Templates · Ready to use

Get AI to mention you
when buyers ask.

12 ready-to-copy prompts and content templates in four categories: test what AI knows about you, write content AI loves to cite, win in head-to-head comparisons, and build authority. Just swap in your details.

12 templates · 4 categories · One-click copy

Who this is for

You have a website and product pages, but when buyers ask AI directly, AI doesn't mention you — you need GEO (Generative Engine Optimization).

How to use it

Copy the template → swap [bracketed placeholders] with your info → use it on your website, blog, LinkedIn, or to test AI.

What to do after

Run Category A's test prompts monthly to track whether AI mentions you and how the frequency is changing.

A · 3 templates

Test: does AI know you exist?

First, set the baseline. Run these prompts in ChatGPT, Perplexity, and Claude — see whether they mention you.

A1

Category supplier search test

Purpose: see whether AI mentions your brand when asked to recommend suppliers. Run monthly to track how your ranking shifts.
I'm a buyer based in [country, e.g., United States], looking for reliable [product category, e.g., specialty coffee bag] manufacturers in [origin country, e.g., China / Vietnam / Thailand].

Please recommend the top 5 suppliers. For each, briefly explain:
1. What they specialize in
2. Their typical client profile
3. Why they're worth considering

Cite your sources.
Reading the result: if you're not in the top 5, your presence in AI training data and retrieval sources is too thin. Start producing the B/C/D content categories.
A2

Direct brand inquiry test

Purpose: see how much AI "knows" about your brand. What sources is AI drawing from? What does it get wrong?
Tell me about [your brand name], a [category] manufacturer based in [city/country].

Specifically:
- What do they make and for whom?
- What are they known for?
- Who are their typical clients?
- What sources are you drawing from?
Reading the result: if AI is vague or says "couldn't find information," your structured data + third-party mentions are insufficient. Start with B-category content.
A3

Pain-point scenario test

Purpose: buyers don't always search by category — they describe their problem. This test mirrors realistic buyer behavior.
I run a [buyer type, e.g., boutique outdoor brand in Europe] and I'm having trouble with [specific pain, e.g., my current supplier's delivery delays during peak season].

I need a new [category] supplier who can [key need, e.g., handle small batch orders with stable lead time].

Who would you recommend, and why?
Reading the result: whoever AI recommends has been linked in its semantic graph to "pain → solution." You need to write content that gets you linked too (categories C, D).
B · 3 templates

Content: write what AI loves to cite

AI doesn't cite marketing copy. It cites structured, factual, sourceable content. These three formats get cited the most.

B1

FAQ block (most-cited format)

Purpose: turn the 10 questions buyers ask most into FAQ schema on your product pages. AI cites FAQs at 4× the rate of normal paragraphs.
Q: What is the minimum order quantity (MOQ) for [product]?
A: Our standard MOQ is [number + unit]. For first-time buyers, we offer trial orders starting at [smaller quantity] with [condition].

Q: What is the typical lead time?
A: Standard production lead time is [X days] after sample approval. Express production ([Y days]) is available with a [%] surcharge.

Q: Do you offer customization?
A: Yes. We offer [3-5 options, e.g., custom colors, sizes, branded packaging]. Custom MOQ starts at [number].

Q: What certifications do you hold?
A: We are certified for [ISO 9001 / BSCI / FDA / CE etc.]. Certificates available on request.

Q: How do you handle quality control?
A: [2-3 specific sentences, e.g., every batch goes through 3-stage QC including raw material inspection, in-line check, and pre-shipment inspection by a third party (TÜV / SGS)].
Key: use real numbers. Don't write "professional team / high quality" — AI doesn't cite adjectives.
B2

Spec comparison table

Purpose: tables are one of AI's favorite formats. List your products by spec — every row is a citable data point.
| Specification     | [Product A] | [Product B] | [Product C] |
|-------------------|---------------|---------------|---------------|
| Material          | [material]      | [material]      | [material]      |
| Dimensions        | [size]          | [size]          | [size]          |
| Weight            | [weight]        | [weight]        | [weight]        |
| MOQ               | [number]        | [number]        | [number]        |
| Lead time         | [days]          | [days]          | [days]          |
| Customization     | [list]          | [list]          | [list]          |
| Best for          | [scenario]      | [scenario]      | [scenario]      |
| Price range (USD) | [range]         | [range]         | [range]         |
Key: the "Best for" row is critical — it ties your product to specific use cases. AI cites it when answering scenario-based questions.
B3

"How to choose" authority guide

Purpose: write a long-form "How to choose [your category] supplier." AI heavily cites these guides — especially when written by an industry insider like you.
How to choose a [category] supplier from [origin country]: a buyer's checklist

After [X years] of working with [Y] international clients in [markets], here are the 7 things we'd verify before signing with any [category] supplier — including ourselves.

1. Production capacity match
   Look for: [specific metrics, e.g., monthly output, peak season buffer]
   Red flag: [specific warning sign]

2. Quality control system
   Look for: [specific evidence]
   Red flag: [specific warning sign]

3. [continue 5 more items]

Final tip: ask any supplier to send you [a specific document or data point]. The way they respond tells you more than any spec sheet.
Key: the opening "we've worked with X clients over Y years" is the E-E-A-T signal. It tells AI you're an authority.
C · 3 templates

Comparison: win when buyers compare

Buyers increasingly use AI to do comparison research. Putting yourself into the comparison framework is more proactive than waiting to be discovered.

