Skip to content
Appath AI · Advisor

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.

Insights · Opportunities Example
  • Missing from a store
    Birthstone stud earrings, 14K yellow gold
    Sold 41 on Amazon in 90 days · not listed on eBay
    Preview on eBay →
  • Out of stock at the supplier
    Heart pendant, rose gold, 18 in.
    A best seller last Valentine’s · supplier stock 0
    See alternatives →
  • Margin left on one channel
    Diamond eternity band, 1 ct. t.w.
    Held to MAP on Walmart · margin room above it
    Check the rule →
Each figure with its period, its stores and its as-of time
Sales history

Every channel’s sales, together, as far back as each 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.

Your stores are read together: a ring selling on Walmart can be the reason to list it on eBay. A product removed from your catalog keeps its sales history.

Best sellers and slow movers

Per store or across stores, over 30, 90 and 365 days, each figure stamped with its period and as-of time.

Sold before, not lately
The short list a seller reads.
No sale on record
The long one, paged, never a bulk delete.

A listing under 180 days old is in neither list.

Insights

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.

Opportunities

Every rule’s findings, each with its evidence, its worth as an estimate, and the step that fixes it.

Products

Best sellers and slow movers by 30, 90 and 365 days, per store or across stores, with high returns beside them.

Stores

Every store in one table: units and sales per period, the last sale, and how much history Appath holds.

Returns

Returned units by store, product and the channel’s reason, beside what sold.

Trends

Units and sales by month and year, by kind of item and by store, and each season against last year’s.

Trends by the kind of item
  • Product type
  • Metal
  • Stone
  • Price band
  • Brand
  • Supplier
  • Store

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.

The jewelry selling calendar

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, and the kinds of item that sold with no live listing now.

  1. Valentine’s
    Jan 25 to Feb 14
  2. Tax refunds
    Feb 1 to Apr 15
  3. Mother’s Day
    The three weeks to the day
  4. Weddings
    May to September
  5. Father’s Day
    The three weeks to the day
  6. Holiday
    Thanksgiving week to Dec 24, with Black Friday to Cyber Monday marked
  7. Engagement
    Nov 20 to Feb 14
The rules

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 best seller missing from one of your stores
  • 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
  • A price held to MAP that leaves margin on one channel only
  • 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 best seller missing from a store opens the listing preview, a MAP finding opens your pricing rule, a kind of item that sold with no live listing opens Add from suppliers in the catalog, and returns are read from every channel’s own reasons.

Margin per product

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.

Traffic, where the channel provides 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.

Common questions

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?
No, never. The Advisor reads your own stores’ sales, returns, listings, stock and books, and nothing else. There are no pooled benchmarks and no “sellers like you”: nothing from one seller’s account informs what another sees.
Where does the data come from?
From your own channels and from Appath. When you press Read sales history on a store, Appath reads that store’s sales back as far as the channel allows, and from then on it keeps the orders it handles. Costs and margins come from your supplier files and your books in Appath; traffic comes from the channels that provide it. Every figure names its period, its stores and its as-of time.
Does the Advisor change anything on its own?
No. Each finding opens the step that fixes it, such as a listing preview, a pricing-rule check or a supplier’s alternatives, and nothing changes until you confirm it there. The Advisor itself only reads.
Will it tell me to delete my slow movers?
No. Slow movers are a list to read, never a bulk delete. On the jewelry stores Appath was built on, few SKUs sold again the next year and most units came from items selling for the first time, so a listing with no recent sale is not a dead listing. A listing under 180 days old is not counted as a slow mover at all.
Does it know the jewelry selling seasons?
Yes. Valentine’s, tax-refund season, Mother’s Day, weddings, Father’s Day, the holidays with Black Friday to Cyber Monday marked, and engagement season are built in. Four weeks ahead of each, the Advisor names what sold in it last year and is not ready this year.
Can I ask the Advisor questions?
Ask the Assistant: it reads the same sales, returns, trends and opportunities the Advisor shows, in the same words, so “what sold last Mother’s Day that I have not listed on Walmart?” has an answer.
Part of Appath AI, in every plan

The Advisor is one of three parts with the Assistant and the AI Product Optimizer, on one credit balance.

See plans →

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.

Built for multichannel jewelry sellers on Amazon, Walmart, eBay and Shopify
Private beta · Now accepting jewelry sellers