Key takeaways
- Each location's quote must use that location's price book, service list and company name.
- Write pricing rules and collect past quotes and invoices before you choose a tool.
- Let AI answer published prices on its own, and send custom or high-value quotes to a manager.
- Report open quotes by location every week and follow up on a schedule.
AI estimates for a multi-location franchise work when each location's prices and rules are written down. For home-service brands, AI can draft a quote from the customer's photos for a manager to approve. For storefront brands, the same idea becomes instant answers on packages, prices and open times at the nearest location.
How photo quoting works
Photo quoting works in three moves: the customer sends photos or a short description, the AI matches what it sees to that location's pricing rules, and a person approves the draft before it goes out. In a franchise group there is a step before all three. The request has to reach the location that serves the customer's ZIP code, because that location's price book is the one that applies.
How much of this fits depends on what your brand sells:
| What your locations sell | What AI quoting looks like | The human step |
|---|---|---|
| Home services priced by scope, such as cleaning, painting or hauling | A quote range drafted from photos or a short video | A manager approves before it is sent |
| Packages and memberships, such as fitness, tutoring or pet care | Instant answers on package prices, trial offers and open times at the nearest location | Staff confirm anything outside the published list |
| Large or technical jobs priced on site | AI books the on-site estimate and prepares a scope summary from the photos | The estimator quotes |
| Food and retail | Not a quoting job. AI answers questions about catering orders, stock and hours | Staff handle custom orders |
The flow for a home-service location runs like this: the request comes in from the website or a form, the CRM assigns it by ZIP code, the AI drafts a range from the photos and the location's rules, the manager approves it in the CRM, and the customer gets it with the location's name and a booking link. Done well, that takes minutes instead of a next-day callback.
How photo quoting works
- The customer sends photos From a text or a form
- AI drafts the quote From your price book and rules
- A person reviews it Nothing is sent unchecked
- The customer receives it With a way to book
- Follow up open quotes Until a yes or a no
What you need first
- A price book for each location. The same service can cost more where labor or rent runs higher. Depending on your system, prices may be set by the brand or by each location. Either way, write them as rules the AI can follow: base prices, size tiers, add-ons and minimums.
- Past quotes and final invoices. Collect a few months for each location. They are the test set for accuracy before any customer sees an AI draft.
- Each location's service list. Record what every location can and cannot do, so the AI never quotes a service a location does not offer.
- Approval rules. Decide which answers can go out on their own, such as published package prices, and which need a manager, such as anything custom, unusual or above a set value.
- A quote template per location. It should show the location's own company name and any notice your agreement requires, such as "independently owned and operated".
- Photo instructions for customers. A short note on which angles and how many photos you need cuts back-and-forth.
- One place to send and track quotes. The CRM or franchise platform your managers already open every day, with a status on every quote.
Accuracy and human review
Accuracy comes from rules and review, not from the AI. Before launch, run last month's requests through the tool and compare each draft with what the location actually quoted and billed. Fix the rules where the drafts drift, and test again.
After launch, track two numbers for each location: how far approved quotes moved from the AI draft, and how long approval took. A location where managers rewrite most drafts has a rules problem. A location where approval takes a day has a staffing problem.
Two franchise-specific risks deserve a rule of their own:
- Price leakage between locations. A tool trained on the whole group's quotes can drift toward another location's prices. Keep each location's rules separate and check drafts against that location's invoices.
- Promises a photo cannot support. Quote ranges, not fixed prices, wherever hidden conditions can change the job, and confirm the final price on site.
Following up open quotes
Follow up on a schedule set for each location, and review the open list every week. Quotes that nobody follows up are the quietest leak in a franchise group, because each location assumes someone else is tracking them.
- Same day: a text that the quote is ready, with the booking link, if the customer agreed to texts.
- Day two: a call from the location to answer questions.
- Day five: an email that restates the quote and what is included.
- Day ten: a last check-in, then close the quote as lost with a reason.
Every follow-up text needs consent and must honor STOP (TCPA rules, CTIA messaging principles). Each week, each location should see its open quotes by count, value and age. Where the brand sells recurring service, a won quote should start the repeat schedule at once.
Quoting works best next to online booking. The follow-up steps can run inside your marketing automation.
How VETS Growth Marketing helps
We write each location's pricing rules, test AI drafts against your past invoices, connect quoting to your CRM with a manager approval step, and set up the open-quote follow-up. Everything stays in your company's accounts. The build is a project with a finish date, and we report quote turnaround, quotes won and booked new customers by location. Book a growth consultation and we will look at how fast your locations quote today and what that delay costs.
Sources
- 47 CFR 64.1200: Delivery restrictions (TCPA rules), Electronic Code of Federal Regulations
- Messaging Principles and Best Practices, CTIA