Cheap Seats

A read-only copy of Cheap Seats measuring itself, updated hourly. Run your own.

Quick wins

The fix lists from the latest run of every prompt set, core sets first, then fastest expected ranking gain: prompts a fix could flip per working day, each weighted by what it has left to win (one minus its recommended rate over the last two weeks; named, for an info prompt). Mark a fix with the commit or pull request you submitted for it; open leaves out the ones you have. A later fix for the same page stays open, with what was tried before.

Statusall 7open 3accepted 4

Priorityall 7urgent 2high 2medium 2low 1

Siteall 7elsewhere 7

Gapall 8documentation 7third-party 1

Setall 27Finding out whether AI assistants recommend us 7Getting recommended instead of a competitor 6Choosing an AI visibility tool 6Cheap Seats head to heads 1Open-source and self-hosted AI visibility 7

Publish popcorn.zone/docs/guides/benchmark-against-competitors on share-of-voice rank accepted urgent documentation effort S flips 3 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/benchmark-against-competitors
Must say: Explain how to benchmark against competitors. Popcorn records every product named in each answer, computes each prompt set's share-of-voice rank and recommended/mentioned rates day by day, and keeps the answers and citations behind each number. Include a worked example showing the competitor table and the rank trend, and explain why comparing top-pick counts on the same prompt set is the fair benchmark.
Done when: A re-run of prompt 9 or 6 names Popcorn or cites this page.
Displaces: https://help.peec.ai/article/decision-lab-what-is-share-of-voice-and-how-is-it-calculated-23
Why: P9: top picks were Profound, Peec AI, Scrunch and Peec AI across the search answers.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/benchmark-against-competitors on share-of-voice rank

When buyers ask an AI assistant the questions below, it doesn't recommend us, or recommends us for the wrong reasons. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- Is there a way to measure our share of voice in AI chatbot answers?
- What's the best way to benchmark my brand's visibility in LLM answers against competitors?
- What metrics should a marketing team use to measure presence in AI assistant answers?

## What the assistant said
P9: top picks were Profound, Peec AI, Scrunch and Peec AI across the search answers.

## Who wins the question today
https://help.peec.ai/article/decision-lab-what-is-share-of-voice-and-how-is-it-calculated-23. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/benchmark-against-competitors so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Explain how to benchmark against competitors. Popcorn records every product named in each answer, computes each prompt set's share-of-voice rank and recommended/mentioned rates day by day, and keeps the answers and citations behind each number. Include a worked example showing the competitor table and the rank trend, and explain why comparing top-pick counts on the same prompt set is the fair benchmark.

## Done when
A re-run of prompt 9 or 6 names Popcorn or cites this page.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

accepted https://github.com/metcalfc/popcorn-site/pull/13 · guides/benchmark-against-competitors (the fix said docs/guides/; guides live at /guides/): share of voice and rank from report.go, daily trend rules from history.go, worked example from run r-20261022-043101-41215d mcp 2026-10-22 05:20:23
pending: the set hasn't run since

From this run

Publish popcorn.zone/docs/guides/check-if-chatgpt-recommends-you with a 15-minute walkthrough accepted high documentation effort S flips 2 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/check-if-chatgpt-recommends-you
Must say: Write a step-by-step how-to. Write 10-20 buyer questions as a TOML prompt set, run docker, configure OpenAI (ChatGPT's provider) and Claude keys or the local Codex/Claude Code CLIs, and set a daily budget. Then read the recommended/mentioned/absent grade, position and top pick for each question. Show a sample graded answer and contrast it with checking by hand in ChatGPT, where memory and personalisation skew results.
Done when: A re-run of prompt 3 cites this page or names Popcorn in at least one search answer.
Displaces: https://www.superlines.io/articles/best-chatgpt-tracking-tools
Why: P3 recall: top pick Peec AI. Search: top pick Otterly.AI. Codex cited help.openai.com/en/articles/8590148-memory-in-chatgpt.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/check-if-chatgpt-recommends-you with a 15-minute walkthrough

When buyers ask an AI assistant the questions below, it doesn't recommend us, or recommends us for the wrong reasons. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- How can I find out whether ChatGPT recommends my product when people ask about my category?
- What tools track how often AI assistants like ChatGPT, Claude, Perplexity and Gemini mention a brand?

## What the assistant said
P3 recall: top pick Peec AI. Search: top pick Otterly.AI. Codex cited help.openai.com/en/articles/8590148-memory-in-chatgpt.

