Two axes, two decisions: fit gates, intent times

The whole model turns on one structural choice: refuse to merge fit and intent. They answer different questions, they drive different actions, and the instant you average them you destroy the information that makes either useful. Keep them apart and the model becomes legible, because every lead now sits in a quadrant that tells you exactly what to do.

Fit is a gate

Fit is the firmographic and demographic match, the answer to a blunt question: is this the right kind of company and the right kind of person for what I sell? Company size, industry, role, geography, the structural facts that decide whether this account could ever be a good client. Fit is a gate, and a gate has a hard property worth stating plainly: no amount of engagement overrides a poor fit. A lead from a company a tenth your minimum viable size can download every asset you own, attend every webinar and reply to every email, and they are still not a buyer. Behaviour cannot promote a non-fit into a real lead, and a model that lets it do so is leaking your attention by design.

Intent is a timer

Intent is the behavioural and buying-signal layer, the answer to a different question: is now the moment? Pricing-page visits, demo requests, repeat sessions, the recency and density of activity that suggest a buyer has moved from idle curiosity into active evaluation. Intent does not decide whether a lead is worth your time, fit already settled that. Intent decides when. A perfect-fit account with no recent activity is not a lead to chase today, it is a lead to nurture until the timer fires. Treat intent as a clock, not a grade, and it stops competing with fit and starts complementing it.

The fit and intent quadrant

Plot fit on one axis and intent on the other and four cells appear, each with an unambiguous instruction. High fit and high intent is act now, the right buyer showing buying behaviour, the lead that deserves your fastest response. High fit and low intent is nurture, the right buyer who has not moved, kept warm until they do. Low fit and low intent is ignore, the easy discard. The dangerous cell is low fit and high intent, the seductive trap: a poor-fit account that is busy, lighting up your dashboard, begging to be chased. The single-number model loves this lead, because activity inflates the average. The two-axis model recognises it as noise and lets it pass, which is exactly the discipline a composite score cannot enforce.

Score the two axes separately, store them separately, and route on the pair. The moment you collapse them back into one figure to make a dashboard tidier, you have rebuilt the trap you spent this chapter escaping. The pair is the product. Guard it.