Retail Intelligence That Reasons About Your Data

Retail data teams make million-dollar decisions from broken data. OnlyMetrix fixes the foundation.

What's actually breaking

Every retail data team recognizes these. Most have accepted them as normal.

Agents hallucinating on inventory and sales data

An AI agent generates SQL that double-counts returns, misjoins product tables, or invents a column that doesn't exist. The numbers look plausible. Nobody catches it until the buy is already placed.

Analyst backlog. weeks to answer simple questions

"What's our basket size trend by store?" goes into the queue. Two weeks later, the answer arrives. By then, the promotion is over and the data is stale.

High-value churn invisible until it's too late

Your best customers stop buying. Nobody notices for 6 months because the churn metric uses a 180-day window when 142 days would catch them earlier. The threshold was a guess.

94% revenue concentration risk nobody has surfaced

Three countries drive nearly all of your revenue decline. The data exists to see it. But nobody ran the sensitivity analysis because it takes a week to set up.

What OnlyMetrix surfaces automatically

These findings came from a real retail transaction dataset. No analyst time. No custom SQL.

Optimal churn threshold: 142 days not 180. +7.4% F1.

Autoresearch tested 29 threshold variations and found that 142 days produces a 7.4% improvement in churn detection accuracy over the industry-standard 180-day window.

340 at-risk customers. 68% share a category pattern.

The analysis layer identified 340 customers showing churn signals, and found that 68% of them concentrated their purchases in the same product categories. a retention opportunity hiding in plain data.

One country accounts for 72% of revenue decline. Surfaced automatically.

The drivers primitive ranked all dimensions by coefficient of variation and found geographic concentration. 72% of total revenue decline traced to a single country, and no analyst had to ask the question.

Churned customers independent of high spenders (Jaccard=0.049).

The correlate primitive found near-zero overlap between churned customers and high-value customers. Churn isn't a pricing problem; it's a product or service problem. This changes the intervention strategy entirely.

From raw transactions to governed intelligence

OnlyMetrix connects to your existing data infrastructure and layers governance, analysis, and continuous improvement on top.

1

Connect to your data

POS systems, loyalty databases, ecommerce platforms, CRM. OnlyMetrix connects to Snowflake, PostgreSQL, and ClickHouse. wherever your retail data lives.

2

Govern retail metrics

Define basket size, churn rate, conversion, average order value, customer lifetime value. with the compiler. Fan-out protection, PII masking, three-way classification included.

3

Analysis layer finds what's changing

13 reasoning primitives investigate your metrics automatically. Trends, drivers, sensitivity, correlation. the analytical chain that would take a human analyst weeks runs in seconds.

4

Metrics improve overnight

Autoresearch tests threshold variations against your ground truth while you sleep. Tomorrow's churn metric is more accurate than today's. Every night.

See your findings in 24 hours

Run the at_risk_profile analysis on your data. See which customers are churning, why, and what the optimal intervention threshold is, before your next standup.