Knowing your customer · The RUW Engine
This is how deep we actually go.
Most agencies say "data-driven" and mean a monthly screenshot of Google Analytics. This page shows you literally what we track, the customer profiles we build from it, and how it turns into decisions — every single week. No other agency will show you this page, because no other agency does the work.
Layer 1 · Tracking setup
What The RUW Engine records.
Before we spend a dollar of your money, your store gets wired end to end. Not "analytics installed" — tracked. Here's the actual event list:
Every session
where it came from — the ad, the post, the search, the QR at your register — device, and landing page
Every click & scroll-depth
which products get looked at, which get ignored, where people stall on a page
Every search on your site
what customers type when they can't find something — pure product-demand data most stores throw away
Every add-to-cart
the moment of intent — and the exact products, variants, and price points that trigger it
Every checkout step
started → shipping → payment → done, so we see the exact step where money leaks
Every purchase
attributed to the channel that drove it — with first-time vs returning split out
Every email & SMS touch
delivered, opened, clicked, purchased — per flow, per campaign, per segment
Post-purchase behavior
who comes back, how fast, for what — the raw material of repeat revenue
Physical store too? Your POS connects to the same system — so online and in-store finally live in one picture.
Layer 2 · Knowing your customer
Your customers, sorted into groups that actually mean something
Raw events become people. Every customer lands in living segments that update automatically — and every campaign, email, and ad speaks to a segment, never to “everyone.”
First-timers
what convinced them — channel, product, and offer — so we can find more people like them
Regulars
their rhythm: how often they buy, what they cross into next, what brings them back
Big spenders
your top slice of customers usually drives an outsized share of revenue — we find what they have in common and protect them
Lapsed
gone quiet past their normal rhythm — winback territory, with the message matched to what they used to buy
Almost-buyers
carted or checkout-started but never finished — the cheapest revenue in your whole funnel
Layer 3 · Attribution
Every dollar out gets matched to the dollar in.
When a sale happens, the Engine answers: which channel found this person, which touch convinced them, and how long it took. That's how we know an ad that looks expensive is actually your best one — because its customers come back — and a channel that looks cheap is quietly a dead end. When it really matters, we go further: pause a campaign for part of the audience and measure the difference, so we know the campaign caused the sales instead of taking credit for them.
Layer 4 · The weekly loop
What happens with all of it on Monday morning
All of it lands in one weekly report you can read in five minutes. Here's the exact shape of it — illustrative numbers, real structure:
SAMPLE WEEKLY REPORT — ILLUSTRATIVE
1 · What happened
Revenue, orders, and traffic vs last week and vs your baseline — with the "why" attached, never just numbers.
2 · What worked
"The winback email to lapsed customers outperformed — that version is now the default." Winners get named and doubled down on.
3 · What didn't
"The Tuesday creative got cheap clicks that never bought — killed it Wednesday." We tell you what failed and what it taught us. Agencies that never report failures are hiding them.
4 · What changes next week
The move list: budget shifts, new tests, pages being fixed — each tied to a number from section 1. You always know what your money is doing next and why.
What this looks like in practice
When the data says this, we do this.
| The Engine sees… | So we… |
|---|---|
| One product page gets traffic but no add-to-carts | we fix that page — images, price framing, sizing info — before spending another ad dollar on it |
| A zip code near your store converts above everything else | local ad budget shifts into that radius, and lookalikes get built from those buyers |
| Site searches spike for something you don't stock online | that product goes online this week — demand already proved itself |
| Checkout drop-off concentrates at the shipping step | we test a threshold (free over $X) — the data tells us what X pays for itself |
| One creative's clicks are cheap but never buy | it gets killed even though it 'performs' — we optimize to revenue, not clicks |
| Email drives repeat orders but the list barely grows | capture becomes the priority: popup offer, register QR, checkout opt-in |
This is the difference between running ads and running a system. The free audit shows you what your store's data would say.