Equal FTD counts can hide very different cohorts

Put two sources with equal FTDs next to each other. The first line looks like a draw. Then follow those players: one group keeps depositing, the other adds very little. A weekly cohort table makes that difference visible at the same age. Keep the geo and the players unchanged throughout, so an older group cannot win simply because it has had longer to pay.

The week tells you who belongs in the group

A deposit cohort is the group of players whose FTD fell in the same week. That is their entry point. Their later payments stay in that group, even when the money arrives in a different reporting week. Otherwise a returning player keeps appearing as a new result and the table loses its purpose.

The group doesn’t shrink to the players who came back. Players who never deposit again stay in it too. Removing them would inflate repeat-depositor share even though nobody’s behaviour changed.

Check which event put the player in the row. A registration date and an FTD date can both produce a weekly table, but one tracks the route to payment and the other tracks what followed it. The deposit report covers the conversion view and the underlying player counts. Choose the source rule before the test. A later visit through another link should not quietly move a player from one cohort to another. If the original source was wrong, correct the record and show the change. The row should still mean “these players made their FTD in this week, attributed to this geo and creator type” when somebody opens it later.

The clock starts with each player’s FTD

Players in the same weekly row arrived on different days. At a calendar cutoff, the earliest arrival has had longer to deposit again. Give each player the same elapsed time from their own FTD, then add up the payments inside that window. The week groups the players while each keeps their own clock.

The table can compare every row in the short window, only the older rows in the medium window, and only the oldest row in the longer window. A timezone and an exact boundary rule belong beside it so the next export uses the same clock.

Equal FTDs can lead to different deposit totals

The first payment gets the player into the cohort. After that, two things can pull results apart: how many players deposit again and how much they add. Equal FTDs tell you neither. Looking only at that count can hide the whole reason to follow cohorts.

That gap is the reason to keep following the players. The next question is whether it appears in another complete weekly group or depends on this one. The comparison of creator types puts those differences in context. The result still comes from the test.

Repeat-depositor share shows how widely players return

A repeat depositor is a cohort member with another successful deposit inside the chosen window. Repeat-depositor share shows how much of the original group did that. Use the same complete window for the player count and the deposit total beside it.

Repeat-depositor share = repeat depositors inside the window ÷ FTDs in the cohort × 100

The repeat-depositor share is what keeps us from getting carried away by a large deposit total. A high total can sit on a narrow group of returning players. That money belongs in the report, but a source decision needs to show how dependent the result is on those players.

A quick brand-side check is to sort the cohort’s deposit amounts and see how much comes from its largest depositors. The brand can do this in its own player data. It can explain why the next weekly group behaves very differently even when the headline FTDs look similar.

Keep the meaning narrow. Repeat deposits show payment behaviour. A wider question about continued play needs the brand’s activity data alongside it. The cohort row can carry that extra measure if the team needs it, with a clear name and the same time boundary.

A young cohort still has time left

The newest row is unfinished. That sounds obvious until it appears at the bottom of a report with the smallest deposit total and somebody calls it the weakest source. It may simply have had less time.

For a complete weekly result, wait until the last player in that group has reached the end of the chosen window. Earlier players reaching it does not close the row. Including only those earlier players would change the group you are comparing.

You can still show progress while a window is open. Call the amount “so far” and keep it outside the completed-window ranking.

Once every player has had the agreed time, check that the export covers it. A delayed export leaves a gap even in an old cohort. Waiting for the players to age won’t supply the missing payments. Use the tracking checks to find what has not arrived.

The next review date follows from the youngest player’s FTD and the window still open. Put that date beside the open window so everyone knows when to read it again.

Combine the counts before the percentages

Weekly rows let you see whether repeat deposits keep appearing or came from one strong week. A combined result helps too, provided every included group has completed the same window. Add their player counts first, then calculate the combined share.

The larger week needs its proper weight. Keep both weekly rows under the combined figure so somebody can see where it came from. Changes in weekly cohort size, payment availability or creator type should remain visible; otherwise one headline smooths away the explanation.

If a cashier interruption affected a week, attach it to that row. The combined result still describes the payments received, but the affected week cannot tell you much about the audience until the product problem is understood.

The test can end before the last cohort closes

The launch period and the cohort follow-up have different finish lines. Players arriving near the end of a test can still have longer windows open after new traffic stops. Agree the follow-up export while planning the test volume, so those players do not disappear from the final discussion.

InfluEdge can add repeat deposits and weekly cohorts at the brand’s request. Complete weeks show the deposit behaviour the brand can already compare. Longer windows still running may change that picture, so keep their follow-up dates beside the current result. If payments are disputed, resolve the records before using those weeks to compare sources.

Those windows stay open after new traffic ends. Read them on the dates agreed, with the same players still in each row.