Segmentation Studies

Segmentation studies break a company’s market into different groups so that different strategies for marketing to these groups can be leveraged. The main reason a company wants to complete market segmentation research is so they can gain actionable insights into how to sell more of their product or services.

segments of fruit are like segments of the population

Customer segmentation uses a data-driven approach to help a business decide how to offer a customized journey to different kinds of customers. For example, an outdoor clothing brand might do a segmentation study and find out that two of their largest customer groups are “outdoor adventuring families” and “health conscious seniors”. They can use this insight to create two different marketing playbooks catered to these two segments.

The landing pages, newsletters, and gear recommendations for the adventuring families customers might include things like:
- pictures of hiking with children
- posts about top outdoor spots for families
- clothing for kids and adults
The same resources for the active seniors group could include:
- pictures of older walkers enjoying a strenuous trail
- posts about nutritional needs for active bodies as they age
- accessible clothes for supporting an active lifestyle with changing physical abilities

It requires money and time to develop these sets of resources and different workflows, and many companies may have more than two segments. In order for a marketing department to make their case for why they should get these resources, they need to be able to show real data to support this segmentation. That’s why segmentation studies matter—because they provide the data to demonstrate why this approach is valid. But they have to be done thoughtfully and with a true understanding of the meaning behind the numbers to achieve real results.

In this article we’ll look at:

What segmentation research is
The segmentation research process
The different ways customers can be segmented
How segmentation studies can be both qualitative and quantitative
A segmentation research example

What Is Segmentation Research?

Segmentation research is the nuts and bolts of learning what meaningful sub-groups there are within the customer base for your product or services. It requires data about a large number of customers, and then the use of segmentation analysis methods to identify robust cohorts within the data. Let’s break these necessary parts of the research down a little further.

How Is Data Gathered?

All segmentation studies start with data about a company’s customers. There are several different ways this data can be collected, each with their own pros and cons. These include:

Survey data – Asking customers about themselves, including what they buy and why. This is often the cheapest and easiest way to gather data, but self-reported survey data will be influenced by customer biases. This bias could include things like the societal pressure to report cooking more meals at home rather than eating fast food, which means survey results show lower rates of fast food consumption than is actually happening.
Observational data – Setting up a way to watch and record what a customer is actually doing as they interact with your business. This could look like a researcher recording customer actions while they are in the store, or a reward card that gives the company concrete data on what purchases each customer makes. A drawback of this method is that it is often expensive or time- consuming to produce the amount of data needed.
Customer relationship management (CRM) database information – Using the company’s existing customer database to analyze what they already know about their customers specifically for segmentation studies. This might include things like address, marital status, purchase history and customer satisfaction scores. One limitation to this is that the only data available will be what a company has already collected and recorded about each customer.
Intercept data – Sourcing information from outside entities about your customers to learn more about them, like data from retailers, warranties, voting records, and restaurants.

How Much Data Is Needed?

Once you know how your data will be sourced, it’s time to think about how much of it you need. Sample size is important in this type of research because segmentation studies are designed to separate customers into groups. If you are using too small a data set, the study will still give you customer groupings. But these groups just may not be meaningful or actionable for the marketing strategy you hope to develop.

segmentation studies are like great filing cabinets of knowledge

To use our outdoor clothing company example again, you could run a segmentation study on data from 10 customers and the report might tell you that there are two distinct groups, people over 60 and people under 60. But that information doesn’t tell the clothing company anything they can use to sell more of their product.

Exactly how many data points you need for a robust segmentation study will depend on which mode of statistical analysis will be applied and how many variables you want to measure. In general, though, you want to aim for at least 70 times the number of variables being measured for the strongest analysis. This means that if our outdoor clothing company wanted to compare 5 variables (like age, preferred outdoor activity, number of children, geographic location, and reason for being active) they would need this data from at least 350 customers (5 variables x 70) for their results to be useful.

What Type of Statistical Analysis Is Useful?

The best way to analyze the data that has been collected will depend on exactly what data is available and what type of insight is being looked for.

Here are some of the methodologies that can be applied.

