You have a 4 pm meeting and a partner who wants the competitive landscape “in broad strokes — but accurate.” Three years ago that meant a panicked afternoon and 30 open tabs. As of June 2026, a Perplexity-plus-Deep-Research loop gives you a defensible five-competitor teardown in 30 minutes, with citations you have actually opened. This tutorial walks the loop end to end and flags exactly where AI still gets pricing, headcount, and feature parity wrong.
TL;DR
- Frame one decision in a sentence, pick 4-6 comparison axes, open a sheet (rows = competitors, columns = axes).
- Use Perplexity (free tier gives ~5 Pro Searches/day; Pro is $20/mo as of June 2026) to pull the list and one query per axis. Paste raw answers with source URLs — no paraphrasing.
- Run one Deep Research synthesis pass (ChatGPT Plus $20/mo allows ~10 runs/month; Claude Research is on any paid Claude plan from $20/mo). This is the only step where AI writes prose.
- Spot-check the two cells your partner will challenge (usually pricing and last funding round). Click through, Cmd+F the number.
- First run: 30 minutes. With a saved template: ~15 minutes.
What this covers
A repeatable 30-minute workflow: pick the right comparison axes for your decision, pull five candidate competitors with Perplexity, validate them with one Deep Research pass, dump everything into a comparison sheet, then spot-check the two cells you would stake the meeting on. The output is a single page your partner reads in 60 seconds.
Who this is for
PMs writing competitive slides before a roadmap review, founders sanity-checking a pitch deck the night before, strategy and BD teams scoping a new vertical, and analysts who normally bill the first three hours of a project to “tab juggling.” Not for long-form market reports — for those, see the AI industry research workflow.
When to reach for it
Reach for this loop when you have one short meeting, a partner or investor who will ask sharp questions, and five competitors who are mostly searchable on the open web. Skip it when the competitors are stealth-mode startups, when most data lives behind paywalls (legal, medical), or when you actually need a 12-page market brief — that is a different tool.
Which engine does what (June 2026)
The split matters: Perplexity is your fast cited-retrieval engine, and a Deep Research agent is your synthesis engine. You want both, not either.
| Tool | Plan + price (June 2026) | What it does best here | Relevant limit |
|---|---|---|---|
| Perplexity Free | $0 | The competitor list + per-axis fact pulls | ~5 Pro Searches/day |
| Perplexity Pro | $20/mo ($10/mo verified student) | Same, without the daily cap | Effectively unlimited Pro Search |
| ChatGPT Deep Research | Plus $20/mo | One synthesis pass over your filled sheet | ~10 Deep Research runs/month on Plus |
| Claude Research | Pro $20/mo (bundles Claude Code + Cowork) | Agentic multi-source synthesis with citations | Multi-step; one run can run several minutes |
Notes for accuracy, all as of June 2026: Perplexity’s free tier caps Pro Search at roughly five per day; Pro removes that cap and adds a model switcher. ChatGPT’s $100 mid-tier Pro lifts Deep Research to roughly 50 runs/month and the $200 Pro tier to around 250. Claude’s Research feature is available on any paid Claude plan (Pro $20, Max $100/$200) — the free tier does not include it. For a single teardown, the free or $20 tiers are plenty.
Before you start
- Write the decision the teardown supports in one line. “Should we ship feature X in Q3?” is a decision; “tell me about competitors” is not. The decision picks the axes.
- Pick 4-6 comparison axes ahead of time: pricing, ICP, distinct feature, distribution, recent funding, team size. Decide which two matter most for the call.
- Open a fresh spreadsheet or table. Rows are competitors, columns are axes, one cell per fact with a link.
- Pick your engines: Perplexity for fast cited answers, ChatGPT or Claude Deep Research for the synthesis pass.
Step by step
- Frame the competitor question in Perplexity. Open perplexity.ai, switch to Pro Search if you have a Pro plan (or budget one of your ~5 free daily Pro Searches). Ask “Who are the top 5 competitors to [your product or thesis] as of 2026, ranked by [traction / revenue / mindshare]?” Read the answer; click two citations to confirm the list is not stale.
- Lock the five names. Drop anyone defunct, pivoted away, or acquired into a different segment. If Perplexity offers eight names, pick the five most relevant to your decision — not the five with the loudest marketing.
- Run one Perplexity query per axis, all five competitors at once. “Pricing for Competitor A, B, C, D, E as of 2026 — list each one with currency and tier.” Repeat for ICP, distinct feature, and last funding round. Five queries, four axes, twenty data points — which fits inside the free tier’s daily Pro Search budget if you are disciplined. For Focus modes and Collections that pay off here, Perplexity basics covers the ergonomics.
