What is marketing context engineering?
Marketing context engineering decides what an AI model reads before it writes for your brand, loads it in code and checks the draft against the same material. How it works, what it costs and where it stops.
Notes on selling into small, named markets
What we learn running go-to-market for companies that sell into a few hundred named accounts, written for the founders and commercial leads who do the selling. Each article ends with a check you can run on your own market this week.
What does the Torke blog cover?
Notes for founders and commercial leads selling into a few hundred named accounts: what counts as a qualified lead and how to audit one, how to measure whether accounts move and stay moved, how to check what AI assistants say about you, how per-lead pricing works, and how to time outreach to a dated event. Each article ends with a check you can run on your own market.
All articles
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How to use the Torke Matrix to decide which accounts to work this week
An account prioritization matrix that crosses fit with timing tells a team which few accounts deserve work this week, and which ones can safely wait.
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How we calculate the Torke Score, and why fit and timing are multiplied
Adding a fit score to an intent score lets one of them hide the absence of the other. Multiplying them makes a high score require both.
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Free Spin, our name for marketing activity that moves no account
Vanity metrics in B2B marketing are the numbers that rise while no account moves closer to buying. We call that activity Free Spin, and it can be measured.
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How to check whether pipeline progress holds, with the Ratchet Rate
Deals and accounts go backwards in the pipeline more often than reports show. The Ratchet Rate counts how much forward movement still holds 90 days later.
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How to measure Account Grip, the share of a buying group that talks to you
One warm contact at an account says little about whether a purchase will happen. Account Grip counts how much of the buying group is actually in the conversation.
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How long before lead generation works? We measure it as Spin-Up Time
Every buyer asks how long B2B lead generation takes to produce anything. We answer with a measured number, the days from signing to the first accepted lead.
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How to measure your Definition Gap, the leads that would not survive five facts
A lead quality audit checks last month's reported leads against five written facts. The share that fails is your Definition Gap, and every cost per lead inherits it.
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How we measure Shortlist Share, how often AI buying agents put you on the list
AI assistants and buying agents can now propose suppliers before anyone visits a website. Shortlist Share measures how often they propose you, and why they leave you out.
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How we check Machine Recall, whether AI names you before anyone mentions you
Most teams check AI answers by typing their own company name. What decides a buyer's shortlist is whether an assistant names you when the buyer doesn't.
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How we measure and fix Answer Fidelity when AI describes you wrongly
AI assistants describe most companies roughly right and get a few facts wrong. We count the wrong statements, trace each one to the page it came from and correct that page.
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How to measure AI Retrievability with a question set that stays the same
A one-off check of AI answers describes one afternoon. A fixed question set asked on a set date each month shows whether you are gaining or losing ground.
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How we define Deal Velocity, from accepted lead to opportunity
The days between a lead and an opportunity belong to nobody, which is where handovers stall. We measure them as the median days from an accepted lead to an opened opportunity.
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What counts as a qualified lead, in five facts
Most arguments between marketing and sales about pipeline are arguments about a definition nobody wrote down. Five recorded facts settle them before they start.
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Why a per-lead price has to start as a subscription
Nobody knows on day one how many qualified leads an account list can produce, so a fair price per lead has to be measured before it is charged.
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Why your addressable market is closer to 400 accounts than 40,000
Most demand programs for deep-tech companies are sized for a market that never existed, and the fix starts with counting the real account list.
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Why most AI companies have no category to rank for yet
When buyers don't yet have a name for what you build, search volume reads as zero, and the work becomes building the vocabulary they'll search for later.
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The week something changed is the whole pitch
In a category with no search volume, the only reliable opening is reaching an account inside the window a dated, public event created.
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Bring us the problem, and we bring the solution to it
Tell us what your team sells, who buys it and where deals stop moving. You'll get a written reply saying which way of working fits you, or whether a Diagnostic makes sense, and if neither does, the reason.