AI demand forecasting for dog groomers.
Built for the dog groomer who's already tried the off-the-shelf option and bounced off it.
What AI demand forecasting actually does
Forecasts that account for school holidays, NZ weather, tourist seasons, and your own promo calendar. With the right workflow automated, nine hours of admin a week could drop to about one.*
*Illustrative example only, based on 9 hours a week of admin falling to about 1 hour a week. Actual results vary by workflow and business.
Appointments, reminders and pet notes handled automatically, so nobody has to put the clippers down for the phone.
One workflow.
In production.
In weeks.
What AI demand forecasting covers
We'd call the engagement a success when dog groomers are using the system without thinking about us.
- Combines your sales history with weather, calendar, and event data
- Per-SKU and per-store forecasts, not whole-business averages
- Re-forecasts weekly as new data comes in
- Explains the why behind every number
- No annual contracts
- No AI theatre
Where dog groomers actually lose hours and dollars.
Groomers run tight appointment slots where a single no-show leaves an expensive gap in the day.
Booking confirmations and reminder texts are the simplest lever for cutting no-shows in a grooming business.
Definitely not a typical AI agency.
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
How much is the admin really costing you?
Nine hours a week of admin is 468 hours a year. That could drop to about 52.*
*Illustrative, based on 9 hours a week of admin at a typical 80% automation rate. The calculator uses your own numbers.
From one-person trades to national organisations, we find the hours :)
The questions a public sector buyer asks, answered up front: privacy impact, the NZISM, where the data lives and how an algorithm is held to account.
*Illustrative example based on nine hours a week of admin. Actual results vary by workflow and business.
Good questions, answered
What if our dog groomer doesn't have any data ready?
Most don't. Getting the data into shape - ingestion, cleaning, the lightweight contracts you need before any model is useful - is part of the engagement. For AI demand forecasting specifically, we typically run that work on Prophet, DuckDB, Claude, BigQuery, Vercel and assume messy starting conditions from day one.
How fast could we have AI demand forecasting in production?
Eight to ten weeks for most dog groomers. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.
Anyone else in this space using AI demand forecasting?
Plenty. Stockouts down 35%, overstock down 22% in the first season. The interesting question is rarely "does it work" - it's "is your team ready to use the output." That's what we'd scope on the call.
Can it keep track of ACC levies?
Yes. ACC work levies are set by the classification unit your work falls under, and self-employed people are invoiced after filing their tax return.
What does the Privacy Act 2020 mean for AI?
The same rules apply as for any system holding personal information. A breach that could cause serious harm must be reported to the Privacy Commissioner, who expects it within 72 hours.
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