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If you’re going to sell successfully to your customers, you need to understand them. As the landscape becomes more competitive, staking out your customer segments and communicating with them in a way that will resonate becomes increasingly important.
This article will explore user segmentation in depth, showing you its importance and teaching you how to leverage it to optimize the experience customers have with your product or service.
For every company, there’s a segment of the population that is most likely to buy its products or services. As a very broad example, luxury brands generally appeal to wealthy people, while budget brands appeal to those with lower incomes.
However, customer segments can be much more granular. User segmentation is the process through which companies identify their customers’ characteristics and divide them into distinct groups based on those characteristics.
Perhaps, after customer segmentation, our fictional luxury brand discovers that many of its customers come from a certain profession or demographic. This information gives them a deeper understanding of the types of products, services, and marketing efforts that will best attract those customers.
Let’s take a deeper look at how segmenting users can benefit a business. Below, you’ll find several of the major reasons companies choose to undertake this process.
Segmenting your customers provides a more nuanced view of your customer base. You’ll be able to identify patterns and trends within each segment that would be difficult or impossible to spot when looking at your audience as a whole.
Nobody likes to be treated like a number or feel they’ve been given the same cookie-cutter communication as everyone else. With knowledge of the unique characteristics shared by different user segments, you can tailor your communications to speak directly to them.
One of the biggest benefits of digital advertising is the ability to target your ads with a kind of hyper-focus that simply isn’t possible without it. However, these benefits mean nothing if you don’t know who to target. Customer segmentation gives you that data.
Although a business will have multiple customer segments, each of which is important to its success, there are almost always customer segments that spend much more than others. Identifying those segments enables companies to better prioritize their efforts and resources.
As you learn more about your customer segments, you’ll also learn more about their needs and preferences. This can help you make important decisions about which new product to introduce or which features to add to existing products.
So far, all these advantages have described how the business itself benefits from being able to appeal directly to their customer’s needs. However, customers also love it when a business aligns with their preferences. Of course, this leads to increased customer loyalty, which is another significant business benefit.
Suppose your competitors haven’t analyzed their customer base but make an effort to speak directly to those demographics anyway. They simply won’t be able to fulfill the needs of that demographic as well as a company that has put in the work.
The exact process of segmenting users depends on your business goals. Below, we’ll discuss seven types of user segmentation. You can use these alone or combine them to create a more granular customer profile.
Be careful not to get carried away, though. Too many customer segments will dilute your efforts rather than focus them.
Demographic segmentation divides users based on personal demographics such as age, gender, income, education level, and marital status.
Example:
A clothing retailer might find that its customers fall into groups like “young professional women (25–35)” or “retired men (65+).” They can then tailor their product offerings and marketing messages to those specific audiences.
Behavioral segmentation groups users based on their actions. These actions are company-specific and can include things like purchasing habits, product usage, brand interactions, and loyalty.
Example:
A software company might segment users into “power users” (those who frequently use the product and its advanced features) and “occasional users” (those who only use basic features and occasionally use the product).
By following the ratio of each and tracking their habits, the company can make more informed strategies for product development and customer support.
Psychographic segmentation looks at various psychological attributes. These can include things like personality traits, values, interests, and lifestyles.
Example:
A travel company might discover that its biggest customer groups are “adventure seekers” (those who are looking for adventurous trips that are off the beaten path) and “luxury travelers” (those who prefer comfort and high-end amenities).
With this information, they know their efforts are best placed in putting together packages specifically for those two types of customers, enabling them to better serve the people to whom their brand appeals.
In the age of big data, companies have a lot of information about their customers at their disposal. Customer data segmentation uses things like purchase history, website behavior, and customer service interactions to create comprehensive profiles.
Example:
An ecommerce platform might use data from customer interactions to create segments like “high-value repeat customers” (those who frequently spend large amounts of money) or “price-sensitive bargain hunters” (those who only purchase when a good deal comes along).
With this information, they can create personalized product recommendations and promotional strategies.
This type of segmentation is used primarily in B2B contexts. It involves grouping customers based on information about the firms they work for. This information might include things like industry, company size, revenue, and location.
Example:
A business software developer groups its clients into “small tech startups,” “mid-sized manufacturing companies,” and “large financial institutions.” It creates product offerings, pricing strategies, and sales approaches that appeal to each group.
This type of segmentation is useful for tech companies because it groups customers based on their technological habits—technology preferences, usage patterns, adoption rates, and more.
Example:
A mobile app developer might group users based on their device type (iOS vs. Android), operating system version, or how frequently they use the app. They can use this data to prioritize feature development and optimize their app across different platforms.
