Player value · early metrics · hub
Early metrics: reading populations before day 30
On the first few days, players already behave differently — not only “retained” or “gone.” Some focus and return. Some focus once and vanish. Some return often but never go deep. If you only watch D1 / D3 / D7, those lives look similar until it is late to act.
This hub teaches a simple move: read early players as combinations of behaviours (show-up, return, depth, recovery, and later spend or social), not as one engagement score. We use the name AFITMRR™ for that seven-lens map — Attention, Frequency, Intensity, Tenure, Monetary, Referral, Resilience — but you can follow the argument in plain language first.
About this page. Teaching material: plain summary, practice contrast, composite examples, and an optional interactive walk-through. Mapping the same ideas onto your real events, weights, and live roadmap is partnership work when you want that depth.
On this page: What this changes · Journey at a glance · Interactive scroll · Examples · What to do next
What this changes in practice
Experienced teams already look at attention, return, session length, and spend. The shift is not “more metrics.” It is named combinations, direction of movement, and contribution weight — so the roadmap aims at a real population story, not an average curve.
| Common dashboard view | Combination read (AFITMRR™) |
|---|---|
| D1 / D3 / D7 as the main story | Early days matter because shapes stick — still ask which groups formed, not only how many returned |
| One “engaged” or “active” segment | Split pairs: high focus × thin return is not the same problem as high focus × high return |
| Average session or average spend | Volume vs contribution — a small group can carry most of the engagement KPI |
| Churn as a single rate | Where they sat before they left (healthy → broken vs never healthy) |
| “Fix retention” as one backlog | Name the weak behaviour on the heavy group before shipping the next feature |
Journey at a glance
The full argument fits in six steps. You do not need the animation to use them. (AFITMRR labels in small type are optional vocabulary.)
- 1 Start with everyone together One early population — not pre-sorted into vanity segments. AFITMRR: whole cloud before the cut
- 2 Cut by two behaviours (example) e.g. “Did they focus?” × “Did they return?” — four different lives, not one “active” bucket. AFITMRR: Attention × Frequency example
- 3 Colour for decisions Green = protect. Orange = can still turn. Red = learn / drop-off. Colours are working labels for your stage, not a universal scoreboard. AFITMRR: green / orange / red
- 4 Watch movement over days Who moves into healthier combinations? Who slides out of them? Direction matters as much as the snapshot. AFITMRR: paths into green vs into red
- 5 Organise the room’s focus Strengths to protect · opportunities to act on · challenges to face — three piles, not forty-two opinions. AFITMRR: strengths · opportunities · challenges
- 6 Ask one product question Knowing what you know — would you change anything about what you are shipping next? Close for the live room
Why the first days still matter
Same day (D0): first focus — or bounce. Day 1: did they return on purpose? Day 3: does the pattern stick? Later, tenure, spend, and social signals mature — but they are easier to read if you already know who was genuinely interested early, and who was already thin.
- D0 First contact Focus in the first session — or fog and exit.
- D1 Return Intentional come-back, or one-shot curiosity.
- D3 Stick Groups separate without waiting for day 30.
- Later Mature signals Spend, social, recovery — clearer if early groups were named.
Simple example: high focus and high return means habit is landing. High return with thin depth is a different product problem than rare visits that go deep. One “engagement” number hides both.
Optional · interactive
Walk the same story in motion
Scroll to watch populations move from one cloud → two-behaviour cut → colours → paths → focus. If you prefer not to scroll, the six steps above are the full argument.
Scroll to move through →
1 · Whole population
One cloud — not yet sorted into behaviour pairs.
What a conventional view can miss
The numbers below are composite teaching examples — stylised from patterns we see across live work, not published client metrics. They show the shape of a better decision, not a benchmark to copy.
Healthy D3, wrong spine
Dashboard: D1 and D3 looked acceptable; “engaged” users were growing after a UA push.
Combination read: A small high-focus / high-return group still carried most sessions. Day-on-day loss inside that group was high. The UA-fed mass was large and light on contribution.
Decision that changed: Pause acquisition spend aimed only at volume; ship recovery and cadence work for the heavy group first.
Why it matters: Average retention stayed “OK” while the business spine was bleeding.
One engaged bucket, two problems
Dashboard: Session length and “engaged days” looked fine after a difficulty tune.
Combination read: High focus × thin return (skill wall?) grew beside high return × thin depth (habit without a reason to stay). One “engaged” segment mixed both.
Decision that changed: Split the backlog — soft the wall for one group; add short, honest session payoff for the other — instead of one more global difficulty pass.
Why it matters: The same average session metric was hiding opposite product jobs.
Deeper teaching cut on volume vs KPI weight: Contribution weight (A×F base case).
Four early buckets (worked example)
Using focus × return as an example cut (not the only cut you will ever need):
| Behaviour pair | Plain read | Typical product question |
|---|---|---|
↑ focus × ↑ return |
Genuine interest | Protect and feed — do not break the habit |
↑ focus × ↓ return |
Engaged once, thin come-back | Difficulty, clarity, or appointment design? |
↓ focus × ↑ return |
Returns but shallow | Friction, load, or shallow loop? |
↓ focus × ↓ return |
Honest miss | Not your lasting pool — stop over-investing |
Mixed cases (e.g. spends early but never focuses; returns often but never recovers after a bad day) are opportunity briefs — act with a named lever, not analysis paralysis. Detail: four buckets, orange opportunity, strengths and neighbours.
What to do next
Chapters if you want more depth: D0–D3 & time · Buckets · Orange · Green & neighbours · Design meets needs. Glossary and contribution: combinations · contribution weight. Primer: seven lenses.
AFITMRR™ library
Related notes — start here, journey chapters, method.
Start here
- Primer · seven lenses
- Early-population journey hub
- Combination glossary
- Contribution weight · volume vs KPI load
Journey chapters · read in order
- D0–D3 & time
- Four housings & weighted types
- Orange opportunity
- Green focus & adjacency
- Design meets needs
Method & care
Try the lenses — or map them on your title
Use the free scorecard to feel the seven lenses. If you want the same combination read on your real events, cohorts, and live cadence, that is partnership work — weights, definitions, and roadmap choices stay with the title.