The best Perplexity prompts for market research
In short: Perplexity is built to search and to show sources, which makes it a good fit for market research as long as you read the sources. These prompts ask for market size, competitors, positioning and the tools your buyers use, and this guide explains what to hand each one and what to distrust in the answer.
Market and industry analysis
Three of these come from one long post shared on X by Success Mindset Mastery, and they escalate in how much they demand.
Industry market analysis asks for the current size, historical and expected growth, leading companies, customer segments, typical pricing, pain points, trends, barriers to entry and threats for one industry in one region, then a comparison of the top competitors. Market research report as a senior analyst covers similar ground but insists on the most recent reliable information and adds market drivers, concentration and customer behaviour.
The one to use when the answer will affect a real decision is the pre-investment briefing. It tells Perplexity you are considering entering the market and to skip the generic overview in favour of information that could change an investment decision. That framing changes the output: you get caveats and gaps instead of a smooth summary.
Whichever you use, treat market-size figures as claims to verify. A number with no source, or a source that is itself quoting an unsourced number, is not something to put in a deck. Ask Perplexity which sentence of which source the figure comes from, and open it.
Competitors and how buyers see you
Competitive analysis of three competitors, also from that post, compares three named companies across product, pricing, features, audience, positioning, marketing, reviews, strengths and weaknesses, and finishes with gaps and ten opportunities for a new entrant. Naming three real competitors, rather than asking it to choose them, keeps the answer checkable.
Check your positioning as a B2B buyer, shared by Todd E Jones, flips the perspective. It asks the model to act as a buyer in your category, look up your brand, and say honestly whether it would recommend you and where your positioning is generic. The useful part is the discomfort: if a model with access to your public site cannot explain what you do, neither can a buyer. Short but complete, shared by Prynt, is the smallest possible version of a research prompt: which tools are best for your customer, and which sources were used. The second half is the whole point.
For a closer look at one rival, Competitive intelligence brief, shared by Romàn, takes a competitor's public content plus your notes from deals and separates what is stated from what is inferred. Competitor and market scan is the lighter, in-library version when you want a map rather than a dossier.
From research to a first message
Research is only useful if it changes what you send. Find the tools your buyers use instead of you, shared by Yannis, looks for the alternatives your buyers already pay for and pulls complaints from their reviews, with the instruction not to invent quotes, then suggests a gap you could own and a headline. Prospect research brief, from AImonkey, ends in a three-line opener, which forces the research to be specific to one company.
If you do this often, start sessions with Research operator for decisions, shared by BotShelf Vampire. It sets the rules once: name the decision, separate facts from opinions, cross-check material claims and do not average away contradictions.
A research habit that survives bad sources
Run research in two passes. First, ask for the landscape with sources. Second, paste the answer back and ask which claims rest on a single source, which sources are older than a year, and which numbers are estimates rather than measurements. Research operator for decisions encodes exactly this, so paste it at the top of a research session rather than hoping you remember.
Keep the scope narrow enough to check. "The CRM market" produces smooth, useless prose. "Tools a 20-person clinic uses to cut missed appointments, with pricing from their own pages" produces something you can verify in an afternoon. When you want the buyer's words rather than the vendor's, Pain-point clusters for ad research, shared by Amin, asks for the phrases buyers actually use and the solutions they have already tried. Pair it with SERP opportunity analysis, shared by Grant O, when the question is whether a smaller site can rank for a keyword: you paste the current top results and it looks for intent the ranking pages miss.
Write down what would change your mind before you read the answer. If nothing in the report would change your decision, you commissioned the research to feel thorough, and you can stop.
How to get good results from any of these prompts
- Fill in every placeholder. Anything in [BRACKETS] is a fact only you know. Leave one empty and the model will guess.
- Tell it what not to invent. Add "use only the facts above, and flag anything missing" if the prompt does not already say it.
- Ask for one version first. Fix the direction, then ask for variations.
- Check every name, number and promise before anything leaves your hands.
- Edit it into your own voice. Read it aloud once; if it does not sound like you, change it.
Prompts in this guide
Success Mindset Mastery @freedom_guiderReport or removeSuccess Mindset Mastery @freedom_guiderReport or removeSuccess Mindset Mastery @freedom_guiderReport or removeSuccess Mindset Mastery @freedom_guiderReport or remove
Todd E Jones @tejonesReport or remove
Romàn @romanbuildsaasReport or remove
Yannis @yannnisReport or remove
Questions people ask
Can I trust the market size Perplexity gives me?
Only after you open the source and confirm it says what the answer claims. Market-size figures are often estimates quoted second-hand.
Why name competitors instead of letting the AI choose?
Naming them keeps the comparison focused and checkable. You can still ask who else it would include afterwards.
Do these prompts work in ChatGPT or Gemini?
Yes, especially if web search is turned on. They were shared for Perplexity because it shows sources by default.
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Written by the Chat Judge team from prompts in our library. We do not run model benchmarks, and nothing here is a claim about results you will get. Spot a problem? Tell us or submit a better prompt.