Neural net – including backpropagation, nonlinear feed-forward, radial basis function using the median or mean, and perceptron
Decision Trees – including CHAID and CART
KNN Algorithm
SVM (Support Vector Machine)
Discriminant
C5
XG Boost tree and XG Boost Linear
QUEST
Random Forest
Logistic Regression
Bayesian Network
Tree-AS
K Means
2-step Hierarchical
Kohonen Method
Self-Organizing Map
Silhouette Algorithm

What Are the 4 Types of Market Segmentation?

Before we dive into how to actually carry out a segmentation study, it’s important to identify what criteria will be analyzed to identify the segments. The data will determine what segments exist, but which data is fed into the analysis will determine what characteristics can be used as variables.

Deciding what information to collect and include in a segmentation study will depend on what type of segmentation you are interested in. Because gathering data takes time and resources, it is important to consider what type of segmentation is likely to be most useful to you as a company. When you have a range of information about each customer, you can divide them into segments based on any number of traits, or a combination. Things like where they live, how old they are, how they act, and how they think.

Each of these customer segments examples relies on a different type of segmentation to define relevant categories.

There are many ways to slice and dice the data about customers that could be used to divide them into groups, but generally the ones that provide a company with the most actionable segments are these four:

1. Geographic Segmentation – This separates customers by location. It can be done at different levels depending on a company’s needs. It could divide them based on country, state, city, or neighborhood. For our outdoor clothing company, if they have a brick-and-mortar presence in one state and sell online across the US, they could use this to identify customers as local shoppers vs online shoppers.

2. Demographic Segmentation – This separates customers by specific quantifiable characteristics, like gender, age, family size, income, marital status, occupation, race, nationality, etc. A simple way to use this type of segment for a clothing company would be to advertise children’s clothes to customers who have a larger family size.

3. Behavioral Segmentation – This separates customers by how they act. It often includes things like:

How they found your company
How often they use your product or service
How long they have been a customer
How they use your product or service
How they engage with your company

4. Attitudinal or Psychographic Segmentation – This separates customers by how they think and feel, their attitudes and values. It is often considered the most useful way to segment an audience, because it provides the clearest actionable steps for a company to take as they try to target each segment. But it can also be one of the most challenging methodologies to collect data for. A way our outdoor clothing company might get at these attitudinal differences is by sending a survey with questions like:

Why do you like to spend time outside?
What are your favorite outdoor activities?
Where do you spend the most time outside?

segmentation data can be understood as cubicles

How Do You Conduct a Segmentation Study?

Market research segmentation techniques reveal very useful information about a company’s audience that can ultimately lead to higher sales and more revenue. But how do you actually carry out this type of study?

What Are the Steps in Segmentation Research?

Think about your audience – Apply what you already know about your audience strategically to help you decide what type of segments make the most sense to drive marketing decisions. Observations from members of the leadership, marketing, and sales teams will be valuable in this step.
Choose a type of segmentation – Take the knowledge you have about your existing customers and your marketing abilities and select the type of segmentation that is likely to give the most useful results.
Perform market research – Decide which type of data collection will be best for the type of study chosen, and collect it. This might mean designing survey questions to get at real attitudinal differences in clients. Or it could mean looking at the data already available in your CRM database to choose the most relevant variables.
Data analysis and segment choice – Analyze the data. This could involve running multiple statistical analyses using several different methodologies to discover robust, meaningful segments. Prepare persona descriptions of each meaningful segment: vivid portraits of the demographic, attitudinal, behavioral, and psychological characteristics of these people.
Make marketing decisions – Use these results to build marketing strategies that target each segment specifically. The best designed study and strongest results won’t improve a business in any way if it isn’t actually used to change anything.

Using these five steps, let’s explore how to do a market segmentation study for the outdoor clothing brand we’ve looked at already. How did they carry out this type of study to discover the two segments of Adventuring Families and Active Seniors that they designed their marketing playbooks around?

