The voice of the customer is important for any company that wants to remain relevant or resonate in a way that supports growth and staying power. Customer research can often uncover pathologies in beliefs and perceptions that lead to breakthroughs in designing better, more engaging products and more effective marketing or sales efforts.
Taxonomic ways of thinking about research
- Category A: Online desk research, store visits, product demos
- Category B: Secondary research sourced from existing studies
- Category C: Primary research or research that is designed and fielded solely for your specific need or goal
Primary research design and methods have their roots in Anthropology and Sociology as well as Statistics and Public Sectors. It’s a tool for understanding, learning, and gaining insight from which we can create, innovate or problem solve.
Once you’re determined that you need to better understand the customer’s perceptions, it can be daunting to determine what kind of research you should conduct and when in your process or cycle is best to bring the voice of the customer in. There are myriad methodologies, and endless ways of designing research, as well as any number of ways of sampling your market, audience, or prospects, all of which have a drastic impact on what you can learn, and how “real” that learning is.
The first rule with primary research is NOT to think about it in terms of “what kind of research” do I need, but instead to think about “what do I need to learn?” Take a moment before jumping headlong into fielding research to ask yourself and your team, what are your learning goals? Do you have the “right” goals to gain unbiased, or “real,” learning? Meaning, are your goals open to any direction the customer’s input might take you?
Now, what methodologies and designs will best suit your goals and ensure “real” learning against those goals? There are three general types of research, each suited to a different goal.
Goal: To discover new ideas!
Exploratory research starts and stops in the context and world of the customer – not of your company or product. The idea is to put yourself in their world, help to uncover how they really feel, what their world is like and where they have challenges or unmet needs or wants, and where they might have entrenched beliefs that impact their thinking or engagement with your category and product. You might find yourself saying “I want to understand that more…” about your customer, and that’s when you want to look more closely at using exploratory research.
Design: Flexible and adaptable depending on the context of the customer and what’s being learned, but most often qualitative
Exploratory research is best when it’s non-stimulated, meaning you do not put ideas in front of the customer for them to react to; instead, you let the customer inform where the conversation goes (to a large extent). Exploratory research can include observational research, shop-alongs, interviews, group discussions, or ethnography.
Timing: exploratory research should be conducted at the beginning of a idea generation, or at a mid-point in creation, but not at the end. You’ll want to use the insights from exploratory research to inform where you start your exploration for your innovation, campaign, or design.
Watch out: Don’t use exploratory to ask hypotheticals. Use it to deeply understand realities, and then take those insights away to create, build, design, and engineer.
Goal: To get a clear picture of a market
Descriptive research includes things like the U.S. Census, or broad surveys meant to tell you how many people there are in a market, which attributes of your product are most important to a certain set of people, what benefits are most liked, how geographical differences impact preferences, or which channels are used. Descriptive research should give you a clear picture of WHAT a particular market, segment, or demographic looks like and cares about. You can use it to understand what a market looks like in terms of what they find important or how they prioritize things, but it cannot give you more diagnostic, emotional information that generates creative breakthroughs. Descriptive research helps to define volume, sizing, and common ground in a market.
Design: Consistent, structured questions across the market or segment in need of definition or description, so it is most often quantitative
Quantitative research is most effective at helping to create the groups and sub-sets needed to get to a clear description of a market or segment. While in some cases interviews, message boards, or group conversations can be descriptive, they are rarely projectible to the entire population at a reliable level, and so should be approached with skepticism. Deciding an entire market cares about your product benefit of agility based on 12 interviews is specious. Descriptive research is binary in nature, and not generative.
Timing: typically at the beginning stages of a business strategy, product strategy, or marketing/campaign strategy.
Watch out: While statistical techniques such as derived importance and regression analyses can uncover a lot of connections in descriptive research, context and emotional contours cannot be uncovered as descriptive research is too blunt a tool for that level of nuance.
Goal: To understand cause and effect
Causal research can be summed up as the scientific method in action. Its purpose is to create or stimulate a “cause” and then to observe and understand the “effect.” This kind of research can tell you what makes a person click on an ad, or which feature is best at generating an intention to purchase the product, or which name best causes someone to read the package, or what user interface generates the most engagement.
Design: Good design of causal research imitates real world scenarios and has a control group and isolates and/or limits variables that are being tested, to get the best read on what “cause” is actually generating the “effect”
Usually, monadic quantitative is the “gold standard” of causal research. While sequential monadic quantitative or even single-cell testing that asks the respondents to compare the variables can be used, they are less “real world” and therefore less reliably predictable of an actual cause-effect scenario.
Timing: causal research happens after you have a hypothesis, feature, name, design, website, user experience, or product to test.
Watch out: Don’t throw 5 names or 3 design concepts or 7 potential user pathways to the same respondent and ask them to choose – no one does that in the real world! And cognitive biases such as the Hawthorne effect or expectancy bias can lead respondents who are asked to sort variables for themselves to end up giving misleading answers – making the research findings and insight moot.
Regardless of the type of research, watch out for just stopping at the answer a customer gives you – that’s the road to a faster horse. People often cannot predict what they will do, but they can say very well how they feel. When you think the customer is giving you their answer, stop and check:
- Does what’s being said match with what’s being done or experienced? Or is there a disconnect? Ask your questions in different ways more than once, to make sure you’re hearing what’s really being said – not just the narrative you’ve formed in your head or in the conference room with your team
- What isn’t being said? Where do people demonstrate affect? Where are they lack-luster or disengaged? Pay attention – 90% of all communication is in tone and body language
- Do you clearly know why something is being said? If not, look for why
- Do you clearly know why something is being done or felt? If not, investigate more
Including the voice of the customer in your product, concept, design or creative generation and evaluation can result in amazing insights and breakthroughs. Be sure you are gearing your research for the learning you want to achieve, and not just checking a box.
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