StatSocial Focus Group · Luvs at 50

Six shopper personas.
A thousand real Luvs buyers behind them.

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.

Ask the room

One question, all six answer.

Talk one-on-one

Pull any parent aside.

See the data

Every answer traces to its source.

7.55/10
Mean loyalty to Luvs
56%
Buy Luvs most often
38%
Rank leak protection first
1,000
Real buyers, screened and calibrated

See it in action

A sample session, grounded in real answers.

Example sessionLuvs buyers · The Deal-First Rotator
Melissa
The Deal-First Rotator · composite of 243

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.

Every answer traces to a real respondent. Ask your own below ↓

The room

Put one question to all six, or pull a parent aside.

Moderator

6 of 6 questions left
Portrait of Melissa

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.

Follows deals, buys what is on saleRotates Luvs with other brandsBuys at Walmart
Portrait of Jasmine

Jasmine

The No-Fuss Loyalist

Speaks for 188

She found the diaper that holds through the night and has not shopped the aisle since.

Luvs only, never rotatesLeak protection firstLoyalty 8.4 of 10
Portrait of Kelly

Kelly

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.

Researches every purchaseLuvs only, no rotatingLeak protection first
Portrait of Taylor

Taylor

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.

Researches every purchaseLuvs plus other brandsLeak protection first
Portrait of Danielle

Danielle

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.

Buys on trusted word of mouthLuvs only, no rotatingLeak protection first
Portrait of Rachel

Rachel

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.

Buys at TargetLeak protection firstRotates brands, Luvs default

The foundation

Real people. Identity stripped. Answers you can trace.

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.

~150M
US adult records in the PeopleGraph identity graph
~50M
meet our behavioral-depth threshold and form the Digital Twins panel
1,000
screened Luvs buyers, drawn and calibrated to benchmarks before any response is generated

Real people, not invented personas

Every twin is an actual person from PeopleGraph carrying hundreds of observed behavioral signals, not a character a model dreamed up.

Calibrated before the model runs

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.

Validated against the benchmarks

Across 30+ external benchmarks, Digital Twins land within an average 3.3 points of the measured result. They are checked against ground truth.

Traceable end to end

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.

StatSocial

How this room was built: k-means, k=6, features = one-hot of [sole/rotator, buying approach, value meaning, loyalty band] plus the full 6-driver rank vector, fixed seed 42, n_init=50; every cluster occupies a unique (buying approach x sole/rotator) combination. The six shopper personas are composites of the 1,000 screened current Luvs buyers in the study. Their replies are generated, grounded in each group's recorded answers and rationales; open “See the data” on any voice to read the source. Spend figures are self-reported estimates.