Amazon analytics AI is software that answers questions about an Amazon seller's performance by reading that seller's own sales, fee, advertising, return, inventory, and cost data. The seller asks in plain language, and the software returns a figure, the products behind it, and the reason it moved.
Three things get confused with it.
Amazon's shopper-facing assistant, Rufus, is for customers. Per Amazon's own announcement on aboutamazon.com, Rufus answers shopper questions from product listing details, customer reviews, and community Q&As, and helps with comparisons and order tracking. It has no view of a seller's costs or fees and is not an analytics tool for sellers.
Keyword and listing AI reads search data and writes copy. It optimizes for traffic and conversion. It does not know what a unit cost to land or what Amazon charged to fulfill it, so it cannot say whether the traffic it won was worth having.
A general-purpose chatbot fed a CSV export can summarize what is in the file. It cannot add what is missing from the file (landed COGS, fees by SKU, refunds by SKU), and it can misstate totals from a long paste. The analysis is only as complete as the export, and Seller Central exports are never complete on cost.
An Amazon seller's profit sits at the intersection of six data sources that Amazon never combines for you: ordered product sales, referral and fulfillment fees, advertising invoices, refunds and reimbursements, storage charges, and your own purchase orders and freight bills. Business Reports show the first. Settlement reports show the second and fourth. The ad console shows the third. Your inventory system shows the last. Nobody at Amazon puts them on one line per SKU.
A seller with 300 SKUs cannot rebuild that line by hand each month. Most do it for the top ten and guess at the rest. Amazon analytics AI, running on data that has already been reconciled at the SKU level, lets the seller ask about SKU 187 with the same confidence as SKU 1.
Illustrative numbers. Take a seller with one SKU, a garlic press at $19.99 in Home and Kitchen, where Amazon's published pricing page lists the referral fee at 15 percent. Fulfillment fee figures are illustrative; Amazon sets them by size tier and weight.
The seller asks: did this product have better margins in July than in August?
July
August
Revenue rose 13.3 percent. Contribution fell 35.7 percent. The answer to the seller's question is July, by a wide margin, and the reasons are three: a fulfillment fee band change worth $0.65 per unit, a landed cost increase worth $0.70 per unit, and $480 more ad spend that bought 40 more units. An analytics AI on reconciled data returns all three. An AI on Business Reports alone returns "August was better," because ordered product sales went up.
Crunch is the analytics AI inside ConnectBooks. It reads the seller's reconciled data from Amazon, Shopify, Walmart, TikTok Shop, and eBay and answers questions about profit, margins, advertising, inventory, fees, and cash flow. Each answer follows the same chain: what changed, across which periods, on which products, why, and what to do next. The data it reads comes from settlement reconciliation into QuickBooks or Xero and the SKU-level profit reporting built on top of it.
What it cannot do: fill in a landed cost you never recorded, know that your supplier raised prices before the PO hits the books, or take an action in Seller Central. It answers and recommends. You decide.
No. Amazon's Seller Assistant, described on aboutamazon.com, works inside Seller Central on account health, inventory alerts, compliance, and listing tasks, and can take actions with the seller's permission. It works with Amazon's view of your account. It does not hold your landed COGS, your Shopify payouts, or your QuickBooks ledger, so it cannot compute contribution margin across channels.
You can get a summary of the export. You cannot get a margin the export does not contain. Business Reports carry no cost data and no fee detail; settlement reports carry fees but no COGS. The chatbot will produce a margin figure anyway, which is the danger.
Landed cost per unit, referral and fulfillment fees per order, ad spend attributed per SKU, refunds and reimbursements per SKU, and storage charges. If any one is missing, the AI should say so rather than compute around it.
Crunch does not. It reads reconciled books and returns answers and recommendations. Price changes, campaign pauses, and removal orders stay with the seller.
A dashboard shows the metrics its designer chose. Analytics AI answers the question you asked, including ones the dashboard has no tile for, such as "which SKUs were profitable last quarter but are losing money this quarter."
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