Share of voice across ChatGPT, Perplexity, Claude, and Google AIO — measured across 8 shopper prompts and 30 brands.
Different AI models weight different sources. A brand that wins ChatGPT may lag in Google AIO if its retail footprint is weak.
Lovevery captures 31.7% share of voice across AI search engines in the baby-kids category, 11.7 points clear of the second-ranked brand and more than twice the share of the fifth. In a category where parents increasingly outsource pre-purchase research to conversational AI, that lead translates into a structural advantage that compounds with every training cycle and citation loop.
The competitive dynamic is bifurcated. The top five brands by SoV — Lovevery, Hanna Andersson, Primary, Monica + Andy, and Babylist — dominate the general-discovery prompts ("best D2C brands," "most popular," "premium"), though the gap to Frida at #6 is narrow. A second tier of specialists — Elvie, Willow, Frida, Hatch, Snoo — wins narrower functional queries around feeding, sleep, and postpartum. Four category-relevant tracked brands (Dock A Tot, Kabrita USA, Bitsy's, Nom Nom Snacks) register zero share of voice, alongside three adjacent-category names in the tracked set. The gap is not driven by product quality; it is driven by which brands have accumulated editorial citations in the sources AI engines weight most heavily.
For a brand sitting at 10–30% SoV, the next 90 days should focus on three things: identifying the two or three prompt clusters where the incumbent is weakest, seeding long-form editorial content with credentialed authors (pediatricians, OTs, dermatologists), and testing whether condition-specific territory (eczema, sensitive skin, allergen-free) can be claimed before competitors notice the vacancy.
Baby-kids is one of the most research-intensive consumer categories. A first-time parent asks questions a returning shopper in apparel or home goods never would: "is this safe for a newborn," "what do pediatricians recommend," "Montessori vs. traditional," "does this work for reflux." These are exactly the queries AI engines are built to answer in prose. The migration from Google's ten blue links to an AI summary is more consequential here than in categories where brand preference is already formed, because the AI answer often is the consideration set.
The shift is early and should be characterized honestly. Most baby purchases still begin on Amazon, Instagram, or through word-of-mouth from a specific friend group. But the top-of-funnel layer — the "who are the brands I should even be considering" question — is moving fastest toward AI. Our read is that a brand's AI visibility today is a leading indicator of its 2026–2027 consideration set inclusion, not a lagging indicator of current sales. That is why the 31.7% figure matters: it describes a position in the future default answer, not today's market share.
| Brand | SoV % | Avg Position |
|---|---|---|
| Lovevery | 31.7 | 1.9 |
| Hanna Andersson | 20.0 | 2.0 |
| Primary | 16.7 | 2.0 |
| Monica + Andy | 14.6 | 2.3 |
| Babylist | 14.2 | 1.9 |
| Frida | 11.7 | 3.4 |
| Elvie | 11.3 | 1.8 |
| Willow | 10.4 | 1.8 |
| Hatch | 8.8 | 2.4 |
| Pehr | 7.5 | 2.1 |
| Finn + Emma | 6.7 | 1.9 |
| UPPAbaby | 5.4 | 3.0 |
| Snoo (Happiest Baby) | 5.0 | 3.5 |
| Bobbie | 4.6 | 3.4 |
| Nanit | 4.2 | 3.8 |
| Owlet | 3.8 | 6.1 |
| Little Spoon | 2.9 | 2.7 |
| Doona | 2.9 | 2.4 |
| Cerebelly | 1.3 | 3.0 |
| Magnetic Me | 1.3 | 3.7 |
| ByHeart | 0.8 | 4.0 |
| Cradlewise | 0.8 | 6.5 |
| 4moms | 0.4 | 6.0 |
| Bitsy's | 0.0 | — |
| Kabrita USA | 0.0 | — |
| Nom Nom Snacks | 0.0 | — |
| Dock A Tot | 0.0 | — |
| Bogg Bag | 0.0 | — |
| Ruggable | 0.0 | — |
| BumbleBee Linens | 0.0 | — |
Lovevery's lead is built on editorial dominance of the Montessori-play and developmental-toy conversation. That conversation has been extensively covered in pediatric and parenting publications, and those sources are disproportionately represented in AI training and retrieval. Its 1.9 average position confirms it is consistently near the top of responses. Hanna Andersson and Primary play a different game — both win on apparel-anchored prompts and benefit from years of editorial coverage and brand familiarity, most pronounced in Hanna Andersson's case given its longer history.
The brand punching above its weight is Elvie, at 11.3% SoV with a 1.8 average position — tied with Willow for the best positional rank in the entire leaderboard. Elvie is mentioned less often than generalists but, when mentioned, is almost always named first or second. That signals strong category relevance in breast pumps and postpartum wellness, a defensible position that is hard for horizontal brands to dislodge. Babylist is the other notable case: its 14.2% SoV comes from being cited as a source (registry, buying guide) rather than as a product, which is a different and durable form of AI visibility.
The floor of the leaderboard tells its own story. Within the tracked set, four category-relevant names — Dock A Tot, Kabrita USA, Bitsy's, and Nom Nom Snacks — register zero mentions across 240 engine calls. These are not obscure businesses. They are brands that have not invested in the editorial surface area that AI engines draw from. (Three other zero-SoV entries in the tracked set — Bogg Bag, Ruggable, and BumbleBee Linens — sit outside or on the edge of the core baby-kids frame and should be read as category-adjacency checks rather than competitive signal.)
Lovevery dominates at 43.3% mention rate, with Monica + Andy (25%) and Primary (23.3%) well behind. ChatGPT leans heaviest on long-form editorial and "best-of" list content, which favors brands with sustained PR footprints. This is the engine where Lovevery's editorial advantage is most pronounced.
