About us

Built by people who lived the problem

RetailNorm exists because we spent years doing the exact work this tool eliminates — normalizing retail media data in Excel before every client call.

Why we're building this

Retail media is a $108B industry with no unified measurement standard. Every platform — Amazon Ads, Walmart Connect, Criteo — uses a different attribution model, a different lookback window, a different definition of success.

For agencies managing campaigns across multiple networks, this means hours of manual work every reporting cycle. Exporting CSVs, normalizing numbers in Excel, building client decks from scratch. It's smart people doing repetitive work.

We built RetailNorm to fix that. One attribution model applied across every platform. One source of truth. One click to generate the client report.

Who this is for

Mid-market agencies with 5–50 people. Media planners and commerce managers who juggle 3–8 clients across 2–4 retail media networks. Teams that are too small to build internal tools but too sophisticated to keep relying on Excel.

The big holding companies — Publicis, Omnicom, GroupM — have built their own internal normalization systems. RetailNorm gives everyone else access to the same capability.

The Problem
Attribution chaos

Amazon uses 14-day last-click. Walmart uses 30-day. Criteo uses post-click + view. Comparing ROAS across these platforms without normalization is comparing fiction to fiction.

The Solution
One correction layer

RetailNorm applies a Bayesian normalization engine that adjusts for window decay, view-through inflation, and model differences — then shows you where budget should actually go.

What we believe
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The industry won't standardize itself

Retailers have no incentive to agree on measurement. The solution has to come from independent tools that sit on top of fragmented data and make sense of it.

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Simple beats comprehensive

You don't need a data warehouse. You need normalized ROAS and a client-ready report before the call starts. We're an opinionated engine, not infrastructure.

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Agencies deserve better tools

Enterprise platforms charge $3k–10k/month with annual contracts. We're building for the other 90% of the market — at a price that makes sense for independent agencies.

$108B
Retail media ad spend
200+
Networks, no standard
54%
Cite analytics gaps
4–8h
Manual work per cycle

See the correction in your data

Upload a CSV from any supported platform. The engine corrects attribution, models returns, and recommends budget allocation — free, no signup required.

Open Dashboard — Try Free How the engine works →