The goal of market segmentation is to identify a group of customers (a segment) who are different from the whole population. It is a tactic for product, marketing, and sales teams to relate to customers - the more of a story you can build about a potential customer, the better you can understand them. Powerpoint slides of customer personas are passed around the office for you to study. “Rachel likes to vacation in the Florida Keys.” “John has two children and works in ‘the city’.” It's an interesting description of a person, but what does it have to do with the product? And if you're a product manager, what does it have to do with you and your work?
The problem isn’t market segmentation as a whole, but rather how it’s being executed. If done well, segmentation can help you find a narrowly defined, underserved group of customers who are different from the total population and more likely to adopt your product. It can also help you understand how that group is struggling and how you need to improve your product to gain their business.
What’s missing in many traditional approaches to segmentation is the true common denominator - the customers’ struggle. Traditional segmentation uses characteristics, such as demographic, psychographic, geographic, behavioral and situational attributes, to group customers. They’re hoping that they will correlate with a common struggle and a likelihood of purchasing your product. But the problem is none of these characteristics cause people to buy a product, their struggle with the job does. Customers will use products that help them get the job done better.
Read more about what a Job-to-be-Done is.
Often a broad population of people who have the same job-to-be-done, i.e. the same goal to achieve, struggles with the job in many ways and no particular struggle stands out as being especially severe. This makes it hard to determine which problem to solve and where to focus your solution. We use segmentation to identify a smaller, but valuable, group of people who have more specific and more severe problems on which we can focus. With Jobs-to-be-Done you can segment directly by struggle instead of using traditional characteristics.
In this post, we will show you how to find that attractive group of customers who will actually buy your product, review the limits of traditional segmentation and personas, and show you how to use Jobs-to-be-Done based segmentation to find underserved customers.
Persona development is not inherently bad if the persona includes how the segment struggles. But personas that are based only on characteristics are much less helpful because people do not buy products based on the school they went to, how tall they are, where they work or what they read. They decide to switch from one solution to another based on what pains them the most and what solution promises to remove that pain.
Let’s take a look at an example:
Here’s a traditional approach to using demographics and behavioral characteristics to develop two personas, Paul and Kate.
Paul’s Customer Profile:
Age: 27 years-old
Home: Lives in Manhattan (Urban)
Job: Entrepreneur
Education: Received an MBA from Wharton
Content Consumption: Reads the New Yorker, NY Times
Activities: Enjoys playing basketball on Saturdays with his friends
Kate’s Customer Profile:
Age: 56 years-old
Home: Lives in Forsyth County, Georgia (Rural)
Job: Administrative Assistant
Education: High school GED
Content Consumption: Local News is her primary resource
Enjoys cooking for family and gardening
Personas like Paul and Kate have two major drawbacks:
They don’t help product teams figure out what to build because they don’t tell you what problems Paul and Kate have and if their problems are different from each other or the broad population you could target.
None of these characteristics preclude Paul and Kate from finding the same solution useful. This can cause you to undersize your target market and miss a big opportunity.
In other words these characteristics aren’t why Paul and Kate buy the things they do. There may be a correlation worth noting in your analysis, but it isn’t the core driver.
When Paul and Kate need to get to a destination on time, they may struggle in the same way - regardless of their characteristics.In fact, when thrv researched how to take share from Google and Apple Maps, we found that there was a group of people who struggled similarly with planning multiple stops when they tried to get to destination on time even though they had totally different demographics, psychographics, etc, like Paul and Kate. They likely make frequent and unfamiliar stops and could be salespeople, medical professionals, delivery people, or anyone who confronts this situation on a regular basis.Not only did this group have common struggles, but they were different than the broad population who didn’t have such clear and severe struggles. This is a more useful way to describe a segment because it provides direction on what to build. If a new solution satisfies the needs related to planning multiple stops, this group of people are likely to adopt it.
Characteristic-based segmentation would not put these two people in the same segment and would have caused us to undersize the addressable market and miss targeting likely buyers. Customers buy new products because they struggle to get a job done at a price they are willing to pay, regardless of their characteristics.
The same approach can be applied to B2B markets. Companies often define their customers using verticals like healthcare, consumer packaged goods, or financial services and firmographics such as the size of the company. For example, if your company provides cloud storage to CIOs at medium-sized retail companies, you might never consider selling to large financial services companies because they are a totally different segment. However, if you consider their job-to-be-done: enable secure data use for their employees you might find that companies in different verticals and different sizes struggle in the same way to get the job done.
Traditional vertical segmentation does not reveal a group of customers who struggle in the same way to get a job done. In fact, our team conducted research in this market and discovered a very valuable segment of CIOs who struggle to enable secure data use for employees because they make frequent network upgrades, not because of their vertical or size.
Read More: How to Answer The Question "What's the job-to-be-done?"
Jobs Theory demonstrates that the struggle to get the job done causes a purchase. We call this struggle an unmet customer need. To determine which customer needs are unmet, we follow these four steps.
Step 1: Run a customer effort survey of people who try to get the job done.
Ask customers how difficult it is to execute each customer need in the job. This is a customer effort score--a high score indicates a high struggle to accomplish the need.
Read more about what a customer need is.
Step 2: Cluster the respondents based on which needs they rate as high effort.
In Jobs-to-be-Done segmentation, we use K-means clustering on customer effort scores to find underserved customer segments. You can use any clustering algorithm you like. The key is to cluster respondents around the needs they rate as high effort.
We’ve studied hundreds of jobs in this way. The remarkable thing is that when we cluster survey respondents by their characteristics, we very rarely see differences in the unmet needs between a given demographic, psychographic, etc. characteristic and broad market. But if we cluster the respondents based on the unmet needs they have in common, we see clear differences with the broad market and often can identify a segment that struggles more severely and more specifically than the general population.
Step 3: Calculate the willingness to pay of each segment To identify the market size of each segment, and to determine which is the most valuable, we include a form of Van Westendorp price sensitivity questions but instead of asking about how much customers are willing to pay for your product, we ask how much they are willing to pay to get the job done. We plot their answers and draw a best fit curve through the scatter plot. The area under the curve is the size of the market.
Step 4: Target the most underserved segment with a sufficient market size
You have identified segments with unmet needs that are different from the broad market and you have calculated the willingness to pay of each segment. Now, choose a target segment that has the best combination of a high number of unmet needs you can satisfy and a market size that is large enough to justify the investment it will take to satisfy the needs.
Once you’ve selected the segment, you can use profiling characteristics to see if they will help you find it. Most advertising platforms use some form of demographics to target audiences. Look at the underlying profile traits of your target segment to see if they will help you distribute your marketing campaigns. If there are common traits among your segment, it can make your marketing efforts a bit easier. Often, though, there are no dominant traits. Don’t panic. AdWords is a very effective tool for marketing to a struggle without targeting a specific demographic.
Want to apply this method to your own company and product? Take our Jobs-to-be-Done online course, and we’ll walk you through how to survey customers correctly and how to use the JTBD statistical cluster analysis to find underserved customer segments in your market. The course includes video lessons, detailed examples, JTBD techniques, and custom exercises in your market. You will quickly get insights that you can use to build, market and sell your products.