The problem this solves
A proper competitive teardown touches eight or nine different research surfaces: company registries for funding and headcount, job boards for hiring direction, the technology profile behind the site, every major ad library, the organic keyword footprint, and now the AI answer engines your buyers actually consult. Pulling all of that by hand is a two-day job for a good analyst, so it happens once a year, usually the week before a board meeting, and it is stale within a month of being presented.
The cost is subtle but constant. Sales walks into deals with last quarter's read on the rival. Product debates roadmap against a positioning page that changed in March. Marketing prices campaigns without knowing the competitor just doubled its ad footprint. The information exists in public sources the whole time; what is missing is a repeatable way to gather it, structure it, and put it in front of the people who decide.
How the mission runs
- Establish the company baseline. The agent starts with Firmographics to profile the target: size, funding history, locations, and the segment it sells into. This baseline anchors everything that follows, because ad spend and hiring patterns only mean something against the backdrop of company stage and headcount.
- Read hiring and technology signals. Hiring Data reveals where the company is investing next, since open roles are a public roadmap written in job descriptions. Technographics reads the stack behind their site and product, from analytics to infrastructure. Together the two show strategy months before it reaches a press release.
- Map the demand footprint. Ad Libraries pulls every active creative across the major platforms and summarizes the angles being tested. Keyword Intelligence maps the organic footprint - which terms they own, which they are climbing on, and where their content engine is pointed. The result is a full picture of how they acquire customers today.
- Test AI-answer visibility. AI Visibility runs live buyer questions in the category through the answer engines and records where the competitor is cited, how it is described, and whether your brand appears at all. This is the layer most teardowns skip and the one buyers increasingly rely on when they shortlist.
- Build the deck and stage the send. Every finding lands in an executive Gamma deck: one narrative, evidence linked on each slide, an implications section at the end. The email goes out through Gmail to the recipients you named, and if you keep approvals on, the send waits in your queue until you clear it.
The prompt
This is the exact objective the agent receives. Swap the obvious placeholders for your own domain, segment or channel and run it as-is from the console, Slack, or the API.
What comes back
A finished Gamma presentation - typically twelve to eighteen slides - covering positioning, funding and headcount, hiring direction, tech stack, ad activity, organic footprint, and AI-answer visibility, with every claim linked to its source. The deck is delivered by email through Gmail to the list you specify, and the raw findings remain attached to the mission run so you can drill into any slide's evidence later.
Make it yours
- Point it at three competitors and ask for a comparative teardown, one section per rival, with a final slide ranking who poses the most credible threat to your pipeline this year.
- Narrow the scope to a single dimension, such as hiring plus technographics, when you want a fast strategy read before a quarterly planning session rather than the full workup.
- Schedule the same prompt monthly and ask the agent to open each deck with a what-changed summary against the previous run, so the teardown becomes a living document.
Frequently asked questions
How current is the data in the teardown?
Everything is gathered at run time. Ad Libraries and Keyword Intelligence reflect what is live when the mission executes, and AI Visibility queries the answer engines during the run itself. Firmographic and hiring records update on their sources' own cycles, so the deck notes the observed date beside each claim.
Can I review the deck before it is emailed?
Yes. With approvals enabled, the Gamma deck is staged and the Gmail send sits in your approval queue until you release it. You can edit the deck in Gamma first, then approve the send, so nothing reaches executives without your sign-off on both content and timing.
Where does the evidence for each claim come from?
Each slide cites its sources: the ad creatives observed, the keyword rows behind the organic read, the specific AI answers captured, and the public records behind funding and hiring. If a signal is inferred rather than directly observed, the deck says so explicitly beside the claim.