How to Use AI Mode’s Follow-Up Questions to Create Non-Commodity Local Service Content
Google tells businesses to publish unique, non-commodity content, but that advice leaves marketers and the brand with a harder question: What information should a local service page provide that is genuinely useful and unavailable elsewhere?
Google AI Mode’s follow up prompts can help uncover the answer. When a user asks for a local service provider, AI Mode often asks follow-up questions about the problem, urgency, service type, cost, or other details it needs to refine its response. Those questions reveal the decision variables that a generic service page may be missing.
In this article, I use a plumber’s thin water heater repair page in Champaign, Illinois, to demonstrate how follow up prompts can help you generate content ideas. By testing AI Mode’s prompts in separate sessions and recording how its answers, recommended businesses, and cited sources change, marketers can identify the local knowledge Google needs and turn it into specific, non-commodity service-page content.
Follow Up Questions In AI Search Reveal Non-Commodity Content Gaps
Most local service pages compete on information Google already owns. Star rating, review count, hours, address, and phone number are already in your Google Business Profile. A page that opens with “highly rated and available 24/7” gives an AI model nothing new to cite.
Non-commodity data provides specific knowledge, experience or context that cannot be reproduced by simply summarizing existing service pages. For a plumbing company, that might include diagnostic costs, what changes a quote, what technicians commonly find after opening a wall, how local water conditions affect their recommendations, and how local permit requirements apply to the work they perform.
An AI model may infer that a plumbing repair requires a permit, but it cannot know that a particular city charges an exact $85 fee or requires a thermal expansion tank without finding supporting information. When Google generates a detailed answer for a local query, pages containing specific, relevant, and verifiable facts are stronger source candidates than pages containing generic claims. Publishing those facts gives Google a locally relevant primary source it can retrieve and cite.
Traditional keyword thinking starts with a phrase and asks where to place it on the page. That worked when search returned links and the user did the reading. In an AI generated answer, the original query is only the starting point. The model searches related questions, gathers sources, and keeps passages containing facts worth quoting.
A page built around “water heater repair Champaign” may repeat that phrase several times without answering anything. A page that publishes permit requirements, repair-versus-replace thresholds, local installation costs, and diagnostic fees gives the model information it cannot get from your Google Business Profile or other citation.
Replace “What do I want to rank for?” with “What does the model need to know that only this business can tell it?”
Step 1: Audit what’s actually on the page
The water heater page I audited had two sentences of copy duplicated back to back. It said hot water matters and promised an honest opinion and fast service. Three testimonials followed, but none discussed water heaters.
The homepage named the service area, said how long the company had operated, noted that the team was licensed and insured, and offered a free quote. The service page still lacked the details a homeowner or AI answer would need: fuel types, tank versus tankless, repair thresholds, prices, permit requirements, warranties, brands, and expected job time.
Step 2: Open AI Mode
Run the search in Google and select the AI Mode tab. Keep the city in the query so the answer has a reason to look for local details. Use a signed-out, fresh window for each independent query. AI Mode carries context forward, so a second query in the same conversation is a follow-up, not a clean test.
Step 3: Run the head query and log the clarifying questions
Start with a sentence a customer might actually type:
“Find me a plumber in Champaign IL who can fix my water heater.”
Figure 1. The exact head query returned a map and local recommendations built largely from commodity listing data.
The answer returned a map and local businesses with ratings, review counts, hours, addresses, phone numbers, and websites.
The useful part came at the end. AI Mode asked whether the heater was gas or electric, whether it was leaking or not producing hot water, and whether the customer needed emergency service or a later appointment.
Figure 2. the fuel-type and symptom questions. AI Mode follow-up wording varies by session; the original test also asked about urgency.
Those questions expose the variables Google cannot resolve from listing data: fuel type, symptom, and urgency. The company whose page I audited did not appear in the original generated answer.
Step 4: Answer each branch and log what changes
Answer each follow up question in a fresh session. Record which businesses appear, how the descriptions change, what facts get cited, and where the sources come from.
Branch A: the symptom
Figure 3. The repair-versus-replace branch stopped behaving like a directory and opened with a direct recommendation based on age, leak location, and expected tank life.
I searched: “My water heater is 12 years old and leaking from the bottom. Should I repair or replace it in Champaign IL?”
AI Mode stopped behaving like a directory. It recommended replacement, explained that a leak at the base of an older tank can signal internal corrosion, and added immediate safety steps. In the original test, it also generated a “Local Regulations & Requirements in Champaign, IL” section covering the plumbing permit, thermal expansion tanks for closed water systems, and T&P relief-valve discharge routing.
Google produced local code guidance without citing a Champaign plumbing company as the source. That suggests Google either could not find or did not select a sufficiently relevant local plumber page for the answer.
