
Melissa
The Deal-First Rotator
Speaks for 243
A deal watcher who rotates Luvs with other brands and stays because it does the job for less.
StatSocial Focus Group · Luvs at 50
These buyers want performance first, then refuse to overpay for it. Every voice here is a composite of real parents who buy Luvs today, grounded in what they actually said. Ask them anything, then trace each answer to its source.
One question, all six answer.
Pull any parent aside.
Every answer traces to its source.
See it in action

QWhy Luvs over the pricier brands?

It holds up overnight as well as the names that cost more, so I am not paying extra for a label. With two kids, the money I save there goes somewhere it matters more.
The room
Moderator
6 of 6 questions left
The Deal-First Rotator
Speaks for 243
A deal watcher who rotates Luvs with other brands and stays because it does the job for less.

The No-Fuss Loyalist
Speaks for 188
She found the diaper that holds through the night and has not shopped the aisle since.

The Research-First Loyalist
Speaks for 174
She compared every diaper on the market before committing, and now Luvs is the only brand in her cart.

The Research-First Rotator
Speaks for 152
She researches every diaper purchase, keeps Luvs in the rotation alongside other brands, and sticks with it because it keeps passing her tests: real leak protection at a price that makes sense.

The Word-of-Mouth Loyalist
Speaks for 133
She buys what the moms she trusts swear by, and once Luvs proved itself on the first big blowout, it became the only diaper in her cart.

The No-Fuss Rotator
Speaks for 110
Luvs stays in her rotation because it handles the blowouts, keeps the price sane, and gives her one less thing to overthink.
The foundation
A StatSocial Focus Group runs on Digital Twins: respondents built from real people in PeopleGraph, our patented identity graph of roughly 150 million US adults, and the hundreds of observed behavioral signals in KnowledgeGraph. Each parent in this room stands for a real cohort of Luvs buyers. Identifying information is stripped before any response is generated, and every answer traces back to a specific respondent and rationale.
Every twin is an actual person from PeopleGraph carrying hundreds of observed behavioral signals, not a character a model dreamed up.
We match the sample to Census and Pew benchmarks across dozens of dimensions before generation, so it is representative by design, not by heavy after-the-fact weighting.
Across 30+ external benchmarks, Digital Twins land within an average 3.3 points of the measured result. They are checked against ground truth.
Open “See the data” on any voice to trace its answers to the cohort, the distribution, and the rationale behind them. Every claim is sourced.