Product Intelligence¶

Rank a website's products on a performance dimension: best sold on Tuesdays, most bought in the evening, highest lifetime value, best candidates for a 10% discount.

Free beta

Product Intelligence is in beta, and free while it's in beta. Expect it to move: dimensions and fields can be renamed, added or removed. Don't build anything business-critical on it without a fallback.

This tool reads the same data as the Product Intelligence API and the dashboard, so the numbers match. Where the API's productInsight query answers "what do I know about this product?", this tool answers the inverse question: "which of my products best match this criterion?".

Products need enough purchase history before Product Intelligence can score them, and those that don't have it are left out. An empty result means nothing matched; it isn't an error. The API page covers what the model needs.

Tips & tricks¶

Pick the card that matches what you're doing. Each prompt is ready to paste into your assistant.

Campaign planning

Ask by the occasion

Ask for products by the occasion you're planning for, and let the assistant pick the dimension.

Which 10 products should I promote in my newsletter this Tuesday?

Discounts

Name the offer

Discount planning works the same way. Name the discount you're considering.

Which products are the best candidates for a 15% voucher on my website?

Two dimensions

Rank on one, filter on another

Rank on one dimension and filter on another to keep the list commercially sensible.

Show the most repurchased products on my website, but only the ones that mostly sell at full price.

Reading the numbers

Look past the rank

Every result carries a 0-1 score and the raw dimensionValue behind it: for DAY_OF_WEEK, the share of a product's purchases that fall on that day. Ask for it when you need to know whether the top product is a strong signal or the best of a weak field.

Show my website's top products for Tuesday and what share of each one's purchases actually happen on Tuesdays.

Weekly planning

Plan the whole week

One call ranks one day. Your assistant is happy to make seven: ask for the whole week and it runs the ranking once per weekday and assembles the calendar.

Build me a promotion calendar for next week: for each day, the three products that sell best on that day.

Across tools

Put the winners to work

The ranked list doesn't have to stop in the chat. The same MCP server carries write tools for Pages, Recommendations and Newsletter Content, so the assistant can put the winners to work. It asks before it changes anything.

Find my ten products with the highest lifetime value and boost them to the top of my bestsellers page.

productIntelligence_getTopProducts¶

Rank a website's products on a Product Intelligence performance dimension, best first. Each result carries a 0-1 score for how well the product matches the dimension (results are ordered by it) and the product's raw dimensionValue. For DAY_OF_WEEK, that's the share of its purchases that happen on that day.

Some dimensions need extra arguments: DAY_OF_WEEK needs weekday, TIME_OF_DAY needs hourFrom and hourTo, DAY_AND_TIME_OF_DAY needs all three, and DISCOUNT needs discountFrom and discountTo. PRODUCT_LIFETIME_VALUE, RETENTION_RATE and RECURRENCE_RATE take none. Passing a dimension without its arguments returns a validation error naming what's missing. The topProducts API page documents each dimension in full, including how discount ranges round out to 10-point bands.

Name	Type	Required	Description
`websiteUuid`	string	Yes	The UUID of the customer's website in Hello Retail. Use `website_getInfo` to look up available websites, or find it in my.helloretail.com under Settings → Website Settings → Website Unique Id.
`dimension`	string	Yes	What to rank by: `DAY_OF_WEEK`, `TIME_OF_DAY`, `DAY_AND_TIME_OF_DAY`, `DISCOUNT`, `PRODUCT_LIFETIME_VALUE`, `RETENTION_RATE` or `RECURRENCE_RATE`.
`weekday`	integer	No	Day of the week to rank by, 1 for Monday through 7 for Sunday. Required by `DAY_OF_WEEK` and `DAY_AND_TIME_OF_DAY`.
`hourFrom`	integer	No	Start of the time-of-day window, 0-23 inclusive. Required by `TIME_OF_DAY` and `DAY_AND_TIME_OF_DAY`.
`hourTo`	integer	No	End of the time-of-day window, 0-23 inclusive. Required by `TIME_OF_DAY` and `DAY_AND_TIME_OF_DAY`.
`discountFrom`	integer	No	Start of the discount range, 1-100 inclusive, to rank purchase probability within. Required by `DISCOUNT`. The discount data is grouped in 10-point bands (1-10, 11-20, ...), so a range covers every band it touches. The range exactly 0-0 ranks by full-price purchases instead.
`discountTo`	integer	No	End of the discount range, 1-100 inclusive. Required by `DISCOUNT`.
`filters`	array of objects	No	Threshold conditions on product metrics, combined with AND. Per entry: `metric` (any ranking dimension, or `PRICE`), `operator` (`GT`, `GTE`, `LT` or `LTE`) and `value` are required. A parameterized metric takes the same arguments inside the filter as its dimension takes on the query (`DAY_OF_WEEK` a `weekday`, `TIME_OF_DAY` an `hourFrom`/`hourTo` window, `DISCOUNT` a `discountFrom`/`discountTo` range), and compares against the same 0-1 share the dimension reports. Products without data for a filtered metric are excluded.
`limit`	integer	No	Number of products to return, 1-100. Default 10.

Example request & response

Example requestReturns

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "productIntelligence_getTopProducts",
    "arguments": {
      "websiteUuid": "<string>",
      "dimension": "DISCOUNT",
      "discountFrom": 1,
      "discountTo": 10,
      "filters": [
        {
          "metric": "RETENTION_RATE",
          "operator": "GT",
          "value": 0.4
        }
      ],
      "limit": 3
    }
  }
}

{
  "products": [
    {
      "url": "<string>",
      "title": "<string>",
      "productNumber": "<string>",
      "price": 0.0,
      "imgUrl": "<string>",
      "score": 0.0,
      "dimensionValue": 0.0,
      "isRecurrent": true
    }
  ],
  "notice": "<string>"
}