Much flatter distribution: Lovevery and Babylist tie at 16.7%, followed by Hanna Andersson at 11.7%. Perplexity's real-time citation model rewards brands that appear in recently updated buying guides and registry sites, which explains why Babylist (itself a guide publisher) performs disproportionately well here.
Gemini is where category leaders compound hardest. Lovevery posts its single highest engine rate here at 46.7%, and Hanna Andersson peaks at 35.0% — the top of its engine distribution. Primary (18.3%), Monica + Andy (16.7%), Elvie and Hatch (both 15.0%) all overperform their overall SoV on Gemini, suggesting the engine retrieves heavily from mainstream parenting and apparel editorial that favors established D2C names. For an incumbent, Gemini reinforces position; for a challenger, it is the hardest engine to move quickly.
Babylist leads at 21.7%, ahead of Lovevery at 20%. Google AIO mirrors traditional SEO signals more closely than the other engines, and Babylist's registry authority translates directly. Hatch is observably stronger here (11.7%) and on Gemini (15.0%) than on ChatGPT (5.0%) or Perplexity (3.3%), an uneven engine profile worth watching but one the data does not yet let us attribute to a specific driver.
Four distinct clusters emerge from the winning-prompt data, each won by a different brand logic.
The Generalist Discovery cluster ("best D2C baby brands 2026," "most popular in the US," "top D2C companies for new parents") is the most contested and most valuable. Lovevery, Hanna Andersson, and Primary all surface here. Winning requires broad editorial mentions in category round-ups rather than product-specific content.
The Montessori and Developmental Play cluster ("toddler playtime," "Montessori-inspired play," "subscriptions," "gifts for new parents") is effectively owned by Lovevery. The brand has built such strong semantic association with Montessori-for-babies that it appears even in prompts that do not explicitly mention play.
The Apparel and Gifting cluster ("newborn essentials," "baby shower gifts," "eco-friendly") splits between Hanna Andersson and Primary, with the former winning gifting and the latter winning value/affordability frames.
The Value Tier cluster ("affordable," "cheap but worth it," "best value," "premium worth the money") is almost entirely Primary's. Primary has positioned itself at the intersection of price and quality in a way that AI engines now repeat verbatim.
The Functional Specialist cluster (feeding, pumping, sleep, monitoring) is where Elvie, Willow, Frida, Hatch, and Snoo compete. Their SoV levels are materially below the leaders, but the positional data (1.8 average for both Elvie and Willow) shows these brands rank highly when they are mentioned — strong specialist relevance rather than category-level ownership.
The leaderboard and engine data make clear that certain condition-specific and need-specific framings are thinly served by tracked D2C brands. While prompt-level empty-space confirmation is beyond the scope of this snapshot and should be validated in a follow-on study, the hypothesis is straightforward: claiming "best D2C brand for eczema" or similar narrow framings likely requires a smaller editorial investment than displacing Lovevery on "best Montessori toys," where the incumbent has a multi-year lead.
Based on the gap between known parent search behavior and the distribution patterns visible in our data, the five most strategically promising unclaimed or under-claimed territories in this category are as follows. These are hypotheses to test, not measured vacancies.
Each of these is likely cheaper to test than to contest an incumbent. Directionally, early authoritative content in under-covered prompt areas appears to carry an advantage, though the durability of that advantage varies by engine and should be re-measured as retrieval layers evolve.
For a brand currently at 10–30% SoV, the ceiling is not another five points of general-discovery share; it is category ownership of two or three narrower prompt clusters. Three 90-day moves, in sequence.
Move 1 (Days 1–30): Commission credentialed editorial in one under-claimed cluster. Pick one of the five territories above and validate the prompt gap directly. Commission a single long-form piece authored by a named pediatrician, OT, or pediatric dermatologist, and place it on a publication with editorial authority — not your own blog. One piece, one author, one publication. Measure SoV lift on the target prompts at day 60.
Move 2 (Days 30–60): Seed buying-guide inclusion on Babylist, The Bump, and Wirecutter-equivalent sources. Our engine data shows Babylist is not just a competitor but a citation source, particularly in Perplexity and Google AIO. Babylist appears to be an influential citation source in this category, and inclusion in its registry guides is a visibility asset that the top of the leaderboard disproportionately enjoys. The work here is PR and merchandising coordination, not paid media. Target inclusion in three round-ups within 60 days.
Move 3 (Days 60–90): Publish a structured comparison page on your own domain. AI engines increasingly cite structured, comparative content (tables, pros/cons, "best for X" framing) from brand-owned domains when third-party sources are thin. The page should compare your product against two named competitors on five or six attributes. This is the one place where self-published content performs, because it fills a structural gap AI engines have in lesser-covered sub-categories. Do not write it as marketing copy. Write it as a review.
The common thread: do not try to beat Lovevery at Montessori. Own a cluster it does not.
This analysis is based on 240 engine calls distributed across ChatGPT, Perplexity, Gemini, and Google AIO, covering 60 shopper prompts designed to mirror real D2C query distributions in the baby-kids category (general discovery, value tier, condition-specific, gifting, and functional sub-categories). Thirty brands were tracked. Share of voice is calculated as the percentage of prompts in which a brand was named in the engine's response. Average position is the mean ordinal rank of the brand across mentions, where position one indicates first-named. The study is a point-in-time snapshot; AI engine outputs shift with model and retrieval updates, and rankings should be re-measured quarterly. Prompt-level empty-space analysis (the "unclaimed territory" hypotheses) should be validated in a follow-on study that captures full response text per prompt.
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