AI can help plan a website, but only when the prompt gives it enough context to understand the business, customers, offers, proof, geography, and conversion goals. A generic prompt produces a generic sitemap. A strategic prompt forces the model to justify why each recommended page deserves to exist.
Most website prompts provide only two inputs:
Then the model returns Home, About, Services, Contact, Testimonials, FAQ, Blog, and a long list of service pages.
That can be a useful brainstorm, but it is not a strategy.
The model still does not know:
Without that context, AI can confidently recommend pages you should never build.
Before you use the prompt below, keep one rule in front of the model:
A page has to earn its existence. The full three-part decision framework is explained in what pages a service-business website should have.
A proposed page should normally have exactly three things:
If two pages would target the same person, answer the same question, use the same proof, and lead to the same action, tell the AI to consider combining them.
That one instruction prevents a great deal of AI-generated website bloat.
Copy the prompt below into ChatGPT and replace the bracketed fields with your business information.
You are helping me plan the information architecture for a business website. Your job is not to maximize the number of pages. Your job is to create the smallest useful website architecture that completely supports the real customer journey, important search intents, proof requirements, and conversion paths.
Business: [company name]
What we sell: [services/products]
Highest-priority services or offers: [list]
Customers we want: [audiences / industries / customer types]
Customers or jobs we do NOT want: [list exclusions if any]
Geography: [office locations, service areas, regional/national scope]
Primary conversion actions: [call, book, request quote, buy, visit, schedule assessment, etc.]
Common questions before purchase: [list]
Common objections or decision barriers: [price, timing, trust, financing, risk, compatibility, availability, etc.]
Proof we have: [reviews, certifications, case studies, photos, awards, results, warranties, team expertise, project examples]
Important business policies or facts: [pricing model, response time, warranty, financing, eligibility, scheduling, service limitations]
Existing pages we must preserve: [paste URLs/titles if this is a redesign]
Now build a recommended sitemap using these rules:
- Give every proposed page one primary customer intent or query family.
- A page must earn its existence through distinct intent + distinct answer + distinct proof/value.
- Do not create separate pages for keyword variations that would produce substantially the same content.
- Do not create location pages simply because city keywords exist. Recommend a location page only when we can provide genuinely useful local information or the location represents a real branch, market, service difference, proof set, or buying context.
- Identify where one hub page should organize several deeper pages.
- Separate commercial pages from educational/supporting content.
- Include proof and decision-support pages where they reduce buyer friction.
- For each proposed page, give: page purpose, primary audience, primary intent, key questions to answer, proof needed, primary CTA, and any page it may overlap with.
- Flag any proposed pages that should probably be combined.
- Identify important information gaps where I need to gather facts before the page can be written.
- Do not invent customer results, statistics, prices, credentials, warranties, service areas, or business facts.
- End with a three-level priority plan: Launch Now, Build Next, Build Only If Evidence Supports It.
Before giving the sitemap, summarize the business and customer journey you inferred from my inputs. If a missing fact would materially change the architecture, list it as an assumption instead of inventing it.
That prompt is intentionally different from “Give me the must-have pages.”
It forces the model to reason about architecture.
Illustration date: September 21, 2026
Model/version: GPT-5.6 Sol
Test status: One illustrative run against a fictional service business. This is not performance proof, benchmark testing, or evidence that every run will produce the same architecture.
For this single illustration, the prompt was filled out for Peachtree Facility Care, a fictional Atlanta-area commercial cleaning company serving offices, medical practices, and light-industrial facilities. The company does not serve residential customers. Its primary conversion action is to schedule a facility walkthrough. Its proof set includes commercial references, team training, insurance documentation, before-and-after photos, and documented cleaning procedures.
The illustrative run produced this architecture:
Home — Broad company orientation, qualification, and routing.
Commercial Cleaning Services — Hub for the company’s major service categories.
Office Cleaning — Distinct intent for recurring office cleaning, with scope, scheduling, proof, and walkthrough CTA.
Medical Office Cleaning — Separate because the buyer, risk profile, proof requirements, and process differ from general office cleaning.
Light-Industrial Facility Cleaning — Separate because facility conditions, scheduling, safety expectations, and proof differ from office work.
About / Why Us — Company credibility, training, insurance, process, and commercial proof.
Service Area — Atlanta-metro coverage and operational boundaries without manufacturing one page for every city name.
Request a Facility Walkthrough — Conversion page explaining what information is collected and what happens next.
Cleaning Process and Quality Control — Worth separating if the company has enough specific procedure, inspection, and reporting detail to provide a distinct answer and meaningful proof.
Commercial Cleaning Pricing Factors — Worth building if pricing questions repeatedly block qualified prospects and the business can explain the variables without publishing misleading fixed prices.
Case Studies / Project Proof — Useful once enough approved customer examples exist.
The model did not automatically recommend city-by-city pages. It flagged location pages as conditional on real local proof, operational differences, branch/service distinctions, or enough unique local information to satisfy the three-part standard.
