Sales, inventory and customer analytics across stores and channels — real-time enough that you can act on a shift in demand before your competitors have finished reading yesterday's report.
Store performance arrives as a batch report the following morning. Inventory sits in the wrong location while another store stocks out. Campaign effect is estimated after the fact, and online and offline numbers are assembled separately by different teams.
We unify point-of-sale, e-commerce and inventory data into one model, then build real-time KPI dashboards covering conversion, average order value, turnover and foot traffic across the whole estate.
Store and channel performance visible as it happens. Stock imbalance surfaced while transfer is still possible. Campaign impact measured against a consistent baseline rather than argued about.
What We Build
Sales, conversion, AOV and basket size by store and hour, not by yesterday.
Turns, coverage and imbalance across locations, with transfer recommendations.
Online and in-store revenue reconciled into a single, consistent model.
Lift measured against baseline, by segment, channel and product group.
Purchase behaviour segmentation feeding targeting and assortment decisions.
Traffic against transactions to separate a demand problem from an execution one.
Proven Results
Proof
Technical Stack
Context
Retail generates more decision-relevant data per hour than almost any other sector, and reports on it with the longest lag. A store that is converting badly at eleven in the morning is a fixable problem at noon and a historical fact by the time it appears in tomorrow's batch report. The reporting cadence is inherited from a period when nightly batch was the only option.
The second problem is channel fragmentation. Point-of-sale, e-commerce and inventory frequently sit in separate systems owned by separate teams, each producing its own version of revenue. Reconciling them monthly is a job; modelling them together once is a solution.
We unify the sources into one model and build for the cadence the decision requires. Stock imbalance surfaced while transfer is still possible is worth considerably more than the same insight delivered accurately a week later.
How It Runs
FAQ
It depends on what your POS exposes. Where direct integration is possible we have delivered refreshes measured in minutes. Where the system only supports scheduled exports, hourly is usually achievable, which is still transformative compared with next-morning batch.
Yes. We have built multi-channel analytics covering a 120-store network, with row-level security so each store sees its own numbers alongside anonymised benchmarks.
That is usually the main reason retailers engage us. Modelling both channels in one governed layer is what makes true multi-channel revenue and customer analysis possible.
Yes, measured as lift against a consistent baseline rather than raw sales during the promotion window. That distinction is what separates a useful campaign report from a misleading one.