- Drop every answer into the sheet with the source URL. Do not paraphrase. If Perplexity returned “$49/seat/month, billed annually,” that goes in the cell verbatim. The URL goes in the next column. Empty cells stay empty — that signals “unknown,” which is honest.
- Run one Deep Research pass for synthesis. ChatGPT (Deep Research) or Claude (Research). Paste the filled sheet as context. Ask “Given these five competitors and four axes, what are the three angles where my product can win, and the two angles where I am structurally behind?” This is the only step where AI writes prose for you. Note your monthly budget: ChatGPT Plus allows roughly 10 Deep Research runs/month, so spend it on synthesis, not the list.
- Spot-check the two cells your partner will ask about. Usually pricing and recent funding. Click the source, Cmd+F the number, confirm it is not from a 2023 blog quoting a now-dead pricing page.
First-run exercise
Pick a product you already know well — your own, or a tool you use daily. Run the full 30-minute loop. Score every cell: green if right, yellow if approximately right, red if wrong. Most first runs come back roughly 75 percent green, 20 percent yellow, 5 percent red — and the red cells are almost always stale pricing or feature claims pulled from a 2024 article. That is the failure mode to watch for on every future run.
Quality check
- Every cell has a source URL. Cells without sources are deleted, not guessed.
- The two cells your partner will ask about have been clicked through and verified.
- No competitor was silently dropped because the AI could not find data. “Unknown” is a valid answer.
- The synthesis paragraph names a specific angle, not a generic “differentiation opportunity in the mid-market.”
- You can read the whole sheet in 60 seconds. If not, you have too many axes.
How to reuse this workflow
- Save the four axes plus the synthesis prompt as a template. New vertical, new five names, same spine.
- Build a personal blocklist of stale sources Perplexity loves to cite (specific Medium accounts, AI-generated SEO sites). Pin them in the prompt as “do not use.” ChatGPT’s Deep Research also lets you scope a run to selected sites, which is the same idea from the other direction.
- Re-run the teardown quarterly on the same sheet. Diffing two quarters tells you who actually shipped versus who only marketed.
Recommended workflow
Decision in one line → axes locked → Perplexity for the list → Perplexity per axis → fill the sheet with URLs → Deep Research synthesis → spot-check two cells → one-page summary. The full loop is 30 minutes the first time, ~15 minutes once you have a template.
Common mistakes
- Skipping the decision sentence — every axis looks relevant, the sheet bloats, the meeting drifts.
- Trusting Perplexity’s competitor list without confirming the companies still exist as described.
- Filling cells from memory because “I think their pricing is around X” — that is the cell your partner will catch.
- Asking Deep Research for the competitor list — it is slower than Perplexity, no more accurate, and burns one of your ~10 monthly runs.
- Treating the synthesis paragraph as the deliverable — the sheet is the deliverable; the paragraph is the lede.
- Forgetting the empty cells. Three “unknown” cells across five competitors is a finding, not a gap.
FAQ
- Why Perplexity instead of just ChatGPT?: Inline citations on every sentence. You can audit the sheet in two minutes; with a plain ChatGPT answer you cannot tell which numbers were retrieved versus invented.
- Do I need a paid plan on either tool?: Not necessarily. Perplexity’s free tier gives ~5 Pro Searches/day as of June 2026, which covers a careful five-query teardown. Deep Research needs a paid tier — ChatGPT Plus ($20/mo, ~10 runs/month) or any paid Claude plan ($20/mo+). For a one-off teardown the free and entry tiers suffice.
- What if a competitor has no public pricing?: Leave the cell empty and write “no public pricing” in a notes column. Do not let AI invent a number.
- Which model should run the synthesis?: Any current flagship is fine for one short pass — ChatGPT (GPT-5.5), Claude (Sonnet 4.6 or Opus 4.7), or Gemini 3.1 Pro. Pick whichever Deep Research / Research agent you already pay for; the prompt matters more than the model here.
- Can I do more than 5 competitors?: Yes, up to 8 before the sheet becomes unreadable in a 60-second scan. Beyond 8, switch to the AI industry research workflow.
- How fresh is “fresh enough”?: Pricing and funding must be 2025 or 2026. Feature claims tolerate 12 months. Anything older needs a click-through. See Anthropic’s overview of the Research feature for how agentic citation chains work.