Value
One revenue number, defensible top to bottom
A single revenue model that reconciles POS, e-commerce, and finance — so weekly reviews stop debating which dashboard is right.
Inventory analytics that move product, not paperwork
Sell-through, weeks-of-supply, and stockout exposure surfaced at the SKU/store grain merchandisers actually plan against.
Customer cohorts you can act on
Repeat-rate, AOV, and channel-mix cohorts built on identity-stitched transactions, refreshed nightly.
Store-level performance that holds up to ops review
Like-for-like sales, traffic conversion, and labor productivity benchmarked store-by-store, with drill-through to receipt-level detail.
E-commerce attribution without the vendor fog
First-party attribution model owned by you — not a marketing platform — so paid spend is judged on incremental revenue, not last-click theatre.
Make better decisions using data
Retail moves fast and reports slowly. Point-of-sale runs on one platform, e-commerce on another, inventory on a third, marketing spend on a fourth — and the weekly business review is somebody’s heroic spreadsheet trying to reconcile all of it before Monday morning. Decisions about markdowns, replenishment, store hours, and ad spend get made on whichever number made it into the deck, not the right number.
Canopy Analytic helps retailers replace that reconciliation tax with analytics that hold up to scrutiny. We build the semantic layer once, plug your channels into it, and give merchandisers, store ops, and marketing the same view of revenue, margin, and customer behavior — refreshed every night, not every quarter.
Where we help
- Revenue dashboards that reconcile POS, e-commerce, marketplaces, and finance to a single trusted number, with drill-through from company total to individual receipt
- Inventory analytics at the SKU and store grain — sell-through, weeks of supply, lost-sales exposure, transfer recommendations — surfaced where merchandisers and store managers already work
- Customer cohorts built on identity-stitched transactions: repeat rate, average order value, channel mix, and lifetime value, segmented by acquisition source and first-purchase category
- Store-level performance scorecards covering like-for-like sales, conversion, basket size, labor productivity, and shrink, benchmarked across the fleet so the bottom-quartile conversation is grounded in evidence
- E-commerce attribution that you own — incrementality-aware models built on first-party data, not whatever the ad platform is willing to show you, so paid spend is judged on real contribution to revenue
How we work with you
We start with the decisions you are trying to make, not the dashboards you currently have. A two-week discovery sprint maps the real revenue waterfall, identifies where channels, calendars, or definitions disagree, and produces a prioritized backlog. From there, the first store-level scorecard is typically live in four to six weeks, with cohort and attribution work running in parallel.
We work primarily in the Microsoft ecosystem (Power BI, Fabric, Azure) and integrate with the POS, e-commerce, ERP, and marketing platforms your team already uses. The deliverable is a system your team can run — not a consulting artifact that decays the day we leave.