Branch B: urgency plus symptom
Figure 4. The no-hot-water query surfaced a different set of Champaign businesses.
I searched: “No hot water at all in my house Champaign IL plumber.”
A different group of businesses appeared. One competitor’s published diagnostic fee became a differentiator in the generated answer. The troubleshooting section appeared after the business cards and relied partly on a YouTube video from outside the market.
The audited company appeared only inside a collapsed related-results grid rather than in the generated recommendation.
Branch C: research intent
Figure 5. The research-intent query produced a full cost comparison without a local map or local plumber cards, leaving the answer to nonlocal publishers.
I searched: “Tankless vs tank water heater replacement cost Champaign IL.”
The answer contained a full cost comparison, infrastructure upgrade estimates, and a local point about water conditions affecting tankless maintenance. It showed no local map or plumber cards.
Feature
Tank Water Heater
Tankless Water Heater
Upfront Cost (Installed)
$1,800 – $2,500
$4,500 – $7,000
Lifespan
8 – 12 Years
15 – 20+ Years
Annual Energy Savings
Baseline cost
$100 – $200 saved per year
Champaign Winter Sizing
Standard (40–50 Gal)
Must upsize due to freezing groundwater
Estimated Payback Period
Immediate savings upfront
12 – 15 years
Its sources included national publishers, YouTube, and businesses outside Champaign. When AI Mode has to leave the market for local cost guidance, the local answer is missing. That gap is the content opportunity.
Step 5: Log the exact language, not just the winners
AI Mode changes how it describes a business after the user adds detail. A company can win a vague query on general authority and disappear when the question becomes specific.
Record the model’s vocabulary: leak isolation, permit filing, thermal expansion tank, T&P relief valve, pilot-light failure, tank, and tankless. These terms are useful because they identify the concepts the model is trying to match.
Do not add terminology merely to include a phrase. Publish the specific fact behind it. If a company handles permit filings, explain who pulls the permit, what it costs, and when it is required.
Step 6: Write answer-first blocks
Turn each meaningful branch into a section phrased as the customer’s question. Resolve the question in the first sentence or two, then add the supporting detail.
The model is anticipating the next questions a user may care about. In plain English, Google searches beyond the first query before building its answer. It can also retrieve one useful passage without relying on the whole page, so each section should make sense on its own.
A replacement block
Do you need a permit to replace a water heater in Champaign?
Yes. The City of Champaign requires a plumbing permit for water heater replacement, and Illinois law requires a state-licensed plumber to perform the work. The plumber typically pulls the permit, and the fee should appear on the quote. A replacement may also require a thermal expansion tank on a closed water system and a T&P relief valve with discharge piping routed safely to the floor or a drain.
Repeat that pattern for the questions uncovered in the test: when to repair or replace, what a leak at the tank base means, gas-versus-electric diagnostics, local tank-versus-tankless costs, water conditions, diagnostic fees, installed brands, job time, and labor warranty coverage.
Use real headings and tables in the page markup. Lead with the answer instead of making the reader work through an introduction before reaching it.
Step 7: Add details Google can verify
Illinois has a specific rule for plumbing advertisements. Under 225 ILCS 320/5, plumbing advertisers must include the license number in the advertisement and display it at the business and on vehicles. The Illinois Department of Public Health enforces the Plumbing License Law.
The audited site said the team was licensed, bonded, and insured but did not publish a license number. Adding the number, licensing body, and state lookup link would improve compliance and give readers and AI a credential they can verify.
Specific, checkable details separate a real operator from a generic lead-generation page. Publish the credential your state requires rather than relying on “fully licensed” as a marketing claim.
Step 8: Know where the line is
Do not create a separate page for every follow-up phrasing. Google’s guidance for AI features warns against producing pages for search variations primarily to influence rankings or generated responses.
Use a separate page only when the answer is genuinely different. Otherwise, cover related questions as self-contained sections on the same service page.
The page AI search still needs
The opportunity is not to publish more generic service pages. It is to become the best local source for facts a business profile cannot supply: fees, diagnostic thresholds, permit requirements, code triggers, process details, warranties, and local conditions.
In this test, AI Mode left Champaign for answers and filled the gaps with non-local sources and its own synthesis. The local expertise had not disappeared. It was trapped in technicians’ heads instead of published in a form the model could retrieve.
Interview the people doing the work. Record the questions customers ask before they book, during the job, and after the invoice arrives. Publish the answers as short, self-contained sections supported by real numbers and verifiable local details.
The service pages that win in AI search will not be the ones that say “trusted, affordable, and available 24/7”. They will be the ones AI can quote when a homeowner asks a specific question no other citation can answer.
Before writing another generic service page, run one head query and three follow-ups. If AI Mode has to leave your market to answer the follow-up questions, you have found the content worth publishing.