Think about the audience – This company started with a meeting where key stakeholders discussed their goals with segmentation studies and took in input from other departments about how existing customers interacted. They knew they wanted to create segments that were different from their competitors, who were looking at basic demographic traits to customize marketing in very predictable ways.
Choose a type of segmentation – This brand wanted to use attitudinal segmentation to find meaningful differences in the attitudes of customers that drove purchasing decisions.
Perform market research – This outdoor clothing company designed a survey with questions about their customers motivation for being outside or wanting outdoor gear. They were able to integrate the survey results with internal customer data for a more complete dataset with both attitudinal and demographic data points.
Data analysis and segment choice – This data was analyzed using several statistical methods, and the combination of attitudinal survey questions and demographic information repeatedly found two distinct groups. Persona descriptions were prepared for each.
1. Adventurous Families – Were between 30 and 50, had a household size of 4 or more, and were going outside for bonding time and adventure.
2. Active Seniors – Were over 60, had a household size of 3 or less, and were going outside for exercise and calm.
Make marketing decisions – This business identified two distinct marketing strategies they wanted to use, targeting these two segments in different ways. They allocated funds to creating and implementing these two different playbooks to get the largest revenue increase from this study.

Is Segmentation Qualitative or Quantitative?

Segmentation analysis in data analytics are often thought of as quantitative, since they use numeric variables and statistical analysis. However, they also use qualitative methods in choosing which type of data is inputted. Additionally, qualitative methods are normally used again in the last stage of a segmentation study to create a fuller picture of each segment. This makes the personas robust enough to design marketing strategies around.

segmentation can be understood as the orderly arrangement of data

Market Segmentation Case Study

Let’s look at a real-world segmentation analysis example to see what actual revenue benefits can come from a well-run segmentation study.

Kaiser Permanente: Increasing ROI

Kaiser Permanente was mailing 600,000 educational material packs monthly about their Group Health Medicare Supplement Plan, sent to all their customers over the age of 65. However, the response rate to these mailers was only 0.3%. Kaiser attempted to increase this response rate by trying to target households suspected of being more likely to respond, but this only raised the response rate to 1.3%.

Kaiser then commissioned a segmentation study from Cascade Strategies to try and discover a more meaningful way to deliver customer value with these mailers. The study found three meaningful groups within their 65 and over customer base:

Seekers – Married or single, middle to high income, tend to proactively seek out information
Sustainers – Married, middle to low income, more casually look for information when required
Survivors – Single, low income, lack time and resources to find information

Of these three, survivors were much more likely to respond to educational mailers. Kaiser began mailing information to only the survivor households they identified, which reduced their monthly mailings from 600,000 to 10,000. ROI increased 410% in the months after this change, because survivors were so much more likely to sign up for the Medicare Supplement Plan after receiving a mailer than the entirety of the customer base.

As you can see, segmentation studies can have a profound effect on business sales and expenses. They are used successfully in a myriad of other cases too, including:

Demographic segmentation in tourism to identify customers aboard a Carnival Cruise ship most likely to gamble. This enabled the cruise line to send targeted brochures to these clients before a trip and while on board.
Behavioral segmentation in energy production to find the best prospects for Southwest Windpower, a company that sells personal wind turbines for homes and farms. The business was then able to identify the most promising potential customers on their list of people who had shown interest.
Attitudinal segmentation in entertainment to discover the group of SkyZone trampoline park users most likely to increase their usage. “Family thinkers” were identified, more family events were scheduled and promoted, and there was a 31% increase in this group in the following year.

Cascade Strategies: Bringing You Meaning from Information

Segmentation studies can bring you and your business some of the most valuable customer insights around. But only if they’re done not just with the latest in AI and Machine Learning technology, but also include the context and meaning that comes from our experts’ human brains.

What does that look like?

Insights instead of reports – Our experienced team keeps working on your project until we get a breakthrough in interpreting the complex quantitative segmentation data. We’re not satisfied just presenting a basic breakdown of your customers that doesn’t give you anything you can really apply to running your business better. Instead we keep looking at the data until a larger picture starts to appear.
News you can use – You don’t need a Master’s in Statistics to understand what we find. We present our findings so that all your important stakeholders can understand them, helping drive data backed decision making at every level. We even develop creative briefs that can be used for advertising and website strategy based on the segments we discover.
Extendable results – Cascade Strategies doesn’t stop at simply dividing your existing customers into segments. We empirically use the segmentation results to give practical action items, like finding the right neighborhoods to target for future acquisition efforts and new product releases.

Cascade Strategies combines our long experience digging deeper to find real insights with the best technological tools out there to give you the largest benefits from studies. We leverage data from eye tracking, biometrics, neural tracking and virtual reality and analyze it with the most advanced AI and machine learning tools. Combining the purely analytical with human understanding is what sets us apart.