While numbers offer safety and scalability, they don't tell the full story. Discover why modern marketers must step away from their dashboards and embrace the messy, revealing reality of ethnography to uncover the "why" behind customer decisions
Marketers must learn to fall in love with numbers. And rightly so. Good quantitative research can size markets, track penetration, test awareness, monitor brand health, diagnose price sensitivity and, crucially, track the drivers of that all-important profit margin.
But numbers can also become a hiding place. Turn a figure into a percentage and the chart suddenly tells a different story.
A dashboard can tell you what happened, but it can't tell you why – what it felt like, what surrounded it, what people compromised on, what they forgot to mention, what they were embarrassed to admit, or what they did automatically without ever recognising it as a decision.
That is where ethnography earns its stripes. Ethnography is the observation of people's behaviour in their own environment: at home, in the workplace, shopping, online and within daily routines.
It’s not a soft alternative to the numbers; it is a disciplined way of getting closer to a consumer's reality. The key word in all of this is behaviour. Not claimed, recalled, or filtered through a survey question. Actual behaviour – raw and in context.
Anyone who has ever rated their own performance and then seen how someone else rates it will recognise the blind spots ethnography can shine a light on. We are all influenced by our own reality, and this shapes our perception of the world around us. We answer questions differently depending on how we think they are being asked, or answer with what sounds sensible, clean, moral, professional or aspirational.
Organisations need to understand that reality and perception – how people want to be seen and what they actually do – are not always the same thing. Our perception is our reality, which is totally different to someone else’s view of the world.
Ethnography is one of the qualitative research methods covered in Module 2 of the MiniMBA in Marketing. But actually, the thinking behind ethnography begins in week one. Because like all good marketing strategies, it starts and ends with the consumer.
What consumers say and do are two different things
A consumer may claim sustainability matters, then choose the cheapest or most convenient option under time pressure. A B2B buyer may say product quality is the deciding factor, then reveal through observation that internal approval, risk avoidance and supplier familiarity dominate the decision. Ethnography can reveal the gap between what people say they value and what they actually – or subconsciously – prioritise.
It can show hidden workarounds. People tape things together, build their own spreadsheets, decant products into different containers, ignore features, invent shortcuts, or use a premium product in a low-value way. These behaviours are clues that other forms of research may miss or fail to uncover.
It can identify category entry points. When does the need actually arise? What triggers it? Who is present? What else is happening? What language do consumers use before they ever think of the brand?
It can expose the social dimension of decisions. Many purchases are not purely individual. They are shaped by partners, children, colleagues, managers, procurement teams, peer groups, influencers, friends and cultural norms.
It can uncover emotional rewards that sit behind functional tasks. A classic example here is Febreze, where the emotional satisfaction of a completed clean outweighed the role of eliminating odours (see below).
These insights can be critical to informing the way we go to market and, ultimately, succeed.
The Febreze lesson: the answer was in the home, not the spreadsheet
Febreze remains one of the best examples of ethnography. In 1998, P&G had a technically impressive product that removed bad odours from fabrics. On paper, the use case looked obvious: people with smelly homes, pets, smoke, teenagers, damp sofas, old jackets and lingering household odours; with early communications focusing on odour elimination. The logic was sound enough – but real consumer behaviour did not follow that logic.
The logic was sound enough – but real consumer behaviour did not follow that logic
P&G researchers discovered that many people living with persistent odours had adapted to them. They did not necessarily notice the smell in the way an outsider did (their perception was their reality). In one widely cited example, researchers visited a woman with multiple cats and found the smell overwhelming, while she did not see her home as having an odour problem.
That is the sort of finding a survey can easily miss. Ask someone: “Do you have a problem with bad smells in your home?” and the answer may be “No”. Observe the home, the routine and the sensory reality, and you may find otherwise.
The breakthrough came when P&G stopped treating Febreze as a problem-solution product for bad smells and started understanding its role in cleaning routines. People liked the moment after cleaning: the room finished, the bed made, the sofa straightened, the visible task complete. Febreze was the finishing touch – the reward at the end of the routine.
