How to Show Up in AI Chat Recommendations (Without Gaming the System)
If you’ve noticed customers asking things like “ChatGPT said you were one of the best options” or “Perplexity recommended your guide”, you’re not imagining it: AI chat tools are becoming a real discovery channel.
But they don’t “rank” content the same way Google does. They assemble answers by stitching together information they trust from across the web. That means your job isn’t only to rank a page — it’s to become a brand AI is confident naming.
Below is a practical, no-fluff playbook for small and medium businesses (especially in Australia) to increase the odds of being recommended in AI chat results.
First: What “AI chat recommendations” actually are
When someone asks an AI tool for advice — “best CRM for a real estate team under 50 staff” or “who can build Shopify email flows in Brisbane” — the model tries to produce the best answer based on:
- What it already “knows” from training data (older, broad)
- What it can retrieve via search/browsing (newer, specific)
- What it can verify across multiple sources (trust signals)
OpenAI’s ChatGPT search feature can pull in live web results and show sources, and OpenAI notes it may share “dissociated” queries with third-party search providers to generate results.
So if you want to show up, you need to be present where AI systems look: your site + trusted third-party sites + consistent brand entities across the web.
1) Build topic clusters and ultra-specific pages (stop being “generic”)
Most business websites have pages like:
- “Services”
- “SEO”
- “Web Design”
- “Digital Marketing”
Those are fine for humans. For AI, they’re often too broad to confidently match a specific question.
What to do instead: go narrower than your competitors
Create specialised pages that map to specific use cases, industries, constraints, and buyer intent. Think:
- “Email automation for NDIS providers”
- “SEO for Brisbane tradies (service-area pages + call tracking setup)”
- “Best CRM for real estate teams under 50 (AU pricing + integrations)”
- “Shopify Klaviyo setup for brands doing 1–5k orders/month”
- “B2B lead gen for engineering firms (long sales cycle)”
This is what “topic clusters” should look like in 2026:
- One core pillar page (broad but still practical)
- 8–20 supporting pages (deep, specific, bottom-of-funnel)
- Internal links that clearly show the relationships
Example cluster (for a marketing agency)
Pillar: “Email marketing for ecommerce brands”
Specialised pages:
- “Klaviyo welcome series for Shopify: templates + timing”
- “Abandoned cart flows for Australia: shipping and payment objections”
- “Email deliverability fixes for Shopify stores”
- “Post-purchase flows to lift repeat rate (30/60/90 day sequences)”
- “Best email cadence for subscription products”
The goal is to make it easy for an AI to match a user question to a page that’s obviously the right fit.
2) Target bottom-of-funnel queries (because AI is being used for purchase decisions)
AI is increasingly used late in the journey — when someone wants to compare options, validate providers, shortlist tools, or solve a problem quickly.
That’s why your content should answer questions like:
- “Which option is best for my situation?”
- “What should I avoid?”
- “How much does it cost in Australia?”
- “What does the process look like?”
- “What’s the fastest path to results?”
Bottom-of-funnel page types that work well in AI
Create pages that sound like how people actually ask AI:
- Comparison pages: “Klaviyo vs Mailchimp for Shopify (AU)”
- Alternatives pages: “Best alternatives to HubSpot for small B2B teams”
- Use-case pages: “Lead gen for allied health clinics”
- Problem-fix pages: “Why your Meta ads aren’t converting (and what to change first)”
- Pricing + scope pages: “How much does SEO cost in Australia? (with ranges + what’s included)”
Quick rule
If a page could help someone make a decision this week, it’s probably aligned with AI-driven discovery.
3) Build “authority distribution” (AI cross-references everything)
AIs don’t just take your word for it. They cross-check what you claim against what the wider web says about you.
That’s why “authority” isn’t just backlinks. It’s independent mentions, consistent information, and multiple reputable touchpoints that confirm your brand exists and does what it says.
Where authority distribution comes from
- Industry directories (reputable, not spammy)
- Professional associations and partner sites
- Guest features and quotes in industry publications
- Case studies on vendor/partner sites (e.g., Shopify Experts, HubSpot Solutions Directory)
- Podcasts, webinars, event speaker listings
- Community discussion (Reddit, forums, Slack groups, Facebook groups)
- High-quality reviews
Even Microsoft’s Bing crawler documentation is a reminder that crawling and indexing basics still matter, because many systems build on search engine infrastructure.
A practical authority checklist (SMB-friendly)
Aim for 10–30 credible mentions over the next 6–12 months:
- 5–10 directory profiles (industry relevant, fully completed)
- 3–5 guest articles or expert quotes
- 3–5 partner ecosystem listings
- 10+ customer reviews across 1–3 platforms that matter in your category
4) Format your content for AI extraction (make it easy to quote)
LLMs do well with content that is:
- Structured
- Specific
- Easy to skim
- “Atomic” (clear, standalone points)
So don’t bury the answer in storytelling.
Content formatting that helps
Use:
- Clear headings (H2/H3) that describe the answer
- Short paragraphs (2–4 lines)
- Bullets for steps, criteria, pros/cons
- Tables when comparing (pricing, features, inclusions)
- “Key takeaways” sections
- FAQs with direct answers
This isn’t just about readability — it helps retrieval systems identify the best snippet to include.
A simple “AI-friendly” page template
- 1–2 sentence summary (the direct answer)
- Who this is for
- Options and recommendations (with reasons)
- Decision criteria (what to look for)
- Steps / process
- Costs / timeframes (ranges, what changes the cost)
- FAQ
- Sources / references (where appropriate)
When your page reads like a helpful briefing note, it becomes easier to cite.
