What Google Ads Really Costs an Appliance Repair Business

Every owner who calls us about paid search asks a version of the same question: “What’s a customer going to cost me?” It’s the right question. The problem is that the two most common ways to answer it are both wrong, and they’re wrong in opposite directions — one inflates the market you think you’re playing in, the other inflates the budget you think you need.

So we measured one instead. We pulled an entire metro’s appliance repair demand through the Google Ads API — every phrase people actually search, the bid range on each, residential and commercial, twelve months of seasonality. Below is what the numbers say, what they cost, and the three findings that change how you’d spend the money.

The short answer on click cost

For residential appliance repair in a large US metro:

	Typical range
Average cost per click	around $7
Top-of-page bid	around $12
Commercial equipment repair	around $13 per click

The gap between those first two rows is the part owners miss. The bid is what it takes to be eligible for the top of the page. The CPC is what you actually pay, and it lands well below your maximum — because in an auction you pay what it takes to beat the advertiser under you, not the number you typed in. In our data, the realized cost came in at roughly 55–60% of the top-of-page bid.

That means quotes built on bid estimates are systematically too high. If someone tells you clicks in your market cost $12, ask whether that’s a bid or a cost.

Trap one: your keyword tool is counting the same demand four times

Keyword research tools return close variants as separate rows carrying identical volume. In our pull, “washing machine repair,” “fix washing machine,” “laundry machine repair,” “washer fixer,” “clothes washer repair,” and “repair the washing machine” all reported the same number — because they aren’t six demands, they’re one demand shown six times.

Sum the raw export and you get a market 4.3 times larger than it is. We’ve watched owners build entire business cases on that inflated number.

The fix is unglamorous: collapse rows that share identical metrics — same volume, same competition index, same bid range — into one cluster before you total anything. A metro that looked like 274,000 monthly searches came back as 63,000 after deduplication.

There’s a second contaminant in the same export. Keyword expansion pulls in adjacent industries that look related and aren’t. Our appliance repair pull dragged in air cooler and air conditioner repair — several thousand searches a month carrying bids around $72, five times the appliance repair rate. That’s HVAC economics, not appliance repair economics. Leave those phrases in your set and your whole market’s average cost per click rises by a third for no reason.

Trap two: volume times bid is not a budget

The intuitive way to size a channel is to multiply monthly searches by the cost per click. It’s wrong twice over: not every search becomes a click, and you don’t pay your maximum bid.

Run the same keyword set through the Google Ads forecast — which returns expected clicks and average CPC for a given bid — and the picture changes hard. In our metro, the volume-times-bid method predicted roughly $16,000 a month to capture a tenth of the market. The forecast said buying every available residential appliance repair click cost about $5,000 a month.

That’s not a rounding error. It’s the difference between “we can’t afford this channel” and “we can own this channel.”

One caution if you run these forecasts yourself: forecast each ad group separately and add them up, and you’ll overstate the total by about 5%. Your own keywords compete against each other in the same auction. Forecast the whole campaign at once.

The finding that actually changes the plan: brands

Here’s the number we didn’t expect. About 42% of all appliance repair searches name a brand. Not “washer repair” — “Whirlpool washer repair,” “Samsung refrigerator repair,” “Maytag washer repair,” “LG dryer repair.”

In the metro we measured, brand-qualified searches ran roughly 23,000 a month. Nearly every appliance repair site we look at handles that with one page listing fifty brand logos.

This is the most qualified traffic in the category, and it’s worth understanding why. Someone searching “washer repair” may be comparison shopping, may be a renter, may be three weeks from deciding. Someone searching “Samsung washer repair” is standing in front of a broken Samsung washer. They know the brand because they’re looking at it. The intent gap between those two searches is enormous, and the bid difference is almost nothing — brand-qualified phrases cost about the same per click as generic ones.

Demand concentrates fast, too. Five manufacturers — Whirlpool, Samsung, GE, LG, Maytag — carry the large majority of it, and the top twenty brand-and-appliance combinations cover about 86% of the brand market. You don’t need fifty pages. You need about twenty, and they need to say something real: the failure modes specific to that brand, the error codes a tech actually sees on the display, what gets fixed in one visit and what waits on a part.

