Example prompts

Ask in plain language. Your AI app picks the FranchiseSEE tools itself; you never need to name one. The MCP tool reference lists every tool, if you want to see what's behind an answer.

Your brand's own names work: "the North region", "our Express stores", "Store 1042". The app learns them from FranchiseSEE before it starts.

Sales and performance#

How did net sales trend week by week across our stores from January through March?

Give me a full scorecard for Downtown Austin last month compared with the month before.

Rank our stores on net sales for last week, with the change from the week before.

Compare Downtown Austin, Round Rock and Store 1042 on net sales, labor percentage and score for last week.

How does labor percentage compare across our regions last month?

How do I compare? (franchisees)#

A franchisee's app never names another store, but it can place you against the network or a peer group. See Franchisee accounts.

How does my store stack up against the rest of the brand on net sales this month? How many stores are up and how many are down?

How do my sales compare with the top quarter of stores in my format?

Show my weekly sales next to the average store in my district since June.

If a comparison comes back withheld, the group is too small to show without revealing a store; choose a larger one, such as your state or the whole brand.

Labor#

Build a labor dashboard for the Northeast region for the last 30 days.

Which stores ran the most overtime last week?

Menu and checks#

What were our 15 best sellers last month, and what share of checks included each one?

What sells best at lunch at Downtown Austin?

How is the Chicken Burrito Bowl trending, and which stores under-sell it?

What do guests add to the Chicken Burrito Bowl most often?

Which items grew or dropped off compared with last year?

What's our average check, and how many items are on a typical check?

How are guests paying: cash, card or delivery apps?

What's our sales split by product category, by order channel and by daypart?

Scores, ratings and audits#

Downtown Austin's score dropped this month. Which metrics are dragging it down?

The answer breaks the SEEScore into the metrics behind it, with each one's weight and gap.

How are our review ratings and audit results looking this quarter?

Goals, competitions, risk and insights#

Are we on pace for this period's sales goal? Which stores are behind?

Where do our stores stand in the current competition?

Which stores have discount or $0-check flags open right now, and why?

Show me any anomaly alerts for Downtown Austin that haven't been delivered yet.

Managing locations and users#

These need the admin server: an HQ API token with write permissions, and the matching account permission.

Create a location called "Downtown Express" at 123 Main St, Springfield, IL 62701. Put it in the Central district and classify it as Express.

Move Round Rock from its current region to the South region.

Here's a CSV of locations and their new regions. Update them all.

The app checks every row and reports success or failure for each. Names, external ids and UUIDs all work.

Give alice@example.com and bob@example.com access to the West Coast location group, and add East Coast for Bob.

Groups are added; existing ones are kept.

Replace all of john@example.com's location groups with just West Region and East Region.

This replaces every group. A user has either one direct location or location groups, never both; see User access model.

Guided prompts#

The reporting server includes two guided prompts that walk your AI app through a multi-step analysis. Apps that support MCP prompts list them in their prompt or slash-command menu.

Referring to stores, districts and users#

Every tool accepts more than one kind of identifier: