Selling home and field service company data for AI

A field service company makes thousands of small, skilled decisions every week. A customer calls about a noise in the furnace. A CSR books the job, a dispatcher picks the right tech, the tech diagnoses the problem, presents options, makes a repair or quotes a replacement, and the office follows up with an invoice and a maintenance reminder. Each job is recorded in a field service management system, often with notes, photos and a timeline.

For HVAC, plumbing, electrical, pest control, landscaping, roofing, garage door, pool and appliance repair companies with years of history, that record shows how skilled trade work gets scheduled, diagnosed, sold and completed. AI labs are interested because almost none of it is on the public internet.

Why field service data is valuable

• Diagnosis: symptom reported, questions asked, what the tech found, what fixed it
• Scheduling and dispatch: matching skills, locations, urgency and capacity in real time
• Customer communication: booking calls, confirmations, delays, estimates and follow-ups
• Option presentation: how techs present repair vs. replace choices and good-better-best options
• Recurring service: maintenance agreements, seasonal demand and renewals
• Exceptions: callbacks, warranty claims, parts delays, rescheduling and complaints

Which records matter most

Job and work order history

Job types, descriptions, tech notes, diagnoses, parts and materials used, time on site, outcomes and callbacks. Field service platforms such as ServiceTitan, Housecall Pro, Jobber, FieldEdge, Service Fusion, Workiz and others generally offer reports, exports or API access, depending on your plan.

Dispatch and scheduling

Booking source, requested windows, assigned techs, reschedules, travel time and emergency calls. This shows how capacity gets managed.

Estimates and sales

Estimates, options presented, which option was chosen, and follow-up on unsold estimates. Your pricebook structure is interesting too, though you may choose to generalize prices.

Call and message records

Call notes, booking scripts and, if you record calls, transcripts. Call recordings involve the most care: they contain customers' voices and personal details, and call recording consent laws vary by state. Many companies exclude raw audio and consider only de-identified transcripts, if anything.

Procedures and training

Booking scripts, dispatch rules, tech training material, diagnostic checklists, safety programs and maintenance agreement procedures. These are often among the cleanest, least sensitive records.

What to exclude or handle carefully

Customer personal information

Customer names, phone numbers, emails and especially home addresses. Service addresses tied to job details (an elderly customer living alone, a vacant home, access codes or "key under the mat" notes) are sensitive. Exclude access instructions, gate codes, alarm codes and lockbox details entirely.

Payment information

Card details and financing applications should stay out. If your platform stores card data with a processor, it shouldn't be in exports at all, but scan free-text notes anyway.

Photos and videos

Job photos can show people, house numbers, license plates, family photos and the inside of homes. Exclude them unless they've been reviewed or you're confident they show only equipment.

Technician personal data

Tech names, GPS and vehicle tracking history, performance and pay details, and HR records. GPS data in particular shows where individual employees were throughout the day. Exclude or aggregate it heavily.

Commercial and franchise restrictions

Commercial customer contracts, home warranty company agreements and franchise agreements may restrict use of customer or system data. If you're a franchisee, check whether the franchisor owns or controls the data in your field service system.

This isn't legal advice. Have counsel review your privacy policy, contracts and the proposed scope.

De-identification for field service

1. Replace customers and techs with consistent codes ("Customer 5521", "Tech 9")
2. Generalize addresses to city, ZIP3 or region
3. Remove contact details, access notes and codes from all free text
4. Remove equipment serial numbers, which can tie back to a specific home through warranty registrations
5. Generalize dates where exact timing could identify a job
6. Review notes by hand, since techs often write personal details into job notes

The workflow stays clear: "Customer 5521 called about no heat; booked for same-day; Tech 9 diagnosed a failed igniter, presented repair and replacement options, customer chose repair; follow-up maintenance agreement sold." See our de-identification guide.

What affects the value

• Years of job history in a consistent platform
• Note quality: detailed tech and CSR notes explain the reasoning
• Trade mix: multiple trades and residential plus commercial work add variety
• Connected sources: job history plus procedures plus internal chat shows the full operation
• Exclusions: excluding photos and call audio reduces volume but makes approval far easier

Offers vary with these factors. See how much is my company's data worth?

Who is a good fit

• Field service companies that have used one field service platform for several years
• Multi-trade or multi-location operators with documented dispatch and booking processes
• Companies with written training, diagnostic checklists and pricebooks
• Companies comfortable keeping customer contact details, photos and call audio out of scope

Getting started

To get an offer, share rough estimates: your trades, which field service platform and other systems you use, roughly how many jobs per year and years of history, headcount and years in business. No exports are needed at this stage.

DataOffer reviews field service datasets case by case, helps you scope around customers and technicians, handles packaging and de-identification (or supports your team), and brings you competing offers. There's no upfront cost, and nothing is shared until you approve the buyer, price and terms.

This guide is general information, not legal, tax or financial advice. Figures and ranges are illustrative; talk to qualified advisors about your situation.