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Last updated on Sep 13, 2026
The Advanced Subscription Momentum Report tells you how much MRR you gained and lost this quarter. It cannot tell you whether the customers you signed two years ago are still holding up, or whether the customers you signed last quarter are churning faster than any group before them. That is what the Cohort Report is for: it splits your book into "like groups," lines them up so you can compare them, and shows you how each group's value changes over time.
This article explains what each of the report's levers is for — the four ways to line up the columns, the two percentage views, expanding a cohort into its own Momentum categories, and row ordering — each with a grounded example. For the full list of settings, see Analyzing Customers Using the Cohort Report.
A cohort is any group of customers that share a trait. The classic one is the "class of" — every customer whose first transaction started in the same month — and the report's Cohort setting offers that directly as Customer: Earliest Start Date, by month, fiscal quarter, or fiscal year. But a cohort can equally be a register, a product family, a country, a contract entry date, or any custom field you have defined on customers, contracts, or transactions — industry, acquisition channel, sales rep. Each cohort becomes a row; each period becomes a column; each cell is the MRR, ARR, amount, quantity, or customer count that cohort carried in that period.
Momentum answers "what happened to the total?" The Cohort Report answers "which group made it happen?" — and, because no new customer can ever join a signup-month cohort after the fact, its value curve is driven entirely by what the customers already in it do: renew, expand, contract, or leave. That makes it the cleanest view of net retention you can get — the curve can rise as well as fall, and a rising one means expansion is outrunning churn.
The Report By setting decides what a column means, and that decision is what turns the same data into four different analyses.
Time puts calendar periods across the top. Each cell is the value that cohort carried on the last day of that month, quarter, or year. Suppose three customers started in January 2023 — A at $1,000 MRR, B at $500, and D at $200, though D's contract ended on January 20 — and C started in February at $300. The "2023-01" row shows $1,500 in January (D is not active on January 31, so it contributes nothing) and $1,500 again in February; the "2023-02" row shows $300 in February. Use Time when the question is about the calendar: what did each signup vintage contribute to this quarter's MRR?
Duration throws the calendar away and aligns every cohort on its own start: "Month 1" is each customer's first month from their actual start date, "Month 2" the second, and so on. Customers who started in January, March, and July all stack into the same Month 1 column. Use Duration when the question is about lifecycle: what does a customer look like six months in, regardless of when they signed? This is the shape you want for a retention curve.
Elapsed is Duration aligned to month boundaries — a customer's Month 1 runs from the first of the month they started, not from their exact start date. If your transactions are prorated so they start mid-month and end at month end, Elapsed keeps the first period from being clipped short and reads the way your MRR schedules do.
Term ignores dates entirely and uses the transaction's Term Number: "Term 1" sums every first-term transaction, "Term 2" every first renewal, and so on. Use Term when the question is about renewals: how does contract value change from the initial term to the first renewal to the second? It works best for clean subscription models, because Maxio's term numbering gets less reliable as mid-term upgrades, extensions, and other changes pile up.
The Display setting turns absolute values into one of two percentage views, and they answer different questions.
Percentage of Start Period divides every cell by the cohort's first period in the report window. On a Duration report this is the retention curve in its purest form: if the January 2023 cohort shows 100%, 96%, 91%, 88%, 88%, 87% across Months 1 to 6, you are looking at how much of its starting MRR that vintage kept. Run it for several cohorts and you can see at a glance whether newer vintages are retaining better or worse than older ones at the same age — the question a plain Momentum churn rate can never answer, because it blends every vintage together.
Percentage of Previous Period divides each cell by the one before it, so the curve becomes a period-over-period rate. The same cohort reads 100%, 96%, 95%, 97%, 100%, 99%: losing value early, then stabilizing. Use it when you want to find when a cohort's value loss concentrates — the Month 2 and Month 3 dips above point at the onboarding window — rather than how much has been lost cumulatively. On an MRR or ARR report a dip alone cannot tell you whether customers left or merely downgraded; to attribute it, expand the cohort into its Momentum categories (below) and read Lost against Contraction, or run the same report with Customer Count as the metric if the question is specifically about logo churn.
One thing to know about the baseline: the "start period" is the first period in your report window that has a value, not the cohort's first month of existence. If a Time report starts in 2024 and a cohort began in 2022, its 100% is January 2024. Set the date range to include the cohort's true start when you want a genuine retention-from-inception curve.
By default a cohort row is a single number per period. The Detail Expansion setting can instead expand each cohort into its own Momentum categories — Opening, New, Expansion, Contraction, Lost, and End of Period — computed with the same interpretive logic as the Advanced Subscription Momentum Report, including reading Lost from the absence of any future transaction rather than from a cancellation flag.
This is the difference between knowing a cohort's MRR fell from $50,000 to $46,000 and knowing that it lost $6,000 to churn, contracted by $1,500, and expanded by $3,500 — three very different stories with the same net. Run the expansion on a Time report cohorted by product family or register, and you get a Momentum waterfall per segment, side by side, in one report.
The expansion also unlocks Short Lost. Turn on the special Short Lost category with a minimum number of periods, and any customer who was New and then Lost within fewer periods than that is separated from the rest of Lost. A cohort that shows $6,000 Lost with $4,000 of it Short Lost has an early-exit problem — customers who never really landed — rather than a base that is eroding, and those call for different fixes. Detail expansion is available when the report is by Time and the metric is MRR, ARR, Amount, Quantity, or a numeric custom field; it is not available when the cohort itself is an earliest-start or fiscal-period field.
With dozens of cohorts, Cohort Row Order decides what you see first. Ascending and Descending sort by the cohort label. The other three sort by value: First Period (High to Low) surfaces the cohorts that started biggest, Latest Period (High to Low) surfaces the ones worth the most today, and Total (High to Low) surfaces the ones that contributed most across the whole window. Comparing the first two orderings is a quick way to spot vintages that started strong and faded — or started small and grew. Period Direction flips the columns to run newest to oldest without changing any calculation.
For every setting, the transaction date rules, and the Transaction: Number cohort that bridges to the Momentum drill-down, see Analyzing Customers Using the Cohort Report.
For the Momentum categories the detail expansion produces and how they are calculated, see Understanding the Advanced Subscription Momentum Report, and for what the Momentum Report itself is built for, see What You Can Do with the Advanced Subscription Momentum Report.
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