That last part isn’t optional. Twenty near-identical pages differing only in the brand name are the fastest route to being filtered out as scaled content. If you can’t get genuine detail from your technicians for twenty combinations, build eight good pages instead. Eight pages with real diagnostic content outperform twenty templated ones, and they don’t put the rest of the domain at risk.

Nobody types your city name

We expected geography to be an axis. It isn’t — at least not in search text.

Across the entire metro dataset, exactly one phrase contained a suburb name, at 30 searches a month. Combinations of city and brand — the “LG refrigerator repair in Matthews” pattern that programmatic page builders love — returned zero measurable volume.

People express location two other ways: with “near me” (about 15% of the market) and by simply being somewhere, which Google handles through their device location. They don’t type the suburb.

This has a direct consequence. A stack of eighteen suburb pages built from one template with the city name swapped in isn’t capturing demand, because the demand isn’t phrased that way. Those pages have a role — confirming your service area to a visitor already on the site, and supporting local pack relevance — but that role needs six or eight substantial pages, not eighteen interchangeable ones.

If you’re wondering whether more page permutations at least help you surface in AI answers: retrieval works on passages, not URLs. One page that clearly states which brands you service and which areas you cover is retrievable for every combination of the two. Three hundred near-duplicate pages get collapsed to one at retrieval and drag your classic rankings down — which matters, because AI answer engines read from those same search indexes.

Commercial equipment: real, but small

We ran the same analysis on commercial kitchen and refrigeration repair — the restaurant and light-industrial side.

The clicks cost about double residential, near $13. The market is roughly one-sixteenth the size. In the metro we measured, total available commercial spend came to a few hundred dollars a month.

And it’s almost entirely refrigeration. Walk-in coolers, freezers, commercial refrigeration — that’s where the searches are. Commercial cooking equipment, warewashing, and laundry each registered ten to thirty searches a month, which is statistically nothing.

Watch the intent bleed here too. “Ice machine repair” and “espresso machine repair” look commercial and carry heavy volume, but they mix residential intent — home ice makers, home espresso machines — with the commercial kind. Bid levels give it away: the phrases with genuinely commercial intent price at $13 and up, while the ambiguous ones price near $1.

None of this makes commercial a bad idea. It makes it a bad standalone campaign. As an ad group and landing page attached to a residential build, where a walk-in cooler call carries a multiple of a home washer ticket, the economics can be better than residential. Just don’t plan for volume that isn’t there.

Demand peaks in December, not July

Twelve months of data show a pattern most owners guess backwards: the peak is December, the trough is June, and the spread is about 1.7x.

The summer dip is counterintuitive — you’d expect heat to kill refrigerators. It doesn’t show up that way in search. What does show up is the holiday load: more cooking, more laundry, more guests, more machines running hard, and less tolerance for a broken one.

For budget pacing, that’s a straightforward instruction. Trim June and July. Hold November through March.

What we’d do with $5,000 a month

Putting it together for a residential appliance repair business in a metro this size:

• Start with brand-qualified campaigns. Highest intent, same click cost as generic, and almost nobody is competing properly for them.
• Target the metro, not the city. City-limits targeting in our market covered a third of the real demand. Service businesses drive to the suburbs; your targeting should follow.
• Don’t split budget by appliance type. Bids across washers, dryers, refrigerators, and dishwashers land within a couple of dollars of each other. Volume and job value should decide your priorities, not click cost.
• Expect the full channel to top out around $5,000/mo. That’s the ceiling for buying every available click, not a recommendation. Most businesses should start at a fraction and scale on measured cost per job.

The number we can’t give you

There’s one figure everyone wants that no keyword tool will produce: conversion rate.

We checked. Google’s forecast API does return a conversions figure, but it’s modeled from the requesting account’s own history, not the market. We ran the identical keyword set from two different accounts and got conversion rates 2.2 times apart — while the click forecasts came back within 3% of each other. Clicks are market data. Conversions are your data.

Which means anyone quoting you an “industry standard conversion rate” for appliance repair is quoting a number that doesn’t exist in any dataset Google publishes. Your conversion rate comes from your own campaigns, your own phone handling, and your own site — and until you’ve run traffic, it’s an assumption, not a benchmark.

That’s the honest limit of research. Everything above tells you what the traffic costs and where it is. What it turns into is something you find out by buying some.