Strategy & Tracking
Cohort Analysis
Grouping customers by a shared starting point — like signup month — to see how their behavior and value differ over time.
Definition
Cohort Analysis groups customers by something they share at the start, such as the month they first hired you, then tracks how each group behaves and spends over time. It reveals patterns that a single blended average hides.
In depth
Cohort Analysis sorts customers into buckets by a common origin — the month they first booked, the channel that brought them, the offer they responded to — then watches each bucket over the following months. Instead of one fuzzy average, you see whether June's customers spend more than January's, or whether a price change improved repeat work.
For a contractor, cohorts turn vague trends into decisions. You might find that spring leads come back for second projects far more than fall leads, or that customers from referrals stick around longer than those from one ad set. That tells you which months to push hardest and which sources carry a higher customer lifetime value than their cost per lead alone suggests.
The common mistake is judging marketing on this month's blended numbers, which mixes brand-new and long-loyal customers into one misleading figure. We pull cohorts from the first-party data in your CRM so changes show their true effect over time, and so a channel that looks expensive up front but loyal over the year gets the credit it deserves.
Worked example
You compare customers won in March versus September. By month six, the March cohort has booked 1.4 jobs each on average while September's has booked 0.8 — telling you spring buyers are worth chasing harder.
Strategy & Tracking
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Clean tracking and honest attribution, so you know which dollars actually produce revenue.