How to Survey Users of a Specific Brand in India

"User" can mean six different people. Pick one definition per cell and write it into the screener. Match the recency window to the buying cycle: a month for a daily-use product, 12 months for a car. These windows are our advice, not a standard.

Purchaser and user differ more than researchers expect. A parent buys a product that a teenager uses. Ask who buys and who uses, then decide whose answers you need.

Brand funnels split awareness in two. One brand-tracking vendor defines unaided awareness as an open-ended question about whether a respondent can recall your brand unprompted, and aided awareness as how many have heard of it. It measures usage as a share of aided awareness (Latana).

Practical order: ask the open-ended brand question first, before any list appears, so the list does not prime it. Then show the list and ask about use.

Build the list with the brand, five or six real rivals, one or two decoys and "none of these". A decoy is a plausible name that does not exist. The screener rules in the audience hub apply here. Remove anyone who claims a decoy, because they may be guessing.

Randomise the list order. If the brand has several products, ask a second question at product level: which lipstick, which model, which pack. People often know the name but not what they use. Check the answer against the product list.

• Naming the brand in the invite or title. ESOMAR's buyer questions note that the information given about a project in an invitation may influence response (ESOMAR, 28 Questions to Help Buyers of Online Samples, 2012 edition, question 13). Use a neutral topic such as "shopping habits".
• Asking brand opinions before the screener ends. Opinions asked early reveal who you want.
• A fixed list order. The first names get more ticks.
• A long recency window. People forget and over-claim.
• Mixing cells. Users, lapsed users and rival users must stay separate in analysis.

Comparison cells also need comparable people. Set quotas by gender, age band and city in each cell so a gap reflects the brand, not the mix. Our platform supports interlocking quotas across gender, age and city.

Illustrative wording for a makeup brand. Swap the category for a car by asking which cars the household owns.

1. Which of these have you bought in the last 12 months? (Makeup, skincare, hair colour, fragrance, none of these). Continue if makeup.
2. Which of these makeup brands have you used in the last 3 months? (Brand A, five real rivals, one decoy, none of these). Randomise the order.
3. Remove anyone who ticks the decoy.
4. Which product from that brand did you use? (A list of its products, including one it does not make.)
5. Who bought it? (Me, someone else, shared in the household).
6. How often do you use it? Route by the answer to the cell: user, lapsed or rival user.

Illustrative shares, not real rates. You want 300 completes in each of three cells. One screening stream fills all three at once, as people qualify.

Calculation: 300 ÷ 0.12 = 2,500; 300 ÷ 0.18 = 1,667; 300 ÷ 0.09 = 3,334 (rounded up). The cells fill from the same stream, so you do not add them. The rarest cell, lapsed users, sets the total at about 3,334 people screened.

Decoys remove some people. If 4% of the 2,500 claim a decoy brand, that is 100 people out. Add them to the number screened. If one person fits two cells, fix a priority rule before launch. Use in-survey over-quota routing to close a cell when it fills, and ask the team which screener answers can carry a quota.

1. Do you hold a profile field for this brand, and how old is it? If not, expect a screener.
2. What feasible count do you give for my cell, with a range?
3. How do you remove decoy-claimers and inconsistent answers?
4. Can I set quotas by gender, age and city within each cell?
5. How are invites worded, and can I see them?
6. Which languages can the screener run in?

For the wider checklist, see the audience hub and verified respondents. For brand health over time, read brand tracking.

Brand use is self-reported. A screener cannot check a purchase receipt. The panel is smartphone-only and India only. We publish no counts of users of any brand, and feasibility depends on how common the brand is among members.

If your job is a brand-user survey in India with a screener and three cells, this is the 900-response study at list price. Screened-out respondents do not count towards a response bundle.

Pro is sold in bundles of 400 to 1,000 responses and costs 20% less per response than Plus. Enterprise pricing is custom.

The SuperJ network has a 25M+ consumer footprint. The survey-eligible panel is a subset, and availability depends on your targeting. Verification details are on /panel-methodology and pricing.

The limit: the app reaches smartphone users only.