Case study · Remodelers
Remodeler SEO case study: trust across a long sales cycle
What we did for a kitchen and bath remodeler (Minneapolis, MN), and what changed.
The outcome
Pricing ranges cited in AI Overviews for kitchen remodel cost searches
Before
The situation
A kitchen and bath remodeler in Minneapolis came to us with a customer who takes their time. Its customers research for months before they book.
That is normal for remodeling. A kitchen or bathroom is one of the larger projects a homeowner takes on, and few people hire the first company they find. They read, compare, save ideas and try to work out what the project will cost long before they ask anyone for a quote.
Before
The problem
A long sales cycle changes what a remodeler's website has to do. It is not enough to show up once. The company needs to be useful at each stage of the research, so that when the homeowner is finally ready, it is already the name they trust.
Cost is the first question most homeowners have, and it is the one many remodelers avoid on their sites. A buyer researching for months wants prices before calling. If a site does not give them a sense of the range, they go looking for one somewhere else, and they may find a competitor that answers it.
The question of cost is also one people now put to AI tools. Google's AI Overviews answer questions like what a kitchen remodel costs in Minneapolis by drawing on pages that state the answer clearly. A site that keeps its pricing vague gives those answers nothing to cite.
The work
What we did
Step 01
Wrote cost guides.
The guides answer the question homeowners ask first: what will this cost? Giving honest ranges early builds trust, filters in people whose budget fits the work and brings the remodeler into the research at its very start, when homeowners are searching for prices.
Step 02
Wrote case studies of the company's projects.
A homeowner researching for months wants proof that a company has done work like theirs and done it well. Case studies show real projects from start to finish and give the homeowner something to come back to as they compare options. Over a long search, the company a homeowner keeps returning to is often the one they call.
Step 03
Built neighborhood pages.
People often think of their home in terms of their neighborhood, and the homes in a neighborhood share a lot: age, style and the kinds of updates they tend to need. Neighborhood pages give Google a page to show for searches in each area and show the homeowner the company knows where they live.
Step 04
Added structured cost data and FAQ schema.
Schema is structured data that states facts in a format machines read directly. Marking up the cost ranges and the common questions makes them clear and easy for Google to use when it builds an answer, instead of leaving it to guess from the page.
After
The results
The cost guides, case studies and neighborhood pages built trust with homeowners across the long sales cycle. Instead of meeting a buyer once, the company now has something useful to offer at each stage, from the first search for prices to the final comparison before booking.
The structured cost data and FAQ schema also earned the company a place in AI search. Its pricing ranges are cited in Google AI Overviews for searches like kitchen remodel cost in Minneapolis, which reaches homeowners at the very start of their research. Out of respect for the company's privacy, we do not publish its name or anything that would identify it.
The outcome
Pricing ranges cited in AI Overviews for kitchen remodel cost searches
Next step
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