Beauty Consumer Research in India: How to Survey Makeup, Skincare and Haircare Users

Pick one rule per study and print it in the questionnaire header. Three common rules:

Keep makeup, skincare and haircare as separate studies or separate quota cells. Their buyers, shops and decision speed differ. For a women-only read on shopping and decisions, see women consumer research in India.

Point the study at the city, age and gender you need, then let a screener confirm category use. No beauty category or brand field is documented, so ask which behavioural segments exist and always screen. See how audience targeting works and the any-audience guide.

Place the screener first, show the category list in random order, and do not reveal the qualifying answer. Brand names appear only as answer options.

Ask the shade question as what people say they use. A survey cannot check whether a shade matches skin. Chart the funnel by quota cell, not only for the total.

YouGov, makeup-wearers. YouGov's Profiles sample of 9,498 urban Indians who wear makeup, interviewed online from August 2020 to August 2021, found 41% had shopped for beauty and cosmetic products online in the past month, and 43% lived in a Tier 1 city. Of these makeup-wearers, 65% said recommendations in articles or product reviews drive their trial of new cosmetics, and 42% said friends and family do (YouGov, 28 September 2021). The base is urban and the data is older, so use it as a hypothesis, not a benchmark.

Kantar, cosmetics panel. On 4 December 2023 Kantar launched a cosmetics panel in India, tracking purchases by more than 3,000 women aged 18-44 in NCCS A and B. It reported that in its first phase, 40% of cosmetics shoppers bought online but only 7% bought exclusively online, and that the ability to try before buying remained important to most shoppers (Kantar press release). It also said 70% of lipsticks bought were the traditional bullet format.

Both sources point the same way for a survey designer: channels are mixed, reviews matter, and trying the product still matters. Ask about each channel separately, since marketplaces, brand stores and kirana shops answer different jobs.

Illustrative only. Say you want 400 recent makeup users in four cells of 100: ages 18-24 and 24-35, in Tier 1 cities and in other cities.

Incidence is explained in the any-audience guide; these figures are placeholders, not our panel's rates. At 100 per cell, a share near 50% has a margin of error of about 9.8 points (1.96 × √(0.25 ÷ 100)). The total of 400 gives about 4.9 points. Compare cells only when the gap is clearly larger than that.

A survey asks people what they think. It does not put a lipstick on their lips. A physical shade or texture test needs a venue or sampling programme outside our platform. Our survey can test images, names, packs and claims only. For testing claims and concepts by survey, see product testing surveys in India. For a pack or logo test that needs only images, see the skincare brand blind test.

Generic questions on verification, duplicates, billing and languages are in the any-audience guide. For beauty, also ask:

• What is your feasibility count for my category and age band in my cities, and for one named brand?
• Is category use confirmed by a screener, and can I add product-type and channel questions?
• Do you reach kirana and offline buyers, or smartphone users only?
• If I need shade or texture trials, which of them can you not support?

This category screener and four-cell study suits an online survey of smartphone-using Indians; at list price it costs:

Panel facts, verification and the subset caveat are on panel methodology; plan prices are on pricing. Screened-out respondents do not count towards a response bundle.