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Teardowns

Teardowns

The score, all five dimensions and the finding are public. The full read is for members.

FoodserviceCategory Leader

Starbucks Rewards

The global benchmark: an app that captures everything, a streak mechanic that builds habit, and a stored-value balance that funds the program.

86
GroceryCategory Leader

PC Optimum

A first-party data trove resolved at scale, monetized by a media network that comfortably outearns the cost of the reward.

85
RetailCategory Leader

Sephora Beauty Insider

An aspirational status mechanic that brings members back by desire, funded by a product margin that absorbs the reward.

82
RetailStrong Contender

Scene+

A coalition that works where most fail: data spans grocery, banking, and entertainment under a single currency.

73
GroceryStrong Contender

Metro & Moi

High-quality grocery data held back by a media monetization that’s nowhere near its potential.

71
FoodserviceStrong Contender

Tim Rewards

Daily frequency that generates rare habit data, paid for by a reward that weighs heavily on margin.

69
RetailFunctional

SAQ Inspire

Exceptional category data, capped by a public mandate that limits both monetization and the aggressiveness of the mechanic.

63
GroceryFunctional

Nectar

A vast legacy base whose value stays locked: coalition heritage and a modest activity rate hold activation back.

59
OtherLaggard

Air Miles

A legacy coalition whose data sleeps and whose margin leaks: dented trust, high redemption friction, weak relevance.

45