From $6M in stranded inventory to over $1M in category revenue within a month of deployment.
The company's analytics infrastructure had not kept pace with the complexity of its business. Excel served as the primary tool, with data distributed across disconnected systems and more reports than actionable insights. The result was predictable: top-selling products suffered from chronic in-stock failures while receiving insufficient inventory support, and slow-moving products tied up $5M in working capital. The company had no competitive pricing intelligence, leaving it unable to benchmark positioning or respond to market moves. Private label expansion opportunities existed but were invisible without the analytical infrastructure to surface them.
Profitmind deployed its agentic AI platform with four specialized agents- Competitive, Pricing, Inventory, and Assortment- working in concert. The platform ingested internal transaction and catalog data alongside live competitor website data, creating a unified intelligence layer in place of the siloed reporting environment. Clickstream analysis was layered in to identify where paid search investment would outperform price changes, allowing the team to allocate spend with greater precision. A Monday Morning reporting cadence was established, delivering weekly KPIs, demand insights, and assortment analytics to decision-makers before the week began. Implementation required six weeks.
In the first month of operation, pricing recommendations for a single category generated over $1M in revenue and over $600K in profit, establishing proof of concept well ahead of schedule. Twelve-month projections, built from POC results and measured elasticity, indicated $14M in incremental revenue and $6M in incremental profit. Working capital tied up in slow-moving inventory is expected to improve by $7M annually as inventory intelligence shifts purchasing toward demand-matched positions.