It also flagged Office Cleaning and a proposed Corporate Office Cleaning page as likely duplicate intent and recommended combining them unless the business could demonstrate a distinct buyer, answer, and proof set.
The useful part of this one run is not the exact sitemap. It is the behavior the prompt encouraged: group overlapping intents, require pages to earn their place, surface missing proof, and separate “launch now” needs from pages that should wait for evidence.
Suppose you enter information for an HVAC company that serves one metro area and offers repair, maintenance, system replacement, indoor-air-quality services, and commercial HVAC.
A weak AI output may recommend:
That list looks productive. It may actually create duplication.
A stronger output would first group intents.
Home — Broad company orientation and routing.
About — Trust, company story, team, credentials, and proof.
Contact / Schedule — Conversion and service-access information.
HVAC Repair — General repair intent, unless emergency service is operationally different enough to deserve its own page.
HVAC System Replacement — Different buying process, cost questions, financing, system choices, and proof.
Maintenance — Recurring-plan or preventive-service intent.
Indoor Air Quality — Different problems, products, questions, and customer needs.
Commercial HVAC — Different buyer, sales process, proof, scheduling, and service requirements.
HVAC Pricing Factors — Useful if customers repeatedly ask how repair or replacement pricing works.
Financing — Useful if financing materially affects the purchase.
Warranties / What to Expect — Could be separate or folded into service pages depending on depth.
Instead of automatically recommending 25 city pages, the model should ask whether the company has real projects, service differences, branches, local proof, or meaningful market information for those cities. Google’s spam policies are one reason not to mass-produce substantially similar city pages that function as doorway content.
That is a better output because the architecture follows the business.
This is one of the highest-value uses of AI in website planning.
Give the model your existing URL list and ask it to create an intent map.
For each URL, have it identify:
Then ask:
“Which pairs of pages appear to answer substantially the same customer need?”
Do not let the model automatically merge or redirect anything. Use the output as a diagnostic, then verify it with Search Console, analytics, backlinks, conversions, rankings, and business value before changing existing assets.
AI is good at pattern detection. It should not be given unilateral authority over URLs that may already have value.
Another strong follow-up prompt is:
For each high-priority service page, list the questions a qualified buyer is likely to ask before contacting the company. Group them into: understanding the service, price/budget, timing, trust/proof, risk, process, eligibility, alternatives, and next steps. Do not turn every question into a new page. Recommend whether each answer belongs on the service page, in an FAQ, on a separate decision-support page, or in an educational article.
That turns the model into a gap-analysis assistant.
It also protects you from a common SEO mistake: creating a new URL every time you discover a related search phrase.
Most AI-generated website plans are generic because the model is given generic inputs.
Feed it the assets that make the company specific:
Then ask where each proof asset belongs.
A website architecture should not be only a map of topics. It should also be a map of evidence.
This is one of the most overlooked inputs.
A website should not attract every possible inquiry.
If your ideal client is a commercial organization with a certain budget, service scope, geography, or level of complexity, tell the AI. If you do not serve residential customers, say so. If you do not take emergency jobs, say so. If a service is profitable only above a minimum project size, include that context where appropriate.
That can change the sitemap, the page copy, the FAQs, and the CTA.
Better architecture is not just about generating more leads. It is about helping the right people self-select.
Before you accept any output, review every factual statement.
AI may fill gaps with plausible but incorrect assumptions about:
Replace assumptions with approved information.
If the answer is not known, mark it as information to collect.
The website will eventually become a source for search engines, customers, employees, and AI assistants. Bad information becomes more expensive when it gets reused.
Before approving the sitemap, ask these questions:
If the sitemap passes that test, AI has done something useful.
ChatGPT can dramatically speed up website planning. It can organize services, expose missing questions, detect potential overlap, suggest page relationships, and turn scattered business knowledge into a coherent draft architecture.
But it still needs the right inputs and the right constraints.
The winning prompt is not the one that generates the most pages.
It is the one that helps you build a website where every important page has a reason to exist, every major customer question has a home, and every qualified visitor can find a clear path to the next decision.
Use the AI output as a planning draft, not as authority. Compare it with the service-business page-planning framework, the customer-question framework, and the One-Page SEO Clarity Test before you build. If the project needs a professional design system after the architecture is approved, see Atlanta web design services.
After AI gives you a draft architecture, compare it with the website you already have. Complete the Free Website Audit / Website Growth Assessment form and the assessment will be delivered by email. It is not instant or anonymous, and it gives you a second input before you build or remove pages. 15+ years.
After AI gives you a draft architecture, compare it with the website you already have. Complete the Free Website Audit / Website Growth Assessment form and the assessment will be delivered by email. It is not instant or anonymous, and it gives you a second input before you build or remove pages. 15+ years.
173 W. Wieuca Road Northeast #104
customersupport@advertisingbusiness.org
(770) 874-6085 
(770) 874-6085
770-874-6085