Customer Segmentation: Key Role, Types, Usage, and Case Studies

Irrelevant marketing campaigns that don't address customers' interests and pains can quickly turn them away from a company. According to the study, 49% of consumers are annoyed by such messages, and 42% feel frustrated when they receive messages that do not meet their needs.

Audience segmentation helps to personalize marketing campaigns by focusing on separate groups of contacts that share common needs and characteristics. By understanding the wishes and demands of segment participants, marketers can find the most relevant offers for them. This focused approach drives customer conversion and improves customer experience. As a result, it increases the return on marketing investment.

Understanding Customer Segmentation

First of all, let's take a look at the definitions.

A segment is a group of contacts united by a certain characteristic, condition, or set of specific characteristics, conditions, and criteria.

The criteria for segmenting the customer base depend on:

• the industry in which the business operates;
• its target market;
• the quantity and quality of data;
• its marketing goals.

CDP helps marketers segment the database and manage these groups within a single system: run triggered marketing campaigns, analyze the groups, and perform A/B testing.

How to Approach Marketing Segmentation: Principles and Creation

Three main types of segments are key to the business, and the marketing strategy should be based on them. Let's explore their specifics in more detail.

Strategic Segments

By strategic segments, marketers mean customer groups that are most important to the company from a financial, conceptual, and communication perspective. The participants in these major segments are categorized according to:

• Life cycle (from the phase of acquaintance with the company to the level of a long-term loyal customer);
• Activity (sales, views – any actions or lack thereof);
• The product or service used by the consumer;
• Basic characteristics (gender, language, location, etc.);
• By the source of customer acquisition.

Several signs help detect a strategic segment. First, you can identify it based on specific numbers you can trust (e.g., the average check amount, the number of items in it, the NPS score, etc.). Second, the segment size is enough to use for tests and experiments. Third, there is a specific way to motivate people from this group to take your desired actions. For example, newcomers need an explanation of the benefits of buying from you, VIP customers need special service conditions and personal offers, etc.

Derived Segments

Derived segments are based on strategic groups. They are a combination of existing strategic segments but with additional clarifications and characteristics. Let’s say if we do a segmentation based on gender alone, we’ll get 4 segments: men, women, them, and ‘not specified.’ The same can be said for language, which is especially important for companies operating in a global market. By combining, adding, or extracting some characteristics, a marketer creates derived segments. For example, from the group of customers who rate our product highly, we can identify residents of a particular city whose average purchase check exceeds $250. In addition, we can remove from this subgroup those who have received marketing messages from the company in the past week. This gives us a separate segment to work with.

Microsegments

Microsegments are the solution for automation, such as trigger activation. To create them, marketers set complex conditions based on the behavioral characteristics of customers, which are constantly changing.

For example, you can add to a single segment all customers who viewed an out-of-stock product that is now available. This way, you can send a highly targeted campaign ‘Back in stock.’ Such segmentation depends on the quantity and quality of customer data. The more data you have, the more targeted trigger marketing campaigns you can set up.

The Purpose of Segmentation and the Problems It Solves

As a result, segments are needed to effectively achieve several key objectives:

• Run marketing campaigns.
• Conduct research (for example, how different segments respond to a particular message. Let's say the OR may be significantly different in the group of active readers, new subscribers, those who read the message but don't click on the link, etc;).
• Run tests (split tests, create control groups).
• Monitor (for example, set up group size tracking and automatically send a notification to the marketer if the size drops to a critical level).
• Automate processes.

One of the main benefits of segmentation is that it helps businesses solve common problems. Let's explore how.

1. Non-personalized marketing – due to the lack of information about customers' personality and their needs, companies send marketing messages that do not resonate with their targeted audience. At the same time, statistics reveal that:

• 76% of customers admitted personalized communication as the major factor making them look closely at a brand.
• 78% said personalized content in marketing messages makes them more likely to buy something again.

