Retail Analytics Platform

At 50,000 orders a month, this D2C brand was still running its operations from platform exports and weekly spreadsheets. The operations team spent six to eight hours every week compiling a report that was outdated before anyone read it. Inventory stockouts were discovered by customer service, not by the data. Marketing spend decisions were made based on what each platform claimed it had driven, and when you added those numbers together they accounted for more revenue than the business had actually generated.

The founder knew the data infrastructure had not kept up with the growth. The question was where to start.

We started with the attribution problem because it had the most immediate commercial impact. Building a unified view of what was actually driving revenue required connecting the marketing platforms, the order management system, and the customer database into a single environment with consistent logic. Once that was in place, the inventory and cohort analytics followed from the same data foundation.

The most significant finding came in the first month. Cohort data showed a sharp drop-off in customer retention at Day 30 that had never been visible before. Not because it was not happening, but because the data to see it had not been organised. A reactivation campaign targeted at customers approaching that drop-off point launched within six weeks.

What we delivered: Unified data pipeline from every source system. Data models for cohort analysis, inventory health, and marketing attribution. Automated daily dashboards for operations, marketing, and finance. Stockout risk alerting that surfaces issues before they affect customers.

The outcome: Six hours of weekly manual reporting reduced to zero, fully automated. Stockout rate reduced by 34% within 60 days. The Day-30 retention issue identified and addressed through a targeted campaign. 20% of marketing budget reallocated to higher-performing channels once unified attribution was in place.