5) Leverage third-party validation (reviews and “real talk” matter)
AI systems tend to trust signals that look less like marketing. That’s why:
- Customer reviews
- User-generated discussions
- Independent comparisons
- Reddit threads and forum posts
…can carry serious weight.
This doesn’t mean you should “game” Reddit or plant fake reviews (bad idea, and it usually backfires). It means you should earn authentic validation and make it visible.
What to prioritise
- Collect reviews right after a win (project launch, results milestone, positive feedback email)
- Ask for specifics: what problem you solved, what changed, what they liked
- Spread reviews across where buyers actually look (Google Business Profile, industry platforms, software marketplaces, etc.)
- Turn testimonials into on-site proof (with names, roles, business type where possible)
If you’re in B2B, even three detailed testimonials often beat 30 generic “great service!” reviews.
6) Optimise for “entity SEO” (build a strong knowledge graph)
Entity SEO is about making sure your brand is consistently understood as a real-world thing:
“Remap Online” = a digital marketing agency in Australia offering SEO, email marketing, paid social, web, etc.
AI systems are better at recognising entities than keywords — but only if the signals are consistent.
The basics that make a big difference
- Same business name everywhere (no variations like “Remap”, “Remap Online”, “RemapOnline” unless intentional)
- Same address / service area, phone, URL (NAP consistency)
- Same core service descriptions across profiles
- Consistent leadership/team signals (LinkedIn, About page, speaker bios)
- Proper structured data (Organisation, LocalBusiness, Service, Review schema where relevant)
Also make sure your “About” page and key service pages clearly connect the dots:
- Who you are
- Where you operate
- What you do
- Who you do it for
- Proof you’ve done it before (case studies, results, testimonials)
This is how you become “recommendable” rather than just “findable”.
7) Maintain technical SEO (yes, the boring stuff still matters)
AI can’t recommend what it can’t reliably access.
Even if you’re doing everything above, a slow, messy, broken site will limit crawling and indexing. Bing (and other crawlers) still operate with standard crawling behaviour and user agents — your site needs to be accessible and performant.
Technical checklist (keep it simple)
- Fast mobile performance (Core Web Vitals as a guide)
- Clean internal linking (important pages reachable in 2–3 clicks)
- XML sitemap submitted (Google Search Console + Bing Webmaster Tools)
- No accidental noindex on key pages
- Canonicals set correctly (avoid duplicate content confusion)
- Clear robots.txt rules (don’t block critical sections)
- Fix broken pages and redirect chains
- Use HTTPS everywhere
If your CMS or theme is bloated, this is where you’ll quietly lose visibility — including AI-driven visibility.
8) Focus on trust (AI is designed to avoid bad recommendations)
This is the big one.
AI models are built to reduce the chance they recommend something misleading, unsafe, scammy, or low quality. So your content has to earn trust.
What “trust” looks like on a page
- Specific claims backed by evidence (screenshots, examples, methodology)
- Clear authorship (who wrote it, why they’re qualified)
- Real-world constraints (pricing ranges, timeframes, “it depends” explained properly)
- Transparent limits (“This approach won’t suit businesses that…”)
- Updated timestamps where freshness matters
- Helpful, non-salesy tone
If you’re writing “best X” content, avoid fluff. AI can smell generic filler because it’s trained on mountains of it.
Putting it all together: a simple 30–60–90 day plan
Days 1–30: Build the foundation
- Pick 3–5 high-intent topic clusters
- Map 20–40 bottom-of-funnel queries
- Create or upgrade your pillar pages
- Fix major technical blockers (speed, indexing, internal links)
- Standardise your entity info (name, services, profiles)
Days 31–60: Publish specialised pages + proof
- Publish 8–12 specialised pages (industry/use-case/problem pages)
- Add FAQs and decision criteria sections
- Build 2–3 strong case studies
- Start a review push (aim for 10 detailed reviews)
Days 61–90: Authority distribution
- Secure 5–10 credible third-party listings/mentions
- Partner ecosystem pages (where relevant)
- One or two guest posts or expert quotes
- Continue publishing specialised pages based on sales conversations
This is the compounding part: every mention and every specialised page becomes another “confidence point” for an AI deciding whether to name you.
FAQs: showing up in AI chat recommendations
“Do I need to rank #1 on Google to be recommended by AI?”
Not always. AI systems often pull from a mix of sources and may cite pages that aren’t top-ranked, especially if the page is uniquely specific and well-structured.
“Is this just SEO with a new label?”
Some of it is classic SEO (crawlability, structure, authority). The difference is the emphasis on:
- ultra-specific intent pages,
- consistent entity signals,
- third-party validation,
- and formatting that’s easy to extract.
“Should I write content differently?”
Yes — write like you’re answering a smart customer who’s ready to act. Be direct, include decision criteria, and make proof easy to find.
“What’s the biggest mistake businesses make?”
Publishing broad, generic pages that say the same thing as everyone else — then wondering why no one (human or AI) chooses them.
The bottom line
To show up in AI chat recommendations, you don’t need tricks. You need clarity + specificity + independent validation + clean technical foundations.
If you do these eight things well:
- Topic clusters + specialised pages
- Bottom-of-funnel intent
- Authority distribution
- AI-friendly formatting
- Third-party validation
- Entity SEO
- Technical SEO
- Trust-first content
…you’ll be building a brand that AI systems can confidently recommend because the wider internet backs you up.