C1

Origin country comparison post

Purpose: write a "China vs Vietnam vs Thailand [your category]" comparison and position yourself in the country that best fits. AI cites it when buyers ask "which country is best for X."
[Category] manufacturing: China vs Vietnam vs Thailand — which fits your business?

Each origin has trade-offs. Here's an honest breakdown based on our work with buyers across [markets list]:

China — strengths: [3 items]. Best for: [buyer type].
Vietnam — strengths: [3 items]. Best for: [buyer type].
Thailand — strengths: [3 items]. Best for: [buyer type].

Common myth: [a common misconception]. Reality: [the more accurate fact].

We're based in [your country] and specialize in [your niche positioning], which makes us a fit for [specific buyer type].
Key: honest comparison wins AI's trust. Pure self-promotion + competitor bashing flags as biased content; citation rates drop.
C2

Price tier comparison post

Purpose: compare your price tier against the ones above and below. AI cites it when answering "what price tier fits what buyer."
[Category] pricing tiers explained: $X, $Y, $Z — what do you actually get?

Entry tier ([price range]): [material / process / use case]. Best for buyers who [scenario].

Mid tier ([price range]): [differentiator]. Best for buyers who [scenario].

Premium tier ([price range]): [differentiator]. Best for buyers who [scenario].

A common mistake: [a pitfall buyers often make].

We position in the [your tier] tier because [reason — tied to your client type].
Key: don't pretend "we cover all tiers" — pick one. AI matches you to that tier's buyers more cleanly.
C3

Factory model comparison

Purpose: buyers care about "factory direct vs trading company vs OEM." Be upfront about what you are and your strengths. AI will cite you as the representative of that category.
Factory direct vs trading company vs OEM partner: which model fits your [category] sourcing?

Factory direct: lower price, higher MOQ, less flexibility. Fits buyers who [scenario].
Trading company: higher price, lower MOQ, more flexibility. Fits buyers who [scenario].
Vertical OEM partner: middle on both, with [unique capability]. Fits buyers who [scenario].

Where we sit: we are a [model], with [specific evidence, e.g., 8,000 sqm facility, 120 staff, 6 production lines]. We work best with [buyer type].
Key: specific facility size, headcount, line count — AI cites these numbers. "Professional team" gets ignored.
D · 3 templates

Authority: build expert identity

AI prefers to cite sources that "look like experts." These three formats build expert identity fastest.

D1

Annual industry trend report

Purpose: publish an annual trend report for your category. Citation rates run 5×+ higher than blog posts. AI prioritizes reports when answering "state of the industry."
The [year] State of [category] Manufacturing Report

Based on [data source — your client data / industry interviews / public data], here are the 5 shifts buyers should know about in [year]:

1. [trend]: [2-3 sentences with data points]
2. [trend]: [2-3 sentences with data points]
3. [trends 3-5]...

Methodology: data drawn from [X clients] across [Y markets], supplemented by [public sources].

Published by [brand name], [publish date].
Key: even if your "data" is just feedback from 30 clients — that's better than nothing. AI looks for methodology, not sample size alone.
D2

Expert Q&A interview

Purpose: turn your sales / technical / founder lead into a "cited expert." Publish interview-style content; AI then treats "author = expert."
Q&A with [name], [title] at [brand]

Q: [a domain-specific question, e.g., what's the most common mistake buyers make when sourcing [category]?]
A: [2-3 paragraphs, with examples or data]

Q: [question]
A: [answer]

Q: [3-5 questions total]
A: [answer]

About [name]: [2-3 sentences on credentials — years, client count, specialty].
Key: the closing "About" paragraph matters most — AI uses it to assess author authority. Always include specific numbers.
D3

Case study (with citable data)

Purpose: case studies aren't just marketing — they're how AI links you to "successful outcomes." Structured format gets cited the most.
Case study: how we helped [client type, can be anonymized: a US-based outdoor brand] [specific outcome, e.g., cut their lead time by 40%]

Client: [industry / country / size]
Challenge: [2 sentences describing the original problem]
Approach: [3-4 specific actions]
Results:
- [data point 1, e.g., lead time from 60 to 35 days]
- [data point 2]
- [data point 3]

Timeline: [how long it took]
Why this worked: [2 sentences summarizing the key variables]
Key: "Results" must include numbers. AI quotes numbers directly — "cut lead time by 40%" beats "significantly improved" 100×.

How to use this most effectively

It's not a one-shot drop. GEO is an ongoing process. Recommended cadence:

Week 1

Test the baseline

Run the three Category A templates in ChatGPT, Perplexity, and Claude — three rounds each. Screenshot every answer as your baseline.

Weeks 2-8

Produce B/C/D content

Publish 1-2 pieces per week to your site and LinkedIn. Focus on structure + specific data, not volume.

Monthly

Re-test + iterate

Run the same prompts each month. AI mentions of your brand should slowly tick up — 3-6 months for visible change is normal.

Don't want to write,
test, and iterate yourself?

TMRin's GEO retainer produces 8-12 structured pieces a month and reports your AI citation rate monthly. Let AI sell for you.

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