions. A proprietary algorithm assesses the client’s products with the most significant lost sales value (LSV) and the sales impact of each in-store intervention, quantifying the influence of Acosta’s intervention and offering constructive feedback on sales rep performance. This advanced system continually refines its accuracy through machine learning.

The forecasting engine prioritizes value-driving activities and guides Acosta’s field merchandising teams to the most strategic retail locations, enabling rapid responses to changing store conditions and immediate issue resolution.

In a single quarter, implementing our data-led approach led to more than $180,000 in incremental orders, affirming the immense value of harnessing data and predictive analytics to transform conventional retail operations. We improved order accuracy and ensured quick product replenishment by making nearly 8,000 critical corrections in stock levels (Balance on Hand – BOH and Computer Assisted Ordering – CAO.)

Through predictive forecasting, we increased orders and significantly enhanced the overall efficiency of our client’s retail execution budget. After seeing these initial results, our client built a dedicated team focused on taking full advantage of the insights Acosta’s proprietary technology offers.