AEO Comparison Pages

Ploy builds competitor comparison pages engineered for AI search citation — positioning your product as the comprehensive default by conceding a narrow niche to each competitor.

By Neel MurthyVP of Growth at Rippling · former YC founder
How it runs

Ploy runs this Ploybook in 5 phases.

  1. Pick the comparison

    Ploy identifies the highest-leverage competitor pairing using SERP data, search volume, and your buyer's actual queries.

  2. Narrow-concession framing

    Position the competitor as good for one narrow use-case. Position your product as good for everything else. Defensible, citable, and honest.

  3. Structured comparison

    Side-by-side table, pricing, integrations, decision criteria — the kind of content AI engines extract verbatim.

  4. AEO schema + structure

    FAQPage and ItemList JSON-LD, quotable answers in the first 160 characters of each section, definitional clarity throughout.

  5. Publish + monitor citations

    Page ships, then Ploy tracks AI mentions across Perplexity, ChatGPT, and Google AI Overviews to confirm citation pickup.

Expected outputs

Buyers are typing "X vs Y" or "alternatives to X" before you. You want AI Overviews and Perplexity to cite your page when they answer those queries. You're ready to take a defensible BOFU position against named competitors.

  • A live vs / alternatives page

    A full competitor comparison page shipped as production code — structured, internally linked, and ready to capture buyers searching for the matchup.

  • AI-citable structure

    Quotable answers in the first lines of each section, plus FAQPage and ItemList schema, so AI engines can lift and cite your page near-verbatim.

  • Defensible BOFU positioning

    The narrow-concession framing concedes one small niche to each rival and claims everything else — an honest, defensible case at the bottom of the funnel.

  • Citation tracking

    Ploy monitors Perplexity, ChatGPT, and Google AI Overviews after launch, so you can see exactly when the engines start quoting the page.

Frequently asked

Workflow questions

Ploy builds competitor comparison pages engineered for AI search citation — positioning your product as the comprehensive default by conceding a narrow niche to each competitor.
Buyers are typing "X vs Y" or "alternatives to X" before you. You want AI Overviews and Perplexity to cite your page when they answer those queries. You're ready to take a defensible BOFU position against named competitors.
A live vs / alternatives page. A full competitor comparison page shipped as production code — structured, internally linked, and ready to capture buyers searching for the matchup. AI-citable structure. Quotable answers in the first lines of each section, plus FAQPage and ItemList schema, so AI engines can lift and cite your page near-verbatim. Defensible BOFU positioning. The narrow-concession framing concedes one small niche to each rival and claims everything else — an honest, defensible case at the bottom of the funnel. Citation tracking. Ploy monitors Perplexity, ChatGPT, and Google AI Overviews after launch, so you can see exactly when the engines start quoting the page.
Yes. A Ploybook is a reusable guide that adapts each run to the inputs you provide. You can run it on demand or customize a workspace copy for recurring work. Review and test that copy before scheduling it. Runs use AI credits, and required services must be connected for the account running the workflow.
About the expert

Neel Murthy

VP of Growth at Rippling · former YC founder

Neel leads growth at Rippling and was previously a two-time Y Combinator founder and Chief Growth Officer at Goldbelly. The narrow-concession comparison-page pattern this Ploybook is built on was popularized by Rippling's own vs / alternatives pages.

More from Neel
Run together

Ploybooks that pair with AEO Comparison Pages.

Powers these in Ploy:Answer Engine OptimizationPloy vs. the alternatives

Run AEO Comparison Pages today.

Bring your inputs and connect the services AEO Comparison Pages needs. Run the workflow, check its output, and adapt it for the next job. Each run uses AI credits.