Customer segmentation 101: A marketer’s guide to building valuable audiences
You’ve likely experienced segmented communication in your personal life. For example, if you are announcing an engagement you may choose to tell close family and friends in person, work colleagues over email, extended family by text (for younger relatives) and phone call (for older relatives), and acquaintances via a social media post.
The way that we, as humans, interact with one another can change subtly or significantly depending on who we are talking to. We may change the timing of our conversation, the slang we use, and the means of communication. While your gamer friends may be interested in hearing about the difficult game level you finally beat, the fact of the matter is your elderly aunt may not be so enthralled. (Although, maybe you should invite her over for an afternoon of gaming to share your interest – after all, women aged 50 and older make up a large portion of mobile gaming players!)
But how does this shifting dynamic pertain to businesses? And how can marketers use customer segmentation to approach their marketing communications in a more thoughtful manner? Let’s start at the beginning.
What is customer segmentation?
Customer segmentation, also known as consumer or market segmentation, is the process of grouping customers in your target audience to create a more tailored marketing message. Segmentation aims to analyze an app’s highest value users to divide potential customers into groups based on similar characteristics.
Why is customer segmentation important?
Just as you would communicate differently with your sibling, parent, or grandparent, or with a close friend, colleague, or stranger, different market segments have different communication needs. A segment’s distinct needs, traits, preferences, aversions, values, and demographics greatly impact their motivations.
As a result, different segments naturally need different marketing messages communicated to them on varying platforms to drive them to convert. These are a few of the benefits of customer segmentation:
- Bypass guesswork: Successfully scaling your app means not relying on assumptions, guesses, or beliefs. Now is the time to lean on data to help you construct strong predictive models and begin to hone in on nurturing your highest value users.
- Improve ROI: Naturally, being able to target consumers similar to your highest value app users, and using channels that have historically brought these users to your app, will help you spend advertising budget incredibly efficiently. As a result, you’ll have a higher conversion rate and a better return on investment.
- Cultivate relevancy: Wide-reaching brand awareness campaigns are important for products or industries with long consideration stages (i.e. apps in the fintech vertical, or e-commerce apps with high price tag items such as furniture). They’re also great for early days user acquisition (UA). But as you gain more insights into your users, creating more personalized campaigns will nurse potential customers down the funnel more effectively.
Types of customer segmentation
There are many factors that will affect which customer segmentation models an app marketer will use. For example, B2B and B2C segmentation will greatly vary as market size, spending power, and number of steps to purchase drastically contrast.
Regardless of whether an app is B2B or B2C, the app’s vertical, how established an app is, and the app’s business goals will also factor into which method will be the most effective.
However, at a broad level, here are some of the main customer segments:
- Demographic segmentation: Gender, age, occupation, income, education, family status, etc.
- Psychographic segmentation: Lifestyle, attitudes, values, interests, personality traits, hobbies, etc.
- Geographic segmentation: ZIP code, city, region, state, or country.
- Behavioral segmentation: Buying habits, use of app features, frequency of sessions, browsing history, average value order, purchase history, etc.
- Technographic segmentation: Which mobile device and software the consumer uses.
This information can be gathered using data from your app’s users, as well as a combination of primary and secondary market research.
How to segment customers
It’s important that you don’t organize your audience into groups without thought and strategy. This is where marketers can go wrong with segmentation. If there’s no value to the business, it’s not a valid segment of the market. The differences in segments’ traits should be productive to your marketing strategy.
To strategically approach segmentation, you should:
Decide how you are defining your highest value users.
Are your best users those who spend the most time in your app, who open your app most frequently, or spend the most money in-app? Depending on your holistic business strategy, there could be multiple categories of high-value customers. In this case, complete the below steps for each definition of ‘high-value’ to determine which will have a large enough segment to validate targeted marketing.
Analyze which channel(s) you acquired these users from.
You may find that your strongest UA channel is also where you’re acquiring your high-value users, or you may be surprised to find that a high quantity of users are coming from one channel while high-quality users are primarily coming from another.
Uncover consistencies among these users.
Run through the main types of customer segmentation to look for any consistent patterns. For example, you might find that high-spenders are either men aged 37 to 43 or women aged 29 to 35, but both of these groups live on the East coast of the United States. Collect as much information as possible.
Assess how these users are interacting with your app.
Is there a time, such as a day of the week or time of day, that they are the most active? What is their typical session frequency? Average session length? What features do they engage with the most in your app?
Derive insights from your data collection.
Based on what you have uncovered above, can you come to any conclusions about a particular group’s interests, behaviors, life stage, or needs?
Evaluate your shortlist of segments.
By now you have pulled together enough trends and patterns to have formed several segments. But not all segments will be worth tailoring a campaign to. For concentrated segments (those of small size but extremely high value), hyper personalization is a great way to create a deeper connection.
Otherwise, analyze the significance of differences between segments to narrow down which will need distinct communications.
Customer segmentation examples
Nike: Demographic segmentation
When Nike launched their Greatness campaign, they targeted various demographics with diverse assets. For example, two separate Greatness running ads were created; one to target a female audience, the other targeting a male audience.
Amazon: Psychographic segmentation
Well-known for its breadth of segmented advertising, Amazon is able to advertise relevant products based on customers’ interests and hobbies with ease thanks to their wide array of products and customer data.
Just Eat: Behavioral segmentation
Food delivery app Just Eat, known as Grubhub in the United States, created ads targeting users based on their cuisine browsing history.
Adjust and customer segmentation
Adjust’s Audience Builder allows you to effortlessly create customer segments based on a variety of data points. Choose device type, iOS or Android users, location, and relevant events. Assemble valuable segments based on time spent in-app, how recently they installed your app, how long ago their last session was, and more.
Target users with your custom audiences across ad networks like Facebook, TikTok, ironSource, and Vungle. You can even A/B test within segments to narrow down the best advertising approach for each unique cohort.
It’s easy to see why customer segmentation is known to be a primary driver of app marketing success.
Ready to get started with your app’s own customer segmentation? Learn how to connect the dots between measurement and real business outcomes or dive deeper into behavioral segmentation.
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