Consumer research and usage & attitudes (U&A) studies

Questions this report answers

• Who buys in our category, and how big is each buyer group?
• How often do people buy, through which channels, and how much do they spend per occasion?
• Which needs and usage occasions are poorly served today?
• What makes a shopper pick one brand or retailer over another?
• Which barriers keep non-buyers and lapsed buyers out of the category?
• How do habits differ between countries, age groups, and heavy and light users?
• Which consumer groups should we prioritise for a launch or a repositioning?

When you need it

A U&A study is most useful when you need a map of the whole category, not only of your own customers. Sales and CRM data show what existing buyers did; they say nothing about people who buy from competitors or have never entered the category.

Four situations come up repeatedly:

• Entering a category or a country. Before committing to a range, channel mix or media plan, you need to know how local consumers actually shop.
• Preparing a segmentation or repositioning. A segmentation study relies on the needs, attitudes and behaviour data a U&A survey collects.
• Your picture of the consumer is out of date. According to Eurostat, the share of EU individuals aged 16–74 who bought online in the previous 12 months rose from 64.7% in 2020 to 73.6% in 2025.
• Sentiment has shifted. Eurostat's consumer confidence indicator for the EU stood at −17.3 in October 2026, against −12.7 a year earlier, so last year's spending intentions may no longer hold.

You probably do not need a full study if the question is narrow. To choose between two product ideas, a concept test is faster; to set a price point, commission pricing research.

Sample table of contents

1. Executive summary
   the findings that matter, each with a recommended action
2. Objectives and methodology
   sample, fieldwork dates, quotas, weighting, margins of error
3. Category penetration and buyer profile
   who buys, by demographics and attitudes
4. Usage patterns
   frequency, volume, occasions, in-home versus out-of-home
5. Path to purchase
   online versus in-store, retailer choice, information sources
6. Needs and motivations
   functional and emotional needs ranked by importance
7. Purchase drivers and barriers
   stated and derived importance of each choice factor
8. Brand repertoire
   awareness, consideration, usage and loyalty among category buyers
9. Heavy users, light users and non-buyers
   where the volume sits and what would grow it
10. Consumer profiles
    portraits combining data with anonymised verbatims
11. Implications
    what to do, in which order, and what to measure

Methodology and sources

Desk research and universe definition

We start with official statistics from Eurostat and national statistics institutes, plus any sales data you hold. This defines the population, quotas and hypotheses to test.

Qualitative exploration

Eight to fifteen in-depth interviews, two to four focus groups or a one-week mobile diary capture the occasions, words and trade-offs consumers use themselves. That language then feeds the questionnaire.

Quantitative survey

The core is usually a CAWI survey on an online panel, with quotas on age, gender and region; CATI or CAPI covers groups that are hard to reach online. A total sample of about 385 gives a margin of error of ±5 points at 95% confidence, and each subgroup you want to report separately needs roughly 100 interviews or more. Our sample size calculator shows the trade-offs. A low incidence rate matters too: if only one adult in five buys the category, five people must be screened for each completed interview.

Quality control

Attention checks, removal of speeders and straightliners, coding of open answers and weighting to population targets are standard. We work to the ICC/ESOMAR International Code and GDPR.

What you receive

• Full report as PDF plus an editable presentation deck
• Two- to three-page executive summary for the leadership team
• Cross-tabulations in Excel by age, region, user type and brand
• Cleaned, weighted respondent-level data (SPSS or CSV) with a codebook
• Consumer profiles illustrated with anonymised quotes
• Optional online dashboard for filtering results
• Half-day workshop to turn findings into priorities

How the project runs

1. Briefing, decisions to support and hypotheses — 2–4 days
2. Desk research and qualitative exploration — 1–2 weeks
3. Questionnaire design, scripting and pilot interviews — 1 week
4. Fieldwork — 1–2 weeks, longer when incidence is low
5. Cleaning, weighting and analysis — 1 week
6. Report, presentation and workshop — 3–5 days

Common mistakes and how to avoid them

• Surveying only your own customers. You miss the non-buyers who represent growth; sample the whole category.
• Taking stated reasons at face value. People overstate rational motives. Combine stated importance with derived importance, which links each attribute to actual preference.
• Asking about "usual" behaviour. Memory blurs averages. Ask about the last purchase occasion instead.
• Ignoring incidence at the planning stage. A low share of category buyers lengthens fieldwork; estimate it from desk data first.
• Reporting averages only. A small group of heavy users often accounts for most of the volume, so split results by usage level.

Who it suits

Updated: 5 Nov 2026