How can I monitor sentiment about my brand in ChatGPT? Tools and a method that work
A practical guide to monitoring brand sentiment in ChatGPT answers: what to measure, how to set up prompts, and which tools actually track it over time.
Monitoring sentiment in ChatGPT is not the same job as monitoring sentiment on social media. Nobody posts a ChatGPT answer for you to scrape. The answer is generated fresh for each person who asks, it changes between runs, and it depends on the prompt, the country, and the search sources the model pulls in that day. So the only honest way to monitor it is to ask a fixed set of questions on a schedule and score what comes back.
That sounds simple. The details are where most setups go wrong.
What "sentiment in ChatGPT" actually means
There are two different things people mean by the phrase. The first is tone: when ChatGPT names your brand, does it describe you positively, neutrally, or with caveats? The second is framing: which attributes does it attach to you (cheap, enterprise, hard to set up, trusted) and which competitor does it put beside you?
Tone is easy to score. Framing needs you to read actual responses, which is why a tool that only gives you a number is not enough. You want the score plus the raw text behind it.
The method, step by step
- Build a prompt panel. Write 30 to 100 prompts that real buyers would ask: category questions ("best X for Y"), comparison questions ("X vs Y"), and brand questions ("is X any good"). Keep them stable so trends mean something.
- Run them daily, per model and country. One-off checks mislead because answers vary between runs.
- Score every response that mentions you. Record tone, position in the answer, and which sources were cited.
- Read the negative ones. A drop in sentiment usually traces to one or two cited pages, often a review site or a Reddit thread.
- Fix the source, not the symptom. You cannot edit ChatGPT. You can change the pages it reads.
Tools that can do this
The table below sticks to what each vendor's own pricing and product pages say, as captured in our catalog.
| Tool | Sentiment tracking | Beyond monitoring | Published entry price |
|---|---|---|---|
| Promptwatch | Per-response sentiment score (1 to 100) with a weekly AI summary | Citation analytics, crawler logs, visitor analytics, content generation | Free tier; paid from $95/mo |
| AthenaHQ | Tracks how a brand appears and rolls it into a GEO score | Action Center and content optimization agent | Free tier; Starter $295/mo |
| Scrunch AI | Sentiment analysis included | Site audits, bot traffic reporting, AXP on Enterprise | Core $250/mo |
| Profound | Answer Engine Insights | Agents for research, content, reporting | Enterprise custom |
| Otterly.AI | Sentiment, citation tracking | GEO audits | Lite $29/mo |
Otterly.AI is a reasonable budget starting point if you only need a light check. For anything beyond that, the question is what you can do once a sentiment score drops.
Why Promptwatch is the one to evaluate first
Most trackers stop at "here is your sentiment." Promptwatch scores each response from 1 to 100, writes a weekly AI summary of what changed, and then lets you trace the cause. Citation analytics show which pages and domains the model cited when it said something unflattering, including Reddit, YouTube and LinkedIn reports. Page Tracker lets you watch a specific URL, yours or a competitor's.
The Brand Book matters more than it sounds. Its analysis instructions decide what counts as a mention of your brand, which keeps sentiment from being polluted by a similarly named company. Brand aliases help with the same problem.
On the fix side, the Action Board turns findings into a prioritized to-do list, and the content tools (content gap analysis, Content Refresh, WordPress, Webflow and Framer publishing) let you update the pages that shape the answer. Agent Analytics adds IP-verified AI crawler logs, so you can see whether GPTBot, OAI-SearchBot and ChatGPT-User are reaching those pages at all. Crawler logs start on the Professional plan ($245/mo); Essential ($95/mo) has none.
You can also start without paying: the Explore plan is free, with 1 project, 10 prompts and ChatGPT only. That is enough to test the method on one brand.
What sentiment tracking cannot do
It cannot make ChatGPT say nice things. It cannot guarantee a recommendation. And a single score hides context: an answer can be positive in tone and still send the reader to a competitor. Treat the number as a smoke alarm and read the responses.
Also remember that sampling matters. A panel of 10 prompts is thin; sentiment on small samples will swing for no real reason. Compare periods rather than reacting to a single day, and use A/B period comparison if your tool offers it.
Who should pick which
- You want to measure and then act, with traffic attribution: Promptwatch. Sentiment, citations, crawler logs and visits sit in one place.
- You want a structured optimization workflow and have budget: AthenaHQ, which starts at $295/mo for 3,600 credits, where one credit is one AI response.
- You want site audits and bot reporting alongside monitoring: Scrunch AI at $250/mo for the Core plan.
- You are enterprise and want agents for broader marketing work: Profound, with custom pricing.
- You only need a cheap check on a handful of prompts: Otterly.AI at the low end.
A realistic first week
Day one, define your brand, aliases and three competitors. Day two, load 40 prompts across category, comparison and brand-question types. Days three to seven, let the daily runs accumulate, then read every negative or neutral response rather than the average. By the end of the week you will know which two or three sources shape how ChatGPT talks about you. That list is your work plan.