Retention is the hardest part of the retainer to prove. Affinsy reads each client’s order history and hands you who is ready to buy again, what to offer them, and when, with the audience for each test ready before the call.
The client asks what to test next, and the answer is in a year of their orders nobody has time to read: which products pull others along, which customers are quietly leaving, who is due to reorder. Every run reads all of it and files the result. When the client asks what changed since last quarter, that quarter’s run is still there, exactly as it was: open it next to the new one or drop it in the deck.
One timeline from what the store collected to what is still ahead: every past month split into what was bought together and what came back as reorders, the reorders that fell due and were missed, and the ones coming due as each buyer's window closes. Every dollar ahead is sized on customers you can actually reach.
Open on the live report
One row per product: what it sells, the role it plays in the basket, whether the customers who started with it came back by month 1, 3, 6 and 12 against the store baseline, and how often it gets reordered. Tick the rows and build a cross-sell, reorder or win-back audience from them, so a client's next campaign starts from the products that earn it. Read it row by row, or see the whole catalogue at once on a treemap sized by revenue.
Open on the live report
Every pair bought together, in a table with its strength, lift, confidence and how often the add-on lands, or on one map: how many customers are left to reach across, how strong the pull is up. The corner where both are high is where to act first, and it becomes one audience for the client's next campaign.
Open on the live report
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.
Customers grouped by the month of their first order and tracked month by month: the share still ordering, what each cohort is worth after six months, and where they sit in the segments today. Compared at the same age, so a young cohort never reads as a bad one, and the second-order window falls out of the data instead of a guess.
The importer recognises the order exports of the major platforms and maps their columns for you. Anything else works as a CSV with an order ID, a date, and a product per row; customer, price, and quantity unlock the full reports.
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.
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.
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.
Turn a cross-sell rule into the exact customers to contact — sized, filtered by segment, and downloadable as a CSV for your email tool.
Invite analysts and account managers with their own logins. They open the same workspace, the same MBA and RFM reports. The AI connection is wired once, for the workspace, so a client engagement survives any single laptop.
When client audits pile up, the reflex is another analyst req. Affinsy makes the analyst you have, or the founder, cover every client on the roster with the evidence to show for it. Same month of work, side by side.
AffinsyHow CRO and retention agencies (and the merchants we work with) typically use Affinsy. Quick, honest answers.
Still have a question? Email usDrop a client’s order history in. Affinsy returns the rules, the hypotheses, and the audience for each one.
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See a sample auditMerchant gives one store the same analyses: basket rules ranked into testable moves, customer segmentation with win-back audiences, and the workspace assistant.
More than 10 client stores or higher data volumes? Tell us about your book, we size larger plans case by case.