## Who wins the question today
https://www.superlines.io/articles/best-chatgpt-tracking-tools. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/check-if-chatgpt-recommends-you so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Write a step-by-step how-to. Write 10-20 buyer questions as a TOML prompt set, run docker, configure OpenAI (ChatGPT's provider) and Claude keys or the local Codex/Claude Code CLIs, and set a daily budget. Then read the recommended/mentioned/absent grade, position and top pick for each question. Show a sample graded answer and contrast it with checking by hand in ChatGPT, where memory and personalisation skew results.

## Done when
A re-run of prompt 3 cites this page or names Popcorn in at least one search answer.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

accepted https://github.com/cheapseatsdev/cheapseats-site/pull/38 · Merged and live at cheapseats.dev/guides/check-if-chatgpt-recommends-you: the 15-minute walkthrough from TOML prompt set to graded answer, own keys or subscription CLIs, daily budget, Docker check and run, the verdict table, two real graded answers, and ChatGPT's own advice on memory and personalisation as the reason not to check by hand. mcp 2026-10-23 02:57:08
pending: the set hasn't run since

proposed https://github.com/cheapseatsdev/cheapseats-site/pull/38 · New guide at cheapseats.dev/guides/check-if-chatgpt-recommends-you (guides live at /guides/): a 15-minute walkthrough from TOML prompt set to graded answer, OpenAI and Claude via own keys or the codex/claude CLIs, a daily budget, Docker check and run, the verdict table with position and top pick, two real graded answers from the 22 October runs, and why checking by hand in ChatGPT misleads, quoting ChatGPT's own advice about memory and personalisation. mcp 2026-10-23 02:55:48
pending: the set hasn't run since

From this run

Publish popcorn.zone/docs/guides/prove-content-impact on daily runs and fix-to-prompt proof accepted high documentation effort S flips 2 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/prove-content-impact
Must say: Explain how to re-check and report change. Set a daily run within a daily budget, watch the day-by-day share-of-voice rank and rates, and tie each shipped fix to the prompts it was meant to flip. Report those prompts before and after, with the stored answers and citations as proof. Include a sample leadership one-pager built from the fix list's 'prompts it should flip' field.
Done when: A re-run of prompt 14 or 15 cites this page.
Displaces: https://help.otterly.ai/monitoring-interval
Why: P14 claude search: top pick 'Otterly.AI'. Codex cited help.otterly.ai/monitoring-interval.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/prove-content-impact on daily runs and fix-to-prompt proof

When buyers ask an AI assistant the questions below, it explains the topic without naming us or citing our pages. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- How often should we re-check whether AI assistants recommend us, and how do we track changes over time?
- How do I prove to leadership whether our content work is changing what AI assistants recommend?

## What the assistant said
P14 claude search: top pick 'Otterly.AI'. Codex cited help.otterly.ai/monitoring-interval.

## Who wins the question today
https://help.otterly.ai/monitoring-interval. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/prove-content-impact so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Explain how to re-check and report change. Set a daily run within a daily budget, watch the day-by-day share-of-voice rank and rates, and tie each shipped fix to the prompts it was meant to flip. Report those prompts before and after, with the stored answers and citations as proof. Include a sample leadership one-pager built from the fix list's 'prompts it should flip' field.

## Done when
A re-run of prompt 14 or 15 cites this page.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

accepted https://github.com/cheapseatsdev/cheapseats-site/pull/41 · Merged and live at cheapseats.dev/guides/prove-content-impact: run cadence and budget, the day-by-day rank and rates with rolling windows and the within-noise test, marking a fix and reading its before/after outcome on its own prompts, a real attempt outcome, and a one-page report built from those fields. mcp 2026-10-23 03:13:30
pending: the set hasn't run since

proposed https://github.com/cheapseatsdev/cheapseats-site/pull/41 · New guide at cheapseats.dev/guides/prove-content-impact (guides live at /guides/): how often to re-check and why (schedule, tiers, budget, measured cost), the rankings series with rolling averages, bands and the within-noise test on a real day, how each fix is tied to the prompts it should flip and judged before and after on exactly those (attempt outcomes, statuses, target seen, host cited), a real too-early outcome with per-prompt counts, and a one-page leadership report built only from the attempt's fields plus a share link. mcp 2026-10-23 03:11:47
pending: the set hasn't run since

From this run

Publish popcorn.zone/blog/ai-visibility-tools-compared: Popcorn vs Peec, Profound, Otterly, Scrunch accepted urgent documentation effort M flips 6 Finding out whether AI assistants recommend us