Customer segmentation allows you to gain valuable insights into different groups. By analyzing clients' demographics, behaviors, and preferences, you can uncover patterns and trends that help you understand their unique desires. Then, you can make informed decisions and develop communication strategies that resonate with each segment by delivering relevant messages through preferred channels at the right time.

2. Waste of time and money – without understanding your target audience and their pain points, your company produces untargeted and ineffective marketing activities. As a result, the business wastes money and team efforts. Consumer segmentation allows to allocate your resources strategically. By identifying the most profitable client segments, you can focus your efforts on channels and tactics that resonate with them the most.

3. Customer churn – when clients are faced with irrelevant experiences, they become disengaged and dissatisfied. This drives them to seek alternatives that can meet their individualized expectations. It reduces revenue as lost customers stop buying. Segmentation lets you personalize products, services, and interactions for a more satisfying customer experience. This fosters loyalty and even helps win back 74% of former customers with tailored offers.

4. The difficulty of attracting new customers – getting a new customer isn't cheap. For example, the average cost of acquiring in ecommerce is $45-50. Generic messages that lack personalization can easily go unnoticed or be dismissed. When your communication is relevant and personalized, it fosters a positive brand perception, positioning your business as customer-centric and attentive to their demands. It establishes trust and credibility for the brand.

Data for Segmentation

The quality and completeness of your data play a key role in the success of the customer segmentation strategy. To send the most fitting message to the right audience at the ideal moment, businesses require Big Data. Therefore, having access to accurate and up-to-date user information is essential. The CDP can make this process possible. Let's explore the data Yespo CDP can collect, manage, and utilize for segmentation:

1. Static data – any information a customer shares with you (name, gender, birthdate, email, push token, phone number, location, marital status, children, etc.).

2. Activity in campaigns with the specified details:

    a. Time (how much activity there was during a specific period).

    b. Interaction type (promo or trigger, daytime, nighttime messages, etc.).

    c. Direct channels in which the customer is active (email, mob push, web push, app inbox, in-app, widgets, SMS, messengers).

3. Purchase history – what products does the customer buy, from what category, at what frequency, what is the average check size, how much money is spent, and so on.

4. User events – all data coming into the CDP about the customer's actions on the website, in the app, in channels, or offline. To track the behavior of web visitors, you need to implement web tracking. To set up the sending of events from the app, use the Yespo SDK.

Let’s use an example of how it works in e-commerce. A person visits your website and fills out a subscription form, leaving their name, email, and phone number. Yespo creates a user profile card and automatically collects data about the subscriber's behavior on the website and in direct channels. When the customer receives a promotional email and follows a link to the page of the product of interest, the system will recognize the person even without authorization on the site. Information about this visit and online actions will automatically update the data of the unified customer profile. This ensures that the data is complete, which is necessary for high-quality segmentation.

Types of Customer Segmentation in Yespo

Based on the intensity of exploration, segmentation is divided into basic and advanced types. You can combine conditions of different types when building a group. This means setting general conditions first and then adding more narrow and specific parameters to them. You can include and exclude any number of parameters and conditions when building audience segments in Yespo. Let's take a closer look at the different types of segmentation.

1. Basic Segmentation

With basic segmentation, a marketer can split the target audience by key characteristics if they are pre-saved in the CDP. 

Demographic segmentation categorizes individuals based on average human characteristics common to large groups of people:

• age;
• gender;
• education;
• pet ownership;
• job, and more.

While this type serves as an initial step in the segmentation strategy, it provides valuable insights into consumer behavior and preferences. It allows businesses to tailor their marketing efforts and offerings to specific demographic groups. For example, before International Women's Day, a marketer segments the audience into women and men. The brand offers women products relevant to them, while men are encouraged to look at women's products for gifts. Demographic segmentation helps businesses make informed decisions regarding product development, pricing strategies, and audience touchpoints.

