Growth Opportunities From Your Own Sales History
What to sell next, and what is quietly going wrong, across your jewelry stores on Amazon, Walmart, eBay and Shopify. Every finding names its evidence and opens the step that fixes it.
- Listing error on a best sellerBirthstone stud earrings, 14K yellow goldSold 41 on Amazon in 90 days · listing error since TuesdayOpen the listing →
- Comes back oftenSterling stackable ring, size 6Returned 7 times in 90 days on Amazon · top reason: too smallSee the returns →
- Units fell after a price riseDiamond eternity band, 1 ct. t.w.Walmart units down since the price moved up · the change markedCheck the rule →
Each store’s sales history, as far back as its channel allows
Press Read sales history on a store and Appath reads that store’s sales back as far as its channel allows. From then on it keeps every order it handles, including orders shipped elsewhere, so the history keeps building with no further channel call. Nothing reads a channel until you press the button.
Each store’s history is read from its own channel and kept with that store. A product removed from your catalog keeps its sales history.
Best sellers and slow movers
For each store, over 30, 90 and 365 days, each figure stamped with its period and as-of time.
A listing under 180 days old is in neither list.
One read-only section for sales, returns and opportunities
Insights sits beside Orders and Books in Appath. It never edits anything: a row opens its product, its store or the step that fixes it.
Every rule’s findings, each with its evidence, its worth as an estimate, and the step that fixes it.
Best sellers and slow movers on each store by 30, 90 and 365 days, with high returns beside them.
Each store’s units and sales per period, its last sale, and how much history Appath holds for it.
Returned units by product and the channel’s own reason, beside what sold.
Units and sales by month and year, by kind of item, and each season against last year’s.
- Product type
- Metal
- Stone
- Price band
- Brand
- Supplier
In jewelry a single SKU seldom sells again the next year, so the history that pays is by kind of item and time of year: which metals, stones and price bands sold, in which season, on which store. Realised price sits beside your rule’s price, so a sale under it shows.
Four weeks before each season, what sold last year and is not ready
The seasons are built in. Each is compared with last year’s, and while one is on, you see its pace day by day against the same days last year. Twenty-eight days before a season starts, the Advisor lists what sold in it last year and is now not listed on a store it sold on, paused, out of stock or discontinued at the supplier, or carrying channel errors.
- Valentine’sJan 25 to Feb 14
- Tax refundsFeb 1 to Apr 15
- Mother’s DayThe three weeks to the day
- WeddingsMay to September
- Father’s DayThe three weeks to the day
- HolidayThanksgiving week to Dec 24, with Black Friday to Cyber Monday marked
- EngagementNov 20 to Feb 14
Each finding names its evidence and opens the step that fixes it
The rules run every night over your own figures. They are fixed rules, not guesses, and each finding’s worth is stated as an estimate, in its unit. Appath keeps every finding’s history: when it was first seen, resolved, dismissed or acted on.
- A high-margin item listed nowhere, sales or not
- A supplier discontinuing a best seller, with its family’s in-stock alternatives
- A best seller out of stock at the supplier
- A best seller whose listing carries channel errors
- An item that comes back often, with its top return reason
- Units that fell after a price rise
- A best seller whose visits fell
The steps are the platform’s own: a listing error opens the listing preview, a price finding opens your pricing rule, a discontinued best seller lists its family’s in-stock alternatives from the catalog, and returns are read from each channel’s own reasons.
Computed and realised, and a timeline that explains a sales move
The computed margin per item and channel, from your rule’s price, the supplier’s cost and the marketplace fee, rebuilt each night and after a rule or supplier file changes. The realised margin from your books, over the orders Appath booked. And a price and stock timeline: each price change and each stock-out a listing had, marked on its sales, so a drop in units has its cause beside it.
What was seen and not bought
Sales say what sold; traffic says what was seen and not bought. Where a channel provides it, Appath reads visits and conversion beside units: Walmart’s item performance per item, Shopify’s sessions, and Amazon’s and eBay’s traffic as each channel’s access allows. Seen and not bought is a content or price finding; not seen is a listing finding, and a rule flags a best seller whose visits fell.
Frequently asked questions
How the Advisor finds growth in a jewelry seller’s own sales, returns, stock and books. If your question isn’t here, get in touch.
Does the Advisor compare me with other sellers?
Where does the data come from?
Does the Advisor change anything on its own?
Will it tell me to delete my slow movers?
Does it know the jewelry selling seasons?
Can I ask the Advisor questions?
The Advisor is one of three parts with the Assistant and the AI Product Optimizer, on one credit balance.
Find What to Sell Next in Your Own Jewelry Sales
Connect your stores, read their sales history, and let the Advisor point at the opportunities and the problems.