You're Wasting Money On Prompt Tracking

AI SEO is barely a couple of years old, but there are already a metric s**t ton of startups focused on showing when your brand is featured in ChatGPT and other AI chat tools.

Given AI is rapidly replacing traditional search (forecasted to pass it by 2028!) it's understandable that marketers, and maybe even you, the reader, would love to know how they are being featured in this new customer discovery channel.

This article explains why an AI prompt tracker isn't the way to go. And at the end it gives you an alternative solution that's not only effective, it's much cheaper.

What's a prompt tracker?

A prompt tracker works very similarly to traditional SEO keyword trackers. A user will enter a set of prompts that they think are likely to feature their brand. The prompt tracker runs these against the AI model and summarizes the output to show when brands are 'cited', meaning included in the list of sources used to generate an answer, and also whether the brand is included in the answer itself. For most prompts the brands included in the summary are a small fraction of the ones included in the list of sources.

How AI Chat Tools Make Recommendations For Brands (And How Each Step Adds Variability)

To understand why a prompt tracker is less like traditional SEO and more like just like dumping a bunch of money in a pit labeled 'Open AI', you need to understand how AI chat tools actually recommend brands, and how a prompt tracker works or doesn't work at each step:

Step 1: The user opens a chat window and enters a prompt.

Already there's a huge difference between how users engage with AI chat vs a search engine. The average length of an AI prompt is 22 words. There are a lot of ways to ask exactly the same question! If you are trying to track prompts the same way you track keyword SERPs you will be tracking exponentially more combinations.

Step 2: AI considers what it "knows" (from the model) and builds a series of web searches to run in parallel to gather data. This is known as 'query fan out'.

What's query fan out? When you enter a prompt into an AI chat that has access to web search, it will break the prompt down into several shorter, overlapping searches and run those. This process is known as 'query fan out' and it's based on a Google patent. It's a way for AI to control for variability in user prompts.

Here's what that looks like:

This recording of a prompt entered into Perplexity shows the query fan-out process in action, for the same prompt. ChatGPT does the same thing, they just don't show the queries in their interface:

Query fan out actually reduces the randomness we discussed in step 1 above. For most of those prompt variations from step 1, you don't actually need to track them individually. You just need to run each of those prompts once and get the underlying query fan out searches, de-duplicate them, and then never go back to the original prompts. For a tool that tracks 150 prompts you'll likely have 30 underlying searches max, which is a significant reduction.

Step 3: The search engine 'behind' the AI returns results.

In this step the AI sends those fan-out searches to the search engine they built or partnered with. All of the major AI chat platforms do this:

ChatGPT -> Bing
Claude -> Brave Search
Perplexity -> Their own custom search engine
Microsoft Copilot -> Bing, obviously
Google Gemini -> Google, obviously

This step adds back some randomness because search engines frequently re-rank their results for different keywords. If you've been in the SEO game for any amount of time you're very familiar with this. What it means to AI is if your brand was selected by the search engine as a result for a fan out query once, it's not guaranteed to be selected the next time that exact query is run. This means if you're tracking prompts, even if you rank #1 for a given prompt there's no guarantee you'll be in the results at all the second time it's run, even for the same person.

It's also worth mentioning that the citation that includes your brand might not be from your website at all! There's a very good chance if your brand is cited, the citation is coming from a third party; a reddit thread, a Quora answer, G2 or Yelp reviews, etc. And any sentiment from the source is likely to be applied to your brand in the summary. So if you got a bad review, AI might very well parrot that back to the user.

Step 4: AI enriches those results with other data sets

This is the step about which the least is known. If your brand is part of the AI model's training set, it will already 'know' things about you, and might use that. We talked about third party sources in Step 3 above, and SEMRush has a great report on which third-party sources are most commonly cited by AI. Most prompt trackers don't tell you 'how' you're cited, just 'whether' you're cited. But if AI mentions your brand constantly and it's all bad, you probably want to know that too!

Step 5: AI synthesizes all of this into a comprehensive response.

If you weren't already convinced that prompt tracking is a waste of time and money, this step will seal the deal. There are two huge factors in how AI generates responses that make the very concept of prompt tracking basically silly:

AI output is nondeterministic.

Most things in the field of computer science are based on the concept of "same input gives you the same output". Imagine if Excel just used a different formula every time you asked it for a calculation!

AI however is different. If you ask AI a question twice you are not guaranteed to get the same answer. In fact you are almost guaranteed to not get the same answer.

It's not exactly "AI just rolls the dice to predict the next word" as some would describe it, but there's definitely randomness involved in the output. You won't get the same response for the same prompt, and the longer the response, the more random the output. If you want to understand how this process works but don't want to do a lot of math, this article is a great start.

