Documentation

get_opportunity_sizing

Ranks the store's revenue leaks in currency, each with the arithmetic that produced the number and a confidence grade.

When to use it

Early in any engagement, and again whenever you need to decide what to work on. Use its ranking to order the investigation — it is the difference between a list of observations and a prioritised plan.

Ask for it like this

You do not name the tool. These are questions that make an assistant reach for it:

Where is my single biggest leak, and what does it cost per day?
Rank everything wrong with my store by how much money it costs.

How to read the result

  • Three estimators feed it: segments converting significantly below the rest of the store, funnel steps below conservative DTC benchmarks, and demand hitting out-of-stock products.
  • Every estimate is deliberately conservative. Segment gaps are sized at closing half the gap, benchmark gaps at half the distance to typical.
  • confidence is proven, probable or hypothesis. Hypothesis-grade items are benchmark-derived — verify them with a drill-down tool before spending against them.

What will make you wrong

Caveats

  • Do not sum overlapping items. One root cause can surface in more than one estimator.
  • Sizing is built on gross pixel revenue. Discount by the store's return rate before recommending investment.

Parameters

This tool takes no parameters of its own.

Shared parameters it accepts

Documented in full on the tool reference index.

Date window — defaults to the last 30 days.

dateFrom
stringdefault: 30 days ago
Start of the window, YYYY-MM-DD. Inclusive.
dateTo
stringdefault: today
End of the window, YYYY-MM-DD. Inclusive.

Every tool also accepts merchantId, which resolves from your connection. You never pass it.

What comes back

JSON. These are the top-level keys; date-scoped tools additionally carry a _meta block with the server date and the data coverage envelope.

currency
The store's reporting currency. Every money field below is in it.
store
Sessions, orders, revenue, AOV and conversion rate for the window.
opportunities
Ranked leaks, each with monthlyValue, the arithmetic string, a confidence grade and a next step.
methodology
How each estimator was built, and what it deliberately leaves out.

Pairs with