This type of segmentation groups users according to their specific needs, pain points, or desired outcomes. It’s useful for goal-oriented products and services.
Example:
A fitness app might segment users based on their fitness goals, such as “weight loss,” “muscle gain,” or “general health maintenance.” This will allow them to provide personalized workout plans and nutrition advice.
We’ve now seen several examples of how your business can use various types of segmentation to optimize customer experiences. You may now have some idea of how to apply this technique to your own industry.
Let’s dive deeper into how to use segmentation to optimize customer experiences.
The onboarding process is one of the first experiences a customer will have with your product. Tailoring this experience to different user segments is a powerful way to increase engagement and set the customer up for long-term success and satisfaction.
Here are some ways to adapt the onboarding process to specific customer segments:
Customize welcome messages: write personalized welcome messages that address each segment’s specific goals.
Adjust feature introduction: as you introduce the user to features, prioritize those that are most likely to appeal to their segment.
Offer segment-specific tutorials: create targeted tutorials or guides that address the challenges or use cases their segment is likely to identify with.
Personalize goal-setting: use data about the customer segment to suggest goals that will appeal to them to increase their motivation and chances of success.
Users are more likely to engage with a product when the messaging matches their current needs. Personalized messaging, based on user segments, is a great way to keep engagement high.
Here are some things you can try:
Tailor email campaigns: create email campaigns specially targeted to the interests or pain points of each segment.
Personalize in-app messages: send in-app notifications or messages specific to each segment and where the user is in their journey.
Customize push notifications: use the user’s segment and behavior to send push messages that are timely and relevant.
Segment-specific content recommendations: suggest content, products, or features that are most relevant to each segment.
Preventing churn is one of the best ways to ensure business growth and a project’s long-term success. User segmentation can help reduce churn in several ways:
Identify at-risk segments: behavioral and engagement data can help you identify segments that are similar to those likely to churn.
Develop targeted retention campaigns: use your knowledge of the customer segment to create retention strategies specific to their pain points or reasons for churning.
Offer segment-specific incentives: provide incentives tailored to each specific segment that encourage them to continue using the product.
Proactive outreach: have customer support reach out to high-value customers when they detect signs of churn.
Here are some general tips that can help you get the most out of your user segmentation efforts:
Start with clear objectives: before you begin the process, understand why you’re segmenting users and how you’ll use the data.
Use multiple data sources: get a more robust view of your users by combining data from multiple touchpoints.
Keep segments actionable: as you decide which segments to split users into, ensure they are distinct enough to provide meaningful insights.
Regularly update and refine: user behavior and characteristics can change over time, so regularly review and update your segments.
Balance granularity with practicality: detailed segmentation can provide valuable insights, but if you go too granular, you’ll have too many segments to manage effectively.
Align segmentation across departments: your user segments should be the same across all departments to ensure a cohesive approach.
Test and iterate: continuously test the effectiveness of your segmentation strategies and be prepared to iterate based on the results.
Consider the customer journey: as you build out your segments, be sure to include segmentation strategies that will benefit all stages of the customer journey.
Leverage AI and machine learning: use advanced analytics tools to identify complex patterns and create more sophisticated segments.
Respect privacy and data regulations: whenever you’re dealing with customer data, be sure to respect user privacy and obey all relevant data protection laws.
User segmentation is a very popular exercise in business, so there are plenty of tools that can help you do it effectively.
Here are some popular categories of tools typically employed for user segmentation:
Tools like Google Analytics, Mixpanel, and Amplitude can segment users based on their behavior, demographics, and other attributes. After segmentation, analytics platforms let you analyze their performance across various metrics.
Customer data platforms (CDPs) like Segment, Tealium, and BlueConic collect customer data from multiple sources and turn it into a single source of truth. This makes comprehensive and accurate segmentation much easier. The platforms themselves often contain segmentation tools, further simplifying the process.
Due to how useful user segmentation is for marketers, marketing automation tools such as HubSpot, Marketo, and Mailchimp offer segmentation features. They allow you to use the segments and data collected to create targeted marketing campaigns.
Advanced machine learning algorithms can identify complex patterns in user data and create sophisticated segments based on predictive analytics. Tools like DataRobot and RapidMiner can be helpful for this purpose.
Don’t forget the need to test and iterate on what you’ve learned. A/B testing tools are the superior method for determining which segments are bringing in the best results with specific approaches.
Tools like Optimizely and VWO allow you to test which segments do the best and test different strategies within a given user segment.
User research tools like Dovetail combine qualitative and quantitative data analysis capabilities, making them particularly useful for user segmentation. With Dovetail, you can centralize user research data, analyze it, and use the insights learned to drive segmentation strategies.
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