Consumer research turns broad market segments into groups you can act on, by showing which needs differ and which choices follow from them.
Market segmentation divides a target audience into groups with shared characteristics, so you can tailor offers and messages.
The result is only as useful as the understanding behind it. Consumer research provides that understanding, and business intelligence helps you keep it current.
This article covers the standard approaches, where they fall short, and how to combine research with data for better decisions.
The four traditional approaches
Most segmentation work starts with four kinds of criteria:
- Demographic: age, gender, income and education.
- Geographic: countries, regions or cities.
- Psychographic: lifestyles, values, interests and attitudes.
- Behavioural: purchasing behaviour, brand loyalty, usage patterns and benefits sought.
Each has its place. Demographic and geographic segments are easy to apply and easy to buy media against. The risk is that they describe who someone is, and not why that person chooses.
Where traditional segments fall short
Two people of the same age in the same city can want completely different things. Broad categories hide that difference. Segments also tend to stay fixed long after preferences have moved.
A segmentation that is several years old can still look tidy on a slide. Before you plan around it, ask when it was last tested. Then ask which decision it actually changes.
Primary and secondary research
Market research collects two kinds of data. Primary data comes directly from target customers through surveys, interviews, focus groups and observation. Secondary data comes from existing sources such as industry reports, government publications and online databases.
Use secondary data to frame the market and form hypotheses. Use primary research to test those hypotheses with the people you want to reach.
A simple customer needs survey template
A customer needs survey does not have to be long. These questions are a starting point, and you should adapt them to your category:
- What were you trying to achieve when you last bought in this category?
- Which alternatives did you consider, and why?
- Which features or qualities mattered most to your choice?
- What frustrated you during the search, the purchase or the use?
- What would make you switch to another option?
Group the answers by need before you look at demographics. You may find that a needs-based group cuts across age and location. That is often where a new segment appears.
What research adds to segmentation
Motivation. Research shows what drives a choice, so you can segment on meaningful criteria. For illustration, a retailer might find that one group chooses mainly on durability.
Pain points. Interviews and feedback channels reveal frustrations that purchase data does not show. A shared frustration can define a group worth serving differently.
Overlooked groups. Research can reveal segments that standard criteria miss. Those groups may be small, so size them before you commit budget.
Tailored offers. Knowing which features matter to which group helps you prioritise development and messaging. A 2017 online survey of 1,000 consumers found 80% more likely to do business with a company offering personalised experiences. That is stated intent from one study, so test it in your own category.
Satisfaction and loyalty. Acting on what customers tell you can address the problems that make them leave. Measure whether the change worked, and do not assume it did.
The limits of research alone
Research answers the questions you ask, at the moment you ask them. It describes the market at that point, and the market keeps moving. Customer research also tends to hear mainly from existing customers.
That is why segmentation benefits from a second, continuous source. Behavioural data from your own systems shows what customers do with you. An outside view shows how demand is developing beyond your own customer base.
Bringing segments into business intelligence
Segments only help if people use them. Build them into the reports that teams already use. Then follow each segment over time, using a few measures tied to a decision.
- Agree on one shared definition of each segment across marketing, product and sales.
- Link each segment to a choice, such as assortment, positioning or budget.
- Set a date to review whether the segment still holds.
- Drop segments that no longer change any decision.
Where demand data fits
Trendata adds this outside view through Demand Intelligence. That is a structured understanding of how market demand forms, changes and is expected to develop.
It uses aggregated demand signals only, with no personal data and no tracking on your site. So it does not describe individual customers or build customer profiles.
What it can show is which customer needs are gaining or losing demand, at category, type, specification and attribute level. That helps you choose which needs deserve closer research. Research then explains why those needs matter, and to whom.
What to do next
Take your current segmentation and pick one decision it should support this year. Check whether the segments still reflect real differences in needs. If they do not, start with a short needs survey. Then look at how demand in the category is developing.