If you are tracking prompts, this variability means you a) Can never be 100% sure that your website will be cited in the summary for any given use of the prompt even if it's a cited source, and 2) In order to feel be 90% confident (with a 5% margin of error) that the result you get is accurate, you have to test each prompt 271 times. At an expected cost of $0.37 per run that's about $100. PER LLM. PER MODEL.

The second issue with trying to prompt trackers is that ChatGPT the web platform and the API are very different!

Most, maybe all prompt tracking tools on the market use the API. This makes a ton of sense because the API is designed for code integrations, and it is a violation of OpenAI (and every other LLM)'s terms of service to run automations against the web interface (not to mention ChatGPT usage is capped, even for paid plans).

But the API and ChatGPT.com are different, for one key reason: the system prompt. The system prompt is the set of instructions that the LLM considers alongside your message. It's the instructions that guide the LLM's behavior; always be helpful, don't tell the user how to make a bomb, that sort of thing.

When you post a message to the API there's no explicit system prompt. You can provide one, but the system prompt for ChatGPT is proprietary, unknown, changes frequently, and is by all accounts very complex. It also makes a huge difference in the output.

Here's the output from ChatGPT GPT-5 and the API for the same prompt, "What are the best wireless headphones under $200?"

ChatGPT

API

Here's what the API gives you for the exact same prompt:

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer [REDACTED]" \
  -d '{
    "model": "gpt-5",
    "input": "What are the best wireless headphones under $200?",
    "tools": [{ "type": "web_search_preview" }]
  }

Output:

