DUC, daily unique converters, answers how many people earned something today. It is deliberately different from a conversion count, and the gap between the two numbers is one of the more useful things a wall can tell you.

How to calculate DUC

DUC = Distinct users with at least one completed offer that day

DUC = Distinct users with at least one completed offer that day

DUC = Distinct users with at least one completed offer that day

A quick example

A wall records 1,400 completions in a day across 500 distinct users:

Conversions = 1,400
DUC         = 500
Offers per converter = 1,400 / 500 = 2.8

Conversions = 1,400
DUC         = 500
Offers per converter = 1,400 / 500 = 2.8

Conversions = 1,400
DUC         = 500
Offers per converter = 1,400 / 500 = 2.8

Almost three offers per converting user is a strong signal: the people who engage are finding several things worth doing rather than completing one and leaving.

What counts as a good DUC?

• Read it against DEU. DEU divided into DUC gives the conversion rate for engaged users, which is the number that reflects offer fit.

• Watch offers per converter. A rising ratio means existing converters are going deeper, usually an offer-supply win.

• Distinguish the two growth paths. Rising DUC with a flat ratio means the wall is reaching new people; a rising ratio at flat DUC means it is monetizing the same ones harder.

• Expect it to be a small share of DEU. Most users who browse a wall do not complete anything that day, and that is normal.

DUC vs. conversions

Conversions measure activity; DUC measures people. Reporting only conversions makes a wall look healthier than it is when a handful of heavy users are generating most of the volume, because a small, highly active group and a broad, lightly active one can produce identical conversion counts. A concentrated converter base is more fragile, and only DUC reveals the concentration.

How to improve it

• Widen the low end of the offer mix. Rewarded surveys and quick actions convert users who will never install anything.

• Reduce time to first reward. A user who earns something on their first visit is far likelier to return.

• Fix failed completions. Users who complete an offer and are not credited rarely try a second time.

• Match offers to the audience. Geography and platform mismatches show up here before they show up in revenue.

Common mistakes to avoid

• Using conversions and DUC interchangeably. They answer different questions and diverge most when it matters most.

• Ignoring concentration. A wall carried by a few heavy users is one churn event away from a revenue problem.

• Reading DUC without DEU. Alone it cannot distinguish a discovery problem from a conversion one.