Stop guessing
what to test next.

Drop a client’s order history in. Affinsy mines what sells together, ranks test hypotheses by expected revenue, and hands you the audience for each one: Klaviyo, CSV, API, or MCP.

Affinsy Mine: association rules ranked by lift, confidence, and revenue impact
01 · How it works

Bring the data in.
Delegate the rest.

Treat Affinsy like a coworker on the account: hand over a client’s orders, delegate the mining, review the filed work. The analysis an analyst would bill weeks for is back in minutes.

client_orders.csv
100%
Auto-detected
order_idcustomer_idproduct_skuqty
Step 01
Hand over

CSV upload or read-only API key. No app install on the client's store, no dev review, no IT ticket. You can have a dataset flowing before the kickoff call ends.

Hypothesis · #1 of 12Validated
Bundle Cleanser + Toner at PDP
Lift
2.3×
Confidence
78%
Audience
1,847
Expected uplift+$4.3k / 30d
Step 02
Delegate

It mines the orders and comes back in minutes with ranked test hypotheses: expected lift, audience size, confidence band. Ask a follow-up in plain language and the assistant runs the next analysis and builds the audience.

Re-runs · MonthlySame settings
Mar 2812 hypotheses
Apr 2818 hypotheses
May 28Next run
Step 03
Review

Every run is filed into the client's spaces, so the work never leaves with whoever ran it. Re-run before every call with the same settings, open the analysis from two months ago in one click, and the next QBR is already half-written.

02 · Merchandising EngineerBeta

Meet your
Merchandising Engineer.

Every workspace comes with a Merchandising Engineer, an assistant that knows the client’s orders, products and analyses. It answers from the data, starts a new analysis when the question needs one, and builds the customer lists to act on.

Grounded
Answers cite your orders
Hands-on
Runs MBA & RFM for you
Included
In the Agency plan
1

Answers from the data, not the internet

Every number comes from the workspace's own orders and completed analyses. If something isn't in the data, it says so. It doesn't guess.

2

Runs analyses from a sentence

Ask a question that needs new work and it starts the Market Basket or RFM run itself, files it into the right space, and links the result when it's ready.

3

Builds lists you can act on

Turn a cross-sell rule into the exact customers to contact — sized, filtered by segment, and downloadable as a CSV for your email tool.

03 · Inside the report

Computed once,
stored for good.

The Mine, Hypothesize, and Activate panels above are the interactive surface. Underneath, every run mines your order history into rules, segments, movers, and product diagnostics, and files the result in its space. When the client asks what changed since last quarter, that quarter’s run is still there, exactly as it was mined: open it next to the new one or drop it in the deck. Nothing to re-run, nothing to reconstruct.

Affinsy report — executive summary revenue waterfall: captured revenue, winnable cross-sell, replenishment due, total potential
On the table
$3.5M
+25% on captured revenue
Executive summary

The headline numbers, up front.

One bridge from captured revenue to what's still on the table: the share flowing through co-purchase patterns, cross-sell winnable right now, and replenishment coming due. Every dollar of upside is sized on customers you can actually reach.

Open on the live report
Affinsy RFM report — revenue treemap by customer segment with a ranked share table
Hibernating
$264.2K
37.6% of revenue, ready to win back
Customer segmentation

Where the money lives, by customer.

Every run also grades the customer base with RFM: Champions to Hibernating, revenue mapped per segment, and a ranked share table ready for the deck. Win-back and VIP audiences export exactly like basket audiences.

Affinsy report — biggest lift changes split into rising and falling rules
Movers
±10% lift
vs. the previous 30-day window
Movers

What's heating up, what's cooling off.

Rules whose lift shifted by 10%+ versus the previous 30-day window, split into risers and fallers. Feature the rising ones before the trend matures, investigate the falling ones before retiring them — the temporal signal you don't get from a single-snapshot report.

Open on the live report
Affinsy report — product popularity table with sparkline trends, orders, buyers, revenue, rules
Top product
1,297 orders
appears in 55 rules
Product popularity

Which products are pulling weight.

Every catalog item sorted by orders, with the number of rules it appears in, what it substitutes for, and a week-by-week trend sparkline. Useful for the moment a client asks why their best-seller stopped lifting the basket.

Open on the live report
04 · Team accounts

Someone’s on holiday.
The client work isn’t.

Invite analysts and account managers with their own logins. They open the same dataset, the same MBA and RFM reports and the same spaces. The AI connection is wired once, for the workspace, so a client engagement survives any single laptop.

5seats, flat price
1bill, owner's card
0shared logins
Start with your team
Horticulture20 003 rows
MKMartaOwner
AKAlexMember
PSPriyaMember
1One dataset, three logins
Import the client's export once. Everyone you invite works on those exact 20 003 rows: no second upload, no version that only one laptop has.
Testing
Reopen the $13.1M paired demandMBA 126
Done
Reopen the $13.1M paired demand
MBA 126AK
2Spaces change hands
A space holds every analysis behind one merchandising idea. Whoever is at their desk opens it, adds a run and drags it from Testing to Done.
MCP serverWorkspace-level
Connected
MKClaude
AKClaude
PSClaude
3Connect AI once
Set up the MCP connection for the workspace, not per person. Every member queries the same client data from their own AI tool.
05 · Frequently asked

The questions we hear most.

How CRO and retention agencies (and the merchants we work with) typically use Affinsy. Quick, honest answers.

Still have a question? Email us
Affinsy is built for the way agencies actually work. Drop in a client’s order CSV (or wire it up via webhook/API) and within two minutes you get back ranked test hypotheses, each with the backing association rules and a customer audience for each. Walk into every QBR with a fresh, statistically-backed test backlog instead of rebuilding spreadsheets the night before. One dataset per client, rerun on your cadence.
Before the next QBR

Walk in with a
ranked test backlog.

Drop a client’s order history in. Affinsy returns the rules, the hypotheses, and the audience for each one.

7-day free trial · Refreshed in under two minutes