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Measurement use cases

10 recipes where the outcome is measurement, each written out in the same seven boxes. The patterns they compose most often: signal quality monitoring, audit trail generation at the decision point and server-side event collection with client-side fallback.

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Cohort analysis for product engagement

Medium-low readiness

Group users by when they signed up or first acted, then watch each group's engagement curve, so a quiet quarter doesn't disguise a real shift in who is sticking

Weeks·Measurement·B2B SaaS·Multiple·Composable stack·3 patterns

Conversion event quality monitoring

Medium-low readiness

Watch the conversion events at the resolution that catches a deploy breaking the cart-success fire before reporting starts surprising people, and surface the fix as an operational alert rather than a quarterly investigation

Weeks·Measurement·Cross vertical·Multiple·Composable stack·3 patterns

Event schema standardization

Medium-low readiness

Define the events once, version them, and enforce the shape at write time, so analytics, activation, and reporting work against one data contract rather than negotiated reconciliations

Weeks·Measurement·Cross vertical·Multiple·Cross archetype stack·3 patterns

Server-side conversion tracking for paid social

Medium-low readiness

Reclaim the conversion signal you lost to browser-side tracking decay

Weeks·Measurement·Cross vertical·Multiple·Cross archetype stack·3 patterns

Server-side event collection with client-side fallback

Medium-low readiness

Make the server the primary record of what happened, with the browser as the backup rather than the system of truth

Weeks·Measurement·Cross vertical·Multiple·Cross archetype stack·3 patterns

Attribution credit allocation rules

Medium-high readiness

Pick an attribution model, lock it, document why, and reconcile its outputs against incrementality, so the channel report becomes one rule the team can defend rather than a debate per meeting

Months·Measurement·Cross vertical·Multiple·Composable stack·4 patterns

Incrementality testing for paid channels

Medium-high readiness

Measure the lift a channel actually adds by running a holdout, not the correlation between exposure and conversion the channel's own report shows

Months·Measurement·B2C ecommerce·Multiple·Composable stack·4 patterns

LTV with a predicted component

Medium-high readiness

Combine realized revenue with a predicted future, and carry the model's uncertainty into the decisions LTV drives, so the bid that depends on it knows what it is standing on

Months·Measurement·B2C subscription·Multiple·Composable stack·4 patterns

Cross-channel paid attribution with consent fallback

High readiness

Measure paid channel contribution honestly when tracking is partial, by separating what you observed from what you modeled

Quarters·Measurement·Cross vertical·EU GDPR·Composable stack·4 patterns

Marketing mix modeling inputs

High readiness

Get the unified spend, exposure, and conversion data clean enough for the model to produce decisions you can act on, not directional outputs that need a footnote

Months·Measurement·B2C ecommerce·Multiple·Composable stack·4 patterns
Measurement martech use cases · martech cookbook