Where: popcorn.zone/blog/ai-visibility-tools-compared
Must say: Compare Popcorn with Peec AI, Profound, Otterly.AI, Scrunch, Ahrefs Brand Radar and Semrush AI Visibility row by row. Popcorn's rows: MIT licensed and self-hosted (one Docker container with SQLite); TOML prompt sets in your own git repo; Claude and OpenAI via API or local Claude Code/Codex CLIs; separate search and recall tracks; recommended/mentioned/absent grading with position, top pick, share of voice and objections; a ranked fix list; a daily budget cap. Confirm competitor engines and pricing from their own pages, and date the table. The homepage 'alternative to Peec AI and Profound' line is still pending, but a tagline cannot be cited as a comparison, so this page has to exist separately.
Done when: On a re-run of prompts 3, 5, 6, 8, 9 and 12, at least one search answer names Popcorn or cites this page.
Displaces: https://rankability.com/blog/best-ai-search-visibility-tracking-tools/
Why: P5 search answers were shaped by tryprofound.com, peec.ai, otterly.ai and scrunch.com. 'Popcorn pages seen: NONE.'

Prompt for Claude Code
# Publish popcorn.zone/blog/ai-visibility-tools-compared: Popcorn vs Peec, Profound, Otterly, Scrunch

When buyers ask an AI assistant the questions below, it doesn't recommend us, or recommends us for the wrong reasons. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- How can I find out whether ChatGPT recommends my product when people ask about my category?
- What tools track how often AI assistants like ChatGPT, Claude, Perplexity and Gemini mention a brand?
- Is there a way to measure our share of voice in AI chatbot answers?
- How do I monitor whether AI search engines cite our website?
- What's the best way to benchmark my brand's visibility in LLM answers against competitors?
- How can I see which web pages AI assistants rely on when they answer questions in my category?

## What the assistant said
P5 search answers were shaped by tryprofound.com, peec.ai, otterly.ai and scrunch.com. 'Popcorn pages seen: NONE.'

## Who wins the question today
https://rankability.com/blog/best-ai-search-visibility-tracking-tools/. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/blog/ai-visibility-tools-compared so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Compare Popcorn with Peec AI, Profound, Otterly.AI, Scrunch, Ahrefs Brand Radar and Semrush AI Visibility row by row. Popcorn's rows: MIT licensed and self-hosted (one Docker container with SQLite); TOML prompt sets in your own git repo; Claude and OpenAI via API or local Claude Code/Codex CLIs; separate search and recall tracks; recommended/mentioned/absent grading with position, top pick, share of voice and objections; a ranked fix list; a daily budget cap. Confirm competitor engines and pricing from their own pages, and date the table. The homepage 'alternative to Peec AI and Profound' line is still pending, but a tagline cannot be cited as a comparison, so this page has to exist separately.

## Done when
On a re-run of prompts 3, 5, 6, 8, 9 and 12, at least one search answer names Popcorn or cites this page.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

accepted https://github.com/metcalfc/popcorn-site/pull/15 · blog/ai-visibility-tools-compared: Popcorn vs Peec AI, Profound, Otterly.AI, Scrunch, Ahrefs Brand Radar and Semrush row by row, dated, linking the /compare/ pages mcp 2026-10-22 05:22:35
pending: the set hasn't run since

From this run

Publish popcorn.zone/docs/guides/search-vs-recall explaining both tracks with an example medium documentation effort S flips 1 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/search-vs-recall
Must say: Explain that each question can be asked with web search forced on or with no tools at all. The two give different answers because one reflects current web pages and the other reflects training data. Show how Popcorn runs both tracks on every prompt and reports them side by side. Include a real anonymised example where the two tracks disagree; pick it from a Popcorn run first.
Done when: A re-run of prompt 13 cites this page in at least one search answer.
Displaces: https://platform.claude.com/docs/en/agents-and-tools/tool-use/web-search-tool
Why: P13: every search answer was shaped by vendor API docs and generic tool lists. No source explained measuring both modes.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/search-vs-recall explaining both tracks with an example

When buyers ask an AI assistant the questions below, it explains the topic without naming us or citing our pages. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- Do ChatGPT and Claude say different things about a product with web search on versus from training data alone, and how do I measure both?

## What the assistant said
P13: every search answer was shaped by vendor API docs and generic tool lists. No source explained measuring both modes.

## Who wins the question today
https://platform.claude.com/docs/en/agents-and-tools/tool-use/web-search-tool. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/search-vs-recall so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Explain that each question can be asked with web search forced on or with no tools at all. The two give different answers because one reflects current web pages and the other reflects training data. Show how Popcorn runs both tracks on every prompt and reports them side by side. Include a real anonymised example where the two tracks disagree; pick it from a Popcorn run first.