{
  "id": "resp_68b04a63a7dc81a39c5527f1f509b0860af5368dc95eb64d",
  "object": "response",
  "created_at": 1756383843,
  "status": "completed",
  "background": false,
  "error": null,
  "incomplete_details": null,
  "instructions": null,
  "max_output_tokens": null,
  "max_tool_calls": null,
  "model": "gpt-5-2025-08-07",
  "output": [
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          "text": "Here are the strongest over\u2011ear wireless headphones you can buy in the US for under $200 today, with quick notes on why they stand out and what to watch for. Prices fluctuate; I list typical street prices as of August 28, 2025.\n\n- Sennheiser Accentum Wireless ($120\u2013$190): Best all\u2011rounder under $200. Clear, engaging sound, aptX HD, effective ANC, and a huge 50\u2011hour battery. Downsides: no auto\u2011pause and no case in the box. ([tomsguide.com](https://www.tomsguide.com/reviews/sennheiser-accentum?utm_source=openai), [bestbuy.com](https://www.bestbuy.com/site/sennheiser-accentum-wireless-bluetooth-headphones-hybrid-noise-cancelling-anc-all-day-comfort-black/6562240.p?utm_source=openai))\n\n- Sony ULT Wear (WH\u2011ULT900N) ($150\u2013$200): Big, fun bass with solid ANC, LDAC, foldable design, and 30h ANC battery. Great if you like an energetic, bass\u2011forward tuning. ([techradar.com](https://www.techradar.com/audio/headphones/sony-ult-wear-review?utm_source=openai), [bestbuy.com](https://www.bestbuy.com/site/sony-ult-wear-wireless-noise-canceling-headphones-black/10101593.p?utm_source=openai))\n\n- Soundcore Space Q45 ($85\u2013$150): Most ANC for the money; comfortable, folding, LDAC, case included, very long battery life. Sound needs EQ for some listeners. ([rtings.com](https://www.rtings.com/headphones/reviews/anker/soundcore-space-q45-wireless/?utm_source=openai), [sfgate.com](https://www.sfgate.com/shopping/article/soundcore-headphone-deal-prime-day-2025-20759708.php?utm_source=openai))\n\n- Sony WH\u2011CH720N ($98\u2013$150): Light, comfy, multipoint, decent ANC for the price and 35h battery. Build is plasticky and ANC isn\u2019t class\u2011leading. ([rtings.com](https://www.rtings.com/headphones/reviews/sony/wh-ch720n-wireless/?utm_source=openai), [engadget.com](https://www.engadget.com/sonys-wh-ch720n-headphones-are-back-on-sale-for-98-142823349.html?utm_source=openai))\n\n- JBL Live 770NC ($160\u2013$200): Big battery (rated up to 65h), multipoint, and \u201cTrue Adaptive\u201d ANC at a mid\u2011range price when on sale. MSRP is higher, so target sale pricing. ([jbl.com](https://www.jbl.com/over-ear-headphones/LIVE770NC.html?utm_source=openai), [amazon.com](https://www.amazon.com/JBL-LIVE-770NC-Headphones-Comfort-fit/dp/B0CT6BC631?utm_source=openai))\n\n- Audio\u2011Technica ATH\u2011M50xBT2 ($170\u2013$200): Best under\u2011$200 pick if you don\u2019t need ANC. Neutral\u2011leaning, detailed sound with LDAC and multipoint; 60h+ battery. Clamps a bit tight for some. ([soundguys.com](https://www.soundguys.com/audio-technica-ath-m50xbt2-review-60821/?utm_source=openai), [rtings.com](https://www.rtings.com/headphones/reviews/audio-technica/ath-m50xbt2-wireless?utm_source=openai))\n\n- 1More SonoFlow Pro ($70\u2013$100): Budget champ. Surprisingly capable ANC, very long battery life (often 40\u201365h with ANC on, depending on test), app EQ, and a carry case. App is basic. ([techradar.com](https://www.techradar.com/audio/wireless-headphones/1more-sonoflow-pro-hq51-review?utm_source=openai), [tomsguide.com](https://www.tomsguide.com/audio/1more-sonoflow-pro-review?utm_source=openai))\n\n- Soundcore Space One ($80\u2013$120): Another budget pick with LDAC, multipoint, and effective voice\u2011focused ANC; very comfortable. ANC/bass not as strong as Q45; soft pouch instead of hard case. ([us.soundcore.com](https://us.soundcore.com/pages/space-one/?utm_source=openai), [bestbuy.com](https://www.bestbuy.com/site/soundcore-space-one/6545162.p?utm_source=openai))\n\nDeal to watch\n- Sony WH\u20111000XM4 (older flagship) frequently dips to just under $200 during big sales; still excellent ANC and sound when you can catch it. ([esquire.com](https://www.esquire.com/lifestyle/tech/a65887935/sony-xm4-headphones-sale-labor-day-2025/?utm_source=openai))\n\nQuick chooser\n- Best overall under $200: Sennheiser Accentum. ([tomsguide.com](https://www.tomsguide.com/reviews/sennheiser-accentum?utm_source=openai))\n- Strongest ANC value: Soundcore Space Q45. ([rtings.com](https://www.rtings.com/headphones/reviews/anker/soundcore-space-q45-wireless/?utm_source=openai))\n- Bass lovers: Sony ULT Wear. ([techradar.com](https://www.techradar.com/audio/headphones/sony-ult-wear-review?utm_source=openai))\n- Lightest for long wear: Sony WH\u2011CH720N. ([rtings.com](https://www.rtings.com/headphones/reviews/sony/wh-ch720n-wireless/?utm_source=openai))\n- Best sound (no ANC): ATH\u2011M50xBT2. ([soundguys.com](https://www.soundguys.com/audio-technica-ath-m50xbt2-review-60821/?utm_source=openai))\n- Best sub\u2011$100: 1More SonoFlow Pro. ([techradar.com](https://www.techradar.com/audio/wireless-headphones/1more-sonoflow-pro-hq51-review?utm_source=openai))\n\nIf you tell me your top priorities (ANC strength, mic quality for calls, battery life, bass vs. neutral sound, Android vs. iPhone), I can narrow this to 2\u20133 perfect picks."
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To make it easier to follow, here's the rendered version of the text response only:

Here are the strongest over-ear wireless headphones you can buy in the US for under $200 today, with quick notes on why they stand out and what to watch for. Prices fluctuate; I list typical street prices as of August 28, 2025.

Sennheiser Accentum Wireless ($120-$190): Best all-rounder under $200. Clear, engaging sound, aptX HD, effective ANC, and a huge 50-hour battery. Downsides: no auto-pause and no case in the box. (tomsguide.com, bestbuy.com)
Sony ULT Wear (WH-ULT900N) ($150-$200): Big, fun bass with solid ANC, LDAC, foldable design, and 30h ANC battery. Great if you like an energetic, bass-forward tuning. (techradar.com, bestbuy.com)
Soundcore Space Q45 ($85-$150): Most ANC for the money; comfortable, folding, LDAC, case included, very long battery life. Sound needs EQ for some listeners. (rtings.com, sfgate.com)
Sony WH-CH720N ($98-$150): Light, comfy, multipoint, decent ANC for the price and 35h battery. Build is plasticky and ANC isn\u2019t class-leading. (rtings.com, engadget.com)
JBL Live 770NC ($160-$200): Big battery (rated up to 65h), multipoint, and "True Adaptive" ANC at a mid-range price when on sale. MSRP is higher, so target sale pricing. (jbl.com, amazon.com)
Audio-Technica ATH-M50xBT2 ($170-$200): Best under-$200 pick if you don\u2019t need ANC. Neutral-leaning, detailed sound with LDAC and multipoint; 60h+ battery. Clamps a bit tight for some. (soundguys.com, rtings.com)
1More SonoFlow Pro ($70-$100): Budget champ. Surprisingly capable ANC, very long battery life (often 40-65h with ANC on, depending on test), app EQ, and a carry case. App is basic. (techradar.com, tomsguide.com)
Soundcore Space One ($80-$120): Another budget pick with LDAC, multipoint, and effective voice-focused ANC; very comfortable. ANC/bass not as strong as Q45; soft pouch instead of hard case. (us.soundcore.com, bestbuy.com)

