All marketers know the importance of understanding their customers. But how best to do it accurately?
For many in the industry, traditional survey-based market research is no longer up to the job. Given that people can’t always explain or describe their behaviour, the thinking goes, there is little value in asking them questions.
This challenge of human inaccuracy often leads to the conclusion that we should stop asking, and instead rely solely on observing: collecting behavioural data (purchase records, search data, app usage etc.) that requires no questions at all.
But tempting as this may be, the human challenge shouldn’t encourage marketers to ditch surveys entirely. Rather, it should push them to develop realistic expectations about what survey research can really achieve, and how to conduct it effectively.
Many advocates of research expect it to magically convert questions about the choices of shoppers into perfect mathematical answers. This would imply you can ask anything that takes your fancy and get a reliable response out the other side.
The reality is that research is a useful but imperfect tool. Like all tools, it needs to be handled delicately. And although research seems increasingly like a purely data-driven practice, this should start with a sound understanding of human decision making.
An important truth about consumers is that they spend very little time thinking about brands. They choose between brands without much conscious effort, often relying on habit or simple recognition. This is especially true for frequent low-involvement purchases (supermarket items), where the shopper autopilot is most active.
And yet a lot of research assumes that consumers care deeply about brands – thoughtfully evaluating every purchase they make. Surveys routinely ask people to assign twenty personality traits to brands of toothpaste. They probe the impact of subtle packaging changes like the addition of an extra nutritional label. They examine attitudes to a brand’s environmental policy or corporate values. Given how little consumers think about these brands, asking them for a detailed analysis is unlikely to yield helpful results.
Perhaps more problematic is researchers’ tendency to ask consumers to make predictions: how likely are they to buy a specific product? Will they enjoy advertising if it features a brand mascot? Psychologists know that we are bad enough at predicting how we will respond to major life events. So it should be no surprise that our ability to forecast brand-related behaviour often misses the mark.
Proper research accepts these limitations, and focuses on what respondents can answer accurately. While not a perfect science, this means asking them to recall and not predict. It means focusing on topics that people care about and have established opinions about. And it means aligning the research context as closely as possible to the real-world decision context.
Here, it’s helpful to look at general election exit polls. Why do they tend to be so accurate? After all, the error margin has been five seats or fewer in all but one of the past five exit polls.
It’s because voters are asked to fill in a replica ballot paper just after they leave the voting booth. In other words, they are asked to recall past behaviour, in a realistic setting, about a subject they have (mostly) thought about.
Reliable research takes into account another human trait: we like to say what sounds good. With little conscious effort, people will give a logical and socially acceptable response to questions even if their behaviour in the real world is radically different.
When Trinity Mirror media group asked consumers what they wanted in a new newspaper, they said content that was upbeat, optimistic and politically neutral. But when the group launched New Day – a newspaper that offered exactly that – readership was so low that the paper shut down within just 2 months. As advertising legend Jon Steel explains, “people tend to present the personalities and habits they would like to have, rather than the ones they really have.”
This also explains why, according to surveys, consumers are excellent at exercise, recycling, eating healthy food and just about any other prosocial activity, even though their corresponding behaviour is rarely as righteous.
The solution is not to avoid asking these questions altogether. Clever question wording techniques aside, the key learning is to not take respondents’ answers too literally. It requires separating what people say from what people mean; what they would like to be from what they are. And crucially it requires pushing past surface level responses.
When done right, this process can lead to breakthrough insights, as the team behind the iconic Got Milk campaign found out. While initially consumers said they liked milk because of its nutritional benefits, a deeper exploration into their responses revealed it was because milk is the vital pairing to the foods we love.
If market research can produce useful results, how can we explain the common view that Steve Jobs – one of the greatest marketers of all time – hated it? After all, he’s famous for saying that “people don’t know what they want until you show it to them.”
Actually, it is a big misconception that Steve Jobs rejected market research. Quite the opposite. When a 2011 lawsuit with Samsung forced Apple to reveal the details of its famously private research policy, the public got to see the truth: the company loves research.
Apple conducts quarterly surveys to understand why consumers buy iPhones and not Androids. It analyses which demographics are most satisfied with its products. It compares consumer attitudes across different countries.
In other words, Steve Jobs was deeply concerned about what his consumers thought. In fact, that same year of the lawsuit Apple launched a series of successful innovations that directly addressed the findings in the previous round of research.
According to the surveys, a key reason why consumers bought an iPhone was the ability to easily transfer music across multiple devices. Apple launched iCloud. Another reason was the functional design of the product. Apple introduced the new iPod Nano with a ‘redesigned user interface for easier navigation’. Market research at its finest.
So when Steve Jobs said that “people don’t know what they want until you show it to them,” he wasn’t condemning all research, but correctly noting its limitations. He realised that, although consumers can express pain points and needs, they are generally bad at imagining and predicting breakthrough innovations. After all, if they could, they wouldn’t just be consumers.
Apple has access to more behavioural data than most companies on earth. The fact it still invests time and money in understanding perceptions tells us something important. A point that is missed by a simplistic reading of market research: behavioural data has its own drawbacks.
For starters, just like survey data, it can be incomplete. Just because it’s observed, doesn’t mean it captures the whole picture. Even something as seemingly objective as supermarket till data is tainted by the fact that not all retailers (like Aldi & Lidl) are willing to share their figures.
More importantly, behavioural data is largely unable to reveal people’s needs and motivations. Imagine a new soft drink is seeing a decline in sales. Panel data can show you the rate of decline. It can show you the demographics of the consumers who are no longer buying it. But it can’t tell you why this is happening. Without asking people directly, it is hard to diagnose the problem and find a solution.
This isn’t to say that behavioural data is worthless, but that relying on it exclusively can lead you in the wrong direction. If the 2003 Tesco research team had looked at behaviour and nothing else, they would have seen that gluten free products were underperforming at their stores and potentially de-listed them.
It was only through survey research they were able to see the whole picture: there was a big appetite for gluten-free products, but consumers felt Tesco and other big retailers lacked the range available in specialty shops. So rather than doing multiple trips, consumers preferred to purchase all their gluten free products from these smaller stores. Armed with this insight, Tesco launched their own Free From range before their major competitors.
As new technologies and tools continue to emerge, the volume of behavioural data will keep rising – becoming more accessible and less expensive. The argument for using old fashioned survey data will appear increasingly weak.
But instead of hiding behind the comfort of mechanical numbers, we should start to embrace the complexity of people.
We should remember that the most meaningful learnings about our customers aren’t revealed by shying away, but by getting up close and asking them. And it’s only by understanding people that we can do this effectively.
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