AI and Business Decisions: What Home Service Owners Need to Know

This is Part 1 of a six-part series on using AI to make better business decisions.

AI is making a pretty big promise to business owners.

Connect it to your company data, and you can start asking questions in plain English. No digging through reports. No building another spreadsheet. No waiting for somebody to pull the numbers.

Want to know why revenue dropped last month? Ask AI.

Want to know how your CSRs are performing? Ask AI.

Want to know which technicians have the highest average tickets, which marketing sources produce your best customers, or where revenue may be six months from now? Ask AI.

That’s pretty amazing.

But somewhere along the way, we’re starting to make a dangerous jump from “AI can answer questions about my business” to “AI can tell me how to run my business.”

Those aren’t the same thing.

The Answer Is Only Part of the Job

Suppose revenue is down 8%, so you ask AI why.

It searches your data and tells you that average ticket fell 11%.

That’s useful information. But should you start working on average ticket?

Maybe.

What if average ticket fell because you ran more maintenance calls and fewer replacements? Meanwhile, your call center booking rate dropped from 78% to 64%.

Both numbers are true, but one may deserve your attention a whole lot more than the other.

That’s the problem we’re going to examine in this series.

The hard part of running a business has never been finding numbers. The hard part is knowing which numbers to trust, which questions to ask, what deserves your attention, and what you should do about it.

AI doesn’t make those problems disappear.

In some cases, it makes them easier to miss.

Five Questions Worth Asking Before You Trust the Answer

Over the next series of posts, we’re going to look at AI from the point of view of a home service business owner rather than someone trying to sell you AI.

We’ll start with “Your Booking Rate May Not Mean What You Think It Means.” Before AI can analyze your numbers, somebody has to decide what those numbers mean. Something as simple as booking rate gets surprisingly complicated once you decide which calls should and shouldn’t count.

Then we’ll look at “AI Can Give You a Good Answer to the Wrong Question.” Accurate information doesn’t help much when you’re working on the wrong problem.

We’ll learn why “More Numbers Do Not Always Lead to Better Decisions,” when we deal with what happens when AI finds ten things you could improve. Business owners don’t have enough time or money to fix everything, so something has to come first.

Despite appearances to the contrary, “AI Can Guess the Future. It Cannot Know the Future,” deals with forecasts. AI can help you estimate where the business is headed, but you need to understand the assumptions behind that estimate before you start spending money based on it.

Finally, a reminder: “AI Can Give Advice. You Still Have to Make the Decision” looks at the point where data and recommendations stop and your judgment begins.

This Isn’t an Argument Against AI

Quite the opposite.

Giving a business owner the ability to talk to company data could become one of the most useful things AI does.

But getting an answer quickly doesn’t make the answer useful. A confident answer doesn’t make it correct. And a correct answer doesn’t automatically tell you what to do.

The business owners who get the most from AI won’t simply ask it more questions.

They’ll get better at knowing which questions deserve to be asked.

We’ll start there with “Your Booking Rate May Not Mean What You Think It Means.”

Read Part 1: Your Booking Rate May Not Mean What You Think It Means →