Deal to watch

Sony WH-1000XM4 (older flagship) frequently dips to just under $200 during big sales; still excellent ANC and sound when you can catch it. (esquire.com)

Quick chooser

Best overall under $200: Sennheiser Accentum. (tomsguide.com)
Strongest ANC value: Soundcore Space Q45. (rtings.com)
Bass lovers: Sony ULT Wear. (techradar.com)
Lightest for long wear: Sony WH-CH720N. (rtings.com)
Best sound (no ANC): ATH-M50xBT2. (soundguys.com)
Best sub-$100: 1More SonoFlow Pro. (techradar.com)

If you tell me your top priorities (ANC strength, mic quality for calls, battery life, bass vs. neutral sound, Android vs. iPhone), I can narrow this to 2-3 perfect picks.

Although several of the cited brands and sources are the same, the output and experience is very different! If you're using the API for prompt tracking (which, legally, is the only way you can use an LLM for this), you're not getting anything close to the same output as a real user would.

How do I track my brand's mentions in ChatGPT?

Hopefully now you are convinced that tracking prompts isn't an option. Do this instead:

Start with the prompts you want to track, and instead of tracking their output, query the LLM for this prompt:

Generate 8 distinct search sub-queries that together cover the user intent:
"[INSERT USER PROMPT HERE]"

Rules:
- Each sub-query should target a different slice of the overall intent (for example: if the user intent is [best wireless headphones under $200], then slices might include reviews, noise cancellation, comfort, battery life, durability, brand comparisons, or call quality).
- Output in a simple CSV table with columns:
  ID, Query, Slice, Priority
- ID = short unique label (Q1, Q2, …).
- Query = the exact search query text.
- Slice = short description of what part of the intent it covers.
- Priority = integer 1–10 (1 = highest).
- Do not add any commentary or prose outside of the table.

This should give you something like this:

ID,Query,Slice,Priority
Q1,"best wireless headphones under $200 2025 reviews","fresh ranked reviews",1
Q2,"noise cancelling headphones under $200 comparison","ANC focus",2
Q3,"battery life wireless headphones midrange $150-200","battery/durability",3
Q4,"comfortable lightweight over ear headphones under $200","comfort/ergonomics",4
Q5,"Sony JBL Anker Soundcore under $200 models","brand scan",5
Q6,"wireless headphones under $200 mic quality calls","voice/call performance",6
Q7,"gaming wireless headsets under $200","gaming use case",7
Q8,"refurbished vs new wireless headphones under $200","purchase context",8

Drop these into your favorite traditional SERP tracker, keeping in mind that ChatGPT uses Bing Search. Then optimize for them the way you always have. It feels good to use those old-school SEO skills!

Now set up an AI Search Analytics tool. We're obviously partial to Spyglasses but there are a handful of them on the market at various price points. Your goal here is to trck two things:

Your total AI citation volume, per website page and per model
The percentage of those citations that result in a clickthrough to your site

Once you have your SERPs and this data, you are back to doing mostly pure SEO, and you have a number to show how your work is increasing your AI 'traffic'. You also saved a few hundred or potentially thousands of dollars a month. Take yourself our to lunch and charge it to the company. You earned it.

Parting thoughts

¹ As if you needed another argument for dumping your prompt tracker, most of them also advise you to use an llms.txt file at the root of your site. This is a good way to screen out the service providers and tools that are not going to be good, because llms.txt is not a thing and never will be.

² Some prompt trackers will also generate brand consistency reports. They compare what your website shows against what various AIs 'know' about you. These are sometimes called AI Visibility Tools. This can be very helpful, because along with whether you are mentioned in ChatGPT and other AI platforms, you want to make sure what it says is accurate. You don't need to run this daily, so look for an AI Visibility Tool that doesn't require an expensive subscription.