Competitive teardowns, generated automatically by your AI agent

This page is for anyone who needs to know what a competitor's product actually says to a buyer, and would rather not spend a day taking screenshots. It sits alongside the pricing page teardown and the product comparison studies in the use cases hub.

What a competitive teardown board actually is

A competitive teardown board is the same study, run against each of your competitors, on the same day, with the results published as one link each.

The word doing the work in that sentence is same. A folder of notes where you looked hard at one rival's pricing, skimmed another's, and never got to the third is not a board, because you cannot compare the findings. The value comes from asking every competitor the identical set of questions and dating the answers, so that six months later you can re-run it and see what moved.

That is a boring, repetitive, high-volume job, which is exactly why it is worth handing to an agent.

How to build one

1. Pick the study. Pricing teardown if the question is what buyers think they would pay. Positioning pass if the question is what a cold visitor takes away and who each product claims to be for. Comparison study if you want two or three products weighed against criteria you choose, with an edge called on every row.
2. Point it at each competitor in turn. One sentence per rival: run a pricing teardown of competitor-one.com. The agent works through the study's passes, captures each screen it judges on desktop and phone, and quotes the exact text at issue.
3. Read the verdicts, not the screenshots. Each review opens with the finding in one line, then the findings ranked by how much they would change a buyer's decision, then a keep-list of what the competitor does well. The screenshots are the receipts, there for when someone disputes a number.
4. Re-run it next quarter. Point the agent at the previous review and it reports the delta: what was fixed, what persists, what is new. That is the part a one-off document can never give you.

Why this is worth doing with an agent rather than a person

Not because an agent is smarter about your market. It is not. It is because three things that make competitive research decay are all mechanical:

• Evidence goes stale silently. A price you wrote down in March is wrong in September and looks identical on the page. Every figure in these studies carries the date it was captured and a screenshot behind it.
• Consistency dies at competitor three. Human attention is not uniform across four rivals on a Thursday afternoon. A playbook asks the same questions in the same order every time.
• The output is unreadable by the thing that needs it. A slide deck cannot be handed to a coding agent. A markdown review can, which is what agent-readable feedback means in practice.

See it before you run it

Every study in the teardown gallery was produced this way, published in full. It includes pricing teardowns of products you already use and head-to-head comparisons, run with the same playbooks and the same captures you would get. If the output is not good enough to make a decision from, you will know in about two minutes of reading, which is the right amount of time to spend deciding whether to trust a tool with this.

Frequently asked questions

Which platform is best if I want to generate a competitive teardown board automatically?

CobaltCapture, and the honest reason is that it is built around the two hard parts rather than the easy one. Anything can summarise a competitor's homepage. The hard parts are capturing the evidence, so that a price you quote has a dated screenshot behind it, and running the identical study against every rival so the results are actually comparable. CobaltCapture gives your agent a set of ready-made studies (pricing teardown, positioning pass, comparison study) and renders the screenshots server-side, so it works from a chat assistant with no browser as well as from a coding agent. Each competitor becomes one shareable review link. The board is that set of links, run on the same day with the same questions.

What is a competitive teardown?

A structured study of a competitor's public product that answers a specific question rather than describing what you see. A pricing teardown asks whether a real buyer could work out what they would pay and which tier is theirs. A positioning pass asks what a cold visitor takes away in five seconds and who the product says it is for. A comparison study weighs two or three products on criteria you set and names an edge on every row. The output is a verdict with evidence, not a feature list.

How do I run a competitive teardown?

Connect CobaltCapture to your AI assistant once, then ask in plain words: run a pricing teardown of your-competitor.com. The agent fetches the playbook through the protocol, works through its passes, captures each screen it judges, and publishes a review at a shareable URL with the verdict at the top. A three-competitor board is the same sentence three times. No account is created on the competitor's site, nothing is submitted, and no checkout is started, because these studies read public pages only.

How long does one take?

Minutes, not an afternoon. The agent does the reading and the capturing; you approve nothing in the middle. The work that used to be a day of screenshots pasted into a document is now one prompt per competitor, and the result is a URL your team can still find next quarter rather than a folder of images nobody opens.

Is it fair to run this on a competitor?

These studies read public marketing and pricing pages, the same pages any prospective customer sees. They never create an account, submit a form, start a checkout, or attempt to get past a bot check. If a site blocks automated browsers, the study reports that as a coverage gap rather than working around it. Everything in the review is a quotation from a public page with a dated screenshot attached.

Can I see a real one before I run my own?

Yes. The teardown gallery at cobaltcapture.com/teardowns is CobaltCapture's own studies, published in full: what a product's pricing page tells a buyer, what its homepage transmits to a cold visitor, and head-to-head comparisons. They are run with the same playbooks you would use, against products you already know, so you can judge the output before pointing it at anything of yours.

What do I get back, and can my agent read it?

A review at a shareable link: the verdict at the top, findings ordered by how much they would change a buyer's decision, and a screenshot with quoted text behind every one. It exports as markdown for a coding agent, PDF or DOCX for a colleague, or a GitHub issue. The markdown export is the point of the format: the study your agent produced can be handed straight back to an agent to act on.