You have job-costing data but don't know which customers, services or crews make money. Short answer: use Claude (analyzes pasted job-cost tables). Free option: ChatGPT. The workflow has 3 steps and 2 copy-paste prompt(s); expect margin tables by service, customer and crew, with findings and next questions. Main caution: AI arithmetic and unit conversions can be wrong; recheck every quantity and total.
The problem
You have job-costing data but don't know which customers, services or crews make money.
Recommended tools
Claude
ChatGPTFree plan works for smaller exports.
Free; paid plans per user - see https://chatgpt.com/pricing
LMN by GranumJob costing data to analyze.
Starter $297/mo; Professional $648/mo; Enterprise contactEditorial opinion based on the vendor capabilities and prices listed in our tools directory. Not paid placements; prices as checked Oct 2026 and may change. Compare all use cases →
All tools mentioned
Step-by-step workflow
- Export job-level data: customer, service, revenue, labor hours, materials, crew.
- Ask AI for profitability by service, customer and crew.
- Check results against your own reports; look for data errors first.
Copy-paste prompts
Here is job data [paste: job, customer, service type, revenue, labor hours, labor cost, materials, crew]. Calculate gross margin by service type, by customer (top/bottom 10) and by crew. List the 5 most notable findings and the data you'd need to confirm them. Show the math.
Draft 3 options for dealing with our lowest-margin customers (reprice, change scope, or let go) and how to explain each to the customer.
What to expect
Margin tables by service, customer and crew, with findings and next questions.
Limits & safety
- AI arithmetic and unit conversions can be wrong; recheck every quantity and total.
- Missing or miscoded hours skew results; clean data first.
Source / inspired by
- Ask Lex: The best first uses for AI in a landscape business — Lex Mason, Landscape Management, Jul 2026. Lists using AI to analyze business data among good first uses. Summarized in our own words.