After repositioning Febreze around that reward, sales doubled within two months and reached $230 million within a year. Quantitative data could show poor sales. It could show weak repeat purchase. It could show that the proposition was not landing. But the crucial insight came from spending time with people and noticing the mismatch between product logic and lived behaviour.
Why marketers get too comfortable in numbers
Marketers can be forgiven for searching through the numbers rather than sentiment. There is a safety in quantitative data. It is scalable, clean and board-friendly. It gives you percentages. It looks objective on a slide. It helps settle arguments. It can be benchmarked, tracked and turned into targets and it doesn’t mean you're spending any time away from your desk.
Ethnography is messier and more uncomfortable. It produces stories, contradictions, tensions and inconvenient nuances. It may show that the segmentation is too tidy, the funnel is too linear, the proposition is too internal, or the customer journey map is mostly fiction. Turning these things around takes time, patience and a lot of convincing internally that this is the right path to take.
Ethnography is messier and more uncomfortable
A good marketing strategy starts with diagnosis. Before consideration can be given to segmentation, targeting, positioning, objectives, product, pricing, distribution and communication, there is a more basic job: understand the market. Not the market as viewed from within the organisation, but the market as it is, in the wild – where ethnography links directly to proper market orientation. That means getting close enough to see what consumers do when no one else is in the room.
Modern ethnography is not just a researcher with a notebook
Some marketers still imagine ethnography as a researcher sitting in a kitchen with a clipboard. That still exists, but modern ethnography has become much broader as technology allows us to observe in very different forms. The traditional watch and learn approach, such as in-home observation, shop-alongs and workplace studies, maintains its rightful place in ethnography. But modern additions include mobile diaries, video diaries, screen recordings and digital communities.
IKEA’s Life at Home programme is a good contemporary example. Between 2014 and 2024, IKEA surveyed more than 250,000 people But they also used qualitative research methods including home interviews, online communities, mobile ethnography and online in-depth interviews. The goal was to find out what “home” actually means in everyday life: how people use space, where joy or friction appears, what domestic routines look like, and how people adapt their homes around real constraints.
When we use a variation of research techniques, it allows us to collate information in different ways. In comparing and contrasting findings across different data sets, you can start to build use cases that are stronger than pinning recommendations on a singular source that might only tell one side of the story.
The danger of false certainty
The seductive thing about numbers is that they look precise even when the underlying question is weak. A survey can tell you that 67% of customers prefer a certain feature. But did the user understand what the feature was originally for? Were they imagining the same context? Would they still choose it if it cost more? Does the feature matter during purchase, usage, renewal or recommendation? Is it a genuine driver or just an easy thing to prove in a questionnaire?
Ethnography slows the marketer down long enough to ask better questions
Ethnography slows the marketer down long enough to ask better questions and make better judgments. In many organisations, speed has become a proxy for competence. Launch quickly. Test quickly. Iterate quickly. Report quickly. But strategic marketing problems are not solved by speed. They are solved by doing a full and rounded diagnosis. A good ethnographic project never ends with “interesting findings”. That is not enough. It should lead us to strategic outputs, moving from what we saw to what it means to what we should do next.
Don’t hide. Go and look.
Ethnography is not glamorous. It is not fast. It can be awkward, expensive and inconvenient. A marketer’s job is not to produce a more polished internal story. It is to make better decisions in the market. Sometimes that means commissioning a survey. Sometimes it means analysing sales data. Sometimes it means brand tracking, econometrics, pricing research or concept testing. And sometimes it means going into homes, workplaces, shops and real customer journeys to watch what actually happens.
Do not overlook ethnography and don’t hide behind the numbers. If the data can tell you where to look, ethnography helps you see in full colour.
Want to break out of your spreadsheets? Read “Qualitative vs quantitative research: why you need both” to explore the concept of "Bothism" in market data.
Or, learn how to run targeted field studies firsthand on Module 2 of the MiniMBA in Marketing.