Geographic segmentation refers to factors related to the physical location of clients. These variables provide valuable insights into customers' surroundings and enable businesses to adapt their marketing strategies accordingly. Some of the most common geographic variables applied in the customer segmentation model:

• Country – allows to address unique cultural aspects, legal requirements, and economic conditions that vary across different regions.
• City – marketers can customize their messaging to reflect the local culture, preferences, or events. This approach is particularly effective for brick-and-mortar businesses.
• Time zone – is essential to ensure that communications reach customers at appropriate times, avoiding the annoyance of untimely or intrusive messages.

Multiplex, the largest cinema chain in Ukraine, segments its customers by city of residence and favorite cinema. For example, residents of a city receive news about upcoming movie premieres or other cultural events, while fans of a particular cinema are informed about updated seats, new film formats, etc. The company's marketer conducted a test between generic and segmented emails. The test showed that for the same open rate, segmented messages had a 4% higher CTOR. It was also found that personalized email content resulted in 51.3% more sales than generic emails.

2. Advanced Segmentation

All CDPs allow you to segment contacts by rules, while more complex platforms, such as Yespo, have sophisticated architecture and extensive data processing capabilities.

Our clients use basic segmentation for free. Advanced segmentation is available in paid plans. Advanced segmentation allows you to drill down into more individual characteristics. The groups identified in this way are smaller, but they can be targeted with more appropriate offers that take into account the unique wishes and needs of the customers.

1. Behavioral segmentation

Behavioral segmentation allows you to divide the audience by analyzing customer interactions with a business. There are several common types of behavioral segmentation based on:

• frequency of use (active customers, mid-clients, weak consumers, non-users);
• advantages (customers sharing the same key benefits they are looking for in a product or service);
• brand loyalty (newcomers, repeat buyers, loyal customers, brand ambassadors, raving fans).

Personalized experience based on behavior is one of the main requirements driving conversion in retail. Analyzing customer actions through behavioral segmentation allows businesses to uncover meaningful signs that indicate customers' intentions. Marketers can send timely triggers and personalized messages to stimulate conversion actions, such as offering a limited-time discount or providing additional product recommendations.

This type of segmentation is crucial for the Ukrainian marketplace of promotional offers Pokupon. The content of promo emails is customized to the interests of each subscriber based on their order history. Subscribers are segmented using multiple conditions. Their activity is taken into account: the time period since the last purchase, as well as customer actions on the website, in the app, and in marketing campaigns. In addition, all contacts are divided by favorite categories: Beauty, Food and Restaurants, Health, and Entertainment. Users are included in the respective segments if they have made at least one purchase in a category. The content of each recipient's email is made up of promotions selected based on their interests. Dynamic content is added using SRT blocks. Thanks to segmentation and personalization, the company has achieved results such as:

• 49.1% growth of the website traffic from the email channel;
• 17.7% growth of the number of active customers;
• 15.6% revenue increase.

Marketers were able to get the following performance indicators in just three months.

2. Segmentation by events

Segmentation by events allows businesses to categorize customers into groups based on specific events and their corresponding parameters. These events can include actions like placing an order and their particular parameters, such as the order amount. For example, you can select a segment of subscribers who clicked on a specific link from a marketing message, or opened only triggered messages and did not read mass campaigns at all, etc. You can also create more detailed conditions based on the behavior of website users. For example, set a condition to form a group of online store visitors who have browsed bags over a certain value during 3 last weeks.

By defining the necessary conditions using these event parameters, businesses can create distinct customer segments and tailor exclusive offers specifically for each group.

For example, an online store that sells women's clothing, shoes, and accessories segments subscribers by their preferred clothing sizes. To do this, marketers added СTA buttons with sizes to promotional emails. When a person clicks on the selected option, the event is recorded, and the consumer is added to the appropriate contact group. The subscriber then receives emails with offers in their preferred size. As a result of this segmentation, customer engagement has nearly doubled, and the number of active customers has increased by 20%.

