service
Competitor analysis.
Continuous intelligence on every move your competitors make — surfaces, signals, spend, pricing — turned into decisions, not dashboards.
What this is — and what it isn’t
Continuous intelligence on the surfaces, signals, spend, and pricing of the businesses that share a buyer with the client. We do not produce a one-time “competitive landscape” deck. The deck is wrong within sixty days; the discipline is the work.
What we actually track
Surfaces
What pages competitors have published, what’s been removed, what’s been added — particularly net-new content, pricing-page changes, and team-page changes (a hiring signal that often predates a major launch).
Signals
Where the competitors are getting cited (which AI engines, in which prompt clusters, at what frequency) and how that’s changing month-over-month. Share-of-voice on the prompts the buyer actually runs — see GEO for the underlying mechanics.
Spend
Public-facing ad activity (Meta Ad Library, LinkedIn Ad Library, Google’s ad transparency surfaces), job postings as a proxy for hiring spend, and any leaked or disclosed signals (earnings calls for public competitors, press releases, partner announcements).
Pricing
Public list prices on the marketing site, packaging changes, the disappearance of “starts at” language (a signal that the floor has moved up), the appearance of new tiers (a signal that the segmentation has changed).
How the output reaches the team
A short weekly note, delivered in writing: what changed, what we think it means, what to do about it. Three to five items, not thirty. The point is decisions the leadership team makes differently because they read it — not a dashboard they bookmark and never reopen.
Alongside the weekly, a private channel (Slack, Discord, or email — whichever the firm uses) for real-time alerts on a defined trigger set: a competitor publishes a comparison page that mentions the client by name, a competitor’s pricing page changes, a competitor’s ad creative pivots. The trigger set is small, the signal-to-noise is high.
What we don’t do
We don’t scrape behind login walls. We don’t pretend to be customers to extract pricing. We don’t make ourselves a vendor of a competitor’s tool to spy on it. The work is restricted to public surfaces, public signals, and the named intelligence services we subscribe to under appropriate licensing. Both because the alternative is unethical and because the alternative is operationally fragile — the day a competitor catches an obviously-bogus support ticket from a research IP, your relationship with that competitor’s market disappears.
Frequently asked questions
How is this different from SimilarWeb or Semrush?
Those are data sources. We use them. The work is the editorial layer on top — deciding which signals matter, which are noise, and what the firm should do. A subscription to Semrush is not a competitive-intelligence function.
Do you do this for B2C as well as B2B?
Yes. The mechanics differ — public retail pricing is easier than enterprise SaaS pricing, ad-library coverage is better for B2C — but the discipline is the same.
Will we know who you’re tracking?
You define the list. We propose additions when we see a new entrant earning attention in the prompts your buyers run. The full tracking set is documented in a shared doc you have access to.
How fast do you alert on changes?
Within 24 hours on the weekly cadence; real-time on the named trigger set. Faster than that, the noise overwhelms the signal.