For multi-channel CPG brands

The context layer for CPG revenue.

AI is only as good as the data you feed it. We make your revenue data legible to AI, surface every dollar you are missing across nine levers, and Rev runs the change — with the math behind every number.

Rev

surfaces dollars + runs the change

Revenue context layer

margins · definitions · what worked

Store · ERP · BI · Ads · Marketplaces

Weekly Revenue Brief

8:00 AM

Pricing · 12 SKUs, margin +1.8 pts

+$38K

Bundles · 3 new, untapped AOV

+$47K

Promotions · 2 under 1.5x return

−$19K

Discounts · 35% of orders given away

−$31K

Shows its work

Approve all →

Your weekly revenue review eats days. It still misses the money.

Every week, your team rebuilds the same report by hand. A dozen tabs, pulled from systems that do not talk. By the time it is done, the meeting is here and nobody has acted on it. The report tells you what happened. It never tells you where the revenue is, or captures it.

Sessions

Conversion

AOV

Margin

Promo

Inventory

Returns

Shipping

Cohorts

Channels

Discounts

Summary

⏱ due 1pm

Three layers. One revenue layer.

Data in at the bottom. Action out at the top.

Layer three — Rev

Rev reads the context, surfaces the dollars across nine levers, ranks them by profit, and runs the change you approve.

Context becomes action.

Layer two — revenue context

AI without context guesses. We encode your margins, your definitions, your rules, what you have tried, and what actually worked.

Every number Rev produces is grounded in how your business runs.

margin rules

definitions

what worked

Layer one — revenue data unified

We connect your commerce stack. Your store, your ERP, your BI, your ad platforms, your marketplaces.

Your revenue data lands in one place, in sync.

Nine levers. Every week. With the math.

Pricing

Margin up 1.8 points on 12 SKUs.

Apply new prices →

Bundles

Three bundles, $47K of untapped AOV.

Build them →

Shipping thresholds

Move $50 to $55. AOV up 4%.

Set it →

Promotions

Two promos returning under 1.5x.

Reallocate spend →

Retention

A lapsing segment worth $90K a year.

Launch the flow →

Inventory

$56K tied in slow stock.

Rebalance it →

Discounts

35% of orders discounted, $31K given away.

Tighten the rules →

Checkout

Drop-off at the shipping step.

Test the fix →

AI search

You are invisible in AI answers for your category.

Close the gap →

Rev does not hand you a dashboard. Rev hands you the dollars, the method, and the change, ready to approve.

Built for the systems you already run.

Shopify, Salesforce Commerce Cloud, Power BI, Amazon, Klaviyo, and the rest of your stack via API. We connect to what you have. No rip and replace.

Your revenue layer

Your revenue data, ready for any AI.

Once your revenue layer is built, it is available to your own tools via MCP. Point Claude, ChatGPT, or your own agents at it and your team gets grounded answers about your revenue, not guesses. Rev runs the change. Your team asks anything.

Claude

ChatGPT

Your agents

Your revenue layer

“AOV is $58, up 4% WoW”

“Margin on SKU-114 is 41%”

“Promo ROAS is 1.3x”

It reconciles to your numbers. That is the whole point.

A national US retailer in the supplements category replaced a manual twelve-tab weekly report with an 8am brief that reconciles to their published revenue within 0.1 percent. Their team stopped building the report and started acting on it.

Weekly Revenue Brief

8:00 AM

$226K

surfaced this week across nine levers

Reconciles to published revenue

within 0.1%

Reconciliation, last four weeks

0.1%

max variance

Week 1

✓ 0.04%

Week 2

✓ 0.09%

Week 3

✓ 0.06%

Week 4

✓ 0.10%

What changes in the first month.

8am brief

A twelve-tab weekly report, rebuilt by hand, now an 8am brief.

Minutes

Days of reporting, down to minutes.

Analysts + tool

On track to replace a few analysts and the reporting tool for the function.

~$100M

GMV analyzed

$2–3M

revenue surfaced

21

statistical models

9

levers