## Done when
A re-run of prompt 13 cites this page in at least one search answer.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

From this run

Publish popcorn.zone/docs/guides/diagnose-ai-traffic-loss: GSC, Bing, GA4 then Popcorn medium documentation effort M flips 2 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/diagnose-ai-traffic-loss
Must say: Cover the free first-party checks: Search Console generative AI performance reports, Bing Webmaster Tools AI Performance, and GA4 referrals with utm_source=chatgpt.com. Then explain the gap those leave: they show clicks and impressions, not whether the assistant recommends you or a competitor. Close that gap by running the buyer questions on Popcorn's search track for AI Overviews-style answers and its recall track for model belief.
Done when: A re-run of prompt 1 or 7 cites this page in at least one search answer.
Displaces: https://developers.google.com/search/blog/2026/06/gen-ai-performance-reports
Why: P7 codex search: top pick 'Ahrefs Brand Radar', shaped by support.google.com/webmasters/answer/16984139.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/diagnose-ai-traffic-loss: GSC, Bing, GA4 then Popcorn

When buyers ask an AI assistant the questions below, it doesn't recommend us, or recommends us for the wrong reasons. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- Our organic traffic is down and I suspect ChatGPT and Google AI Overviews. How do I check whether AI search is what's taking it?
- How can I tell whether Google AI Overviews and AI Mode mention our brand for the topics we care about?

## What the assistant said
P7 codex search: top pick 'Ahrefs Brand Radar', shaped by support.google.com/webmasters/answer/16984139.

## Who wins the question today
https://developers.google.com/search/blog/2026/06/gen-ai-performance-reports. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/diagnose-ai-traffic-loss so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Cover the free first-party checks: Search Console generative AI performance reports, Bing Webmaster Tools AI Performance, and GA4 referrals with utm_source=chatgpt.com. Then explain the gap those leave: they show clicks and impressions, not whether the assistant recommends you or a competitor. Close that gap by running the buyer questions on Popcorn's search track for AI Overviews-style answers and its recall track for model belief.

## Done when
A re-run of prompt 1 or 7 cites this page in at least one search answer.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

From this run

Publish popcorn.zone/docs/guides/choosing-prompts with measured prompt-count variance low documentation effort M flips 1 Finding out whether AI assistants recommend us

Where: popcorn.zone/docs/guides/choosing-prompts
Must say: Give a method for picking buyer questions: split them into category, comparison, problem and info prompts, and store them as TOML files changed through pull requests. Give sample-size guidance only after measuring it: run one prompt set repeatedly in Popcorn and publish the observed run-to-run variance in the recommended rate. Do not cite a prompt count without that data.
Done when: A re-run of prompt 11 cites this page.
Displaces: https://cloro.dev/blog/ai-visibility-sample-size/
Why: P11 codex search: top pick 'Ahrefs Brand Radar', shaped by ahrefs.com/aeo/choose-prompts-to-track.

Prompt for Claude Code
# Publish popcorn.zone/docs/guides/choosing-prompts with measured prompt-count variance

When buyers ask an AI assistant the questions below, it explains the topic without naming us or citing our pages. This is a documentation gap: the answer needed a page we don't have, or ours says the wrong thing.

## The questions it affects
- Which questions should we track to measure AI visibility, and how many prompts do we need before the numbers mean anything?

## What the assistant said
P11 codex search: top pick 'Ahrefs Brand Radar', shaped by ahrefs.com/aeo/choose-prompts-to-track.

## Who wins the question today
https://cloro.dev/blog/ai-visibility-sample-size/. Read it and make sure our version answers everything it does, better.

## Your task
Write or update the page at popcorn.zone/docs/guides/choosing-prompts so it closes this gap. Find where pages like this live in the repo, match their structure, front matter and tone, and make the change there. If the page exists, edit it rather than starting over.

## What it must say
Give a method for picking buyer questions: split them into category, comparison, problem and info prompts, and store them as TOML files changed through pull requests. Give sample-size guidance only after measuring it: run one prompt set repeatedly in Popcorn and publish the observed run-to-run variance in the recommended rate. Do not cite a prompt count without that data.

## Done when
A re-run of prompt 11 cites this page.

## Rules
- Don't invent numbers, benchmarks, prices, capabilities or customer names. Where a fact is needed and you can't find it in the repo or on our site, leave a clearly marked TODO saying exactly what to measure or who to ask.
- Answer the questions above directly and early on the page, in the words buyers use. AI assistants quote pages that state the answer plainly.
- Keep it scoped to this one fix. When you're done, summarise what you changed and list any TODOs.

From this run