3. RFM segmentation

RFM segmentation is based on analyzing the date, number of purchases, and total value of orders to categorize customers into distinct segments. Here are the main segments that can be identified using the RFM method and the options for triggers and campaigns for them:

• newcomers – a welcome chain of messages;
• regular buyers – promotional campaigns, emails with useful content;
• VIP – exclusive offers (referral or loyalty programs, early access to sales, and unique rewards);
• customers at risk – use additional motivators for purchase (targeted comeback offers such as limited-time discounts or free shipping);
• lost clients – those who have not bought for more than a year. It is better to leave them alone.

By utilizing this data-driven approach, businesses can effectively identify customer behavior patterns and preferences. It forecasts their likelihood of transitioning between segments. Leveraging this segmentation analysis, businesses can establish triggers to automatically send relevant campaigns to users when they move to specific segments.

Purchases and Email Engagement

Traditionally, RFM is based on purchases. However, with Yespo CDP, we have taken it a step further by offering the same analysis for email engagement. Instead of the number of sales, the matrix is built on the basis of opens and clicks, enabling companies to identify the most engaged subscribers and automate communications based on the contacts' movements through such segments.

For example, marketers at Ukrainian retailer Stylus used RFM analysis to identify inactive customers and try to reactivate them. They sent emails with personalized discounts and a survey to subscribers in the dormant segment. As a result, the company regained full communication with 5% of previously inactive subscribers.

4. Cohort Analysis Segmentation

With cohort analysis, a marketer segments the contact base into groups or cohorts. These include customers who are related to each other by a certain event that occurred at a specific moment: 

• adding a contact to the base;
• registering on the website; 
• making the first purchase;
• installing a mobile app, etc.

A marketer can identify and analyze behavioral patterns throughout the customer lifecycle. In the Yespo omnichannel CDP, segmentation by cohort helps track customer retention. This allows you to identify periods when customer engagement drops across all cohorts. If you see this pattern in consumer behavior during certain times of the year, you can plan marketing campaigns. For example, if you see that contacts' activity in channels decreases in July every year, you may want to hold off releasing new products during that month. You can also compare the performance of different cohorts. For example, compare the activity of contacts who subscribed to the newsletter during the BFCM with other cohorts. This will help you understand whether big sales are attracting long-term customers or just people who were interested in a one-time purchase with a big discount.

5. Value-based customer segmentation

Value-based customer segmentation uses key value indicators to measure buying behavior. Let's explore some examples of them:

• number of purchases – this allows to identify loyal and repeat buyers, as well as those who may require incentives to increase their purchase frequency;
• average purchase value – it enables to target customers who have a higher ability for spending and tailor marketing efforts to maximize revenue generation;
• order contents (items) – by identifying patterns and preferences, businesses can deliver personalized recommendations to drive additional sales.

Value-based segmentation helps businesses to create highly targeted marketing campaigns tailored to specific customer groups. By delivering personalized messages and offers, companies can significantly enhance customer engagement and drive conversion rates.

This segmentation approach also enables to identify valuable customers who may display signs of declining engagement or satisfaction. By addressing their concerns, improving their experience, and providing tailored solutions, companies can effectively reduce customer churn and increase customer loyalty.

Moreover, value-based segmentation allows businesses to pinpoint clients with a high potential lifetime value. These individuals demonstrate significant purchasing abilities and are more likely to establish long-term relationships with the company. By focusing resources on these customers and nurturing those relationships, businesses can optimize long-term profitability.

6. Predictive segmentation

Predictive segmentation helps businesses to proactively understand clients' behavior and tailor their marketing strategies accordingly. Yespo provides a set of AI algorithms forecasting the likelihood of customer acquisition or churn and building corresponding contact segments. Artificial intelligence can also predict the likelihood that a customer is ready to make a purchase. In this case, our AI algorithms consider the following markers of consumer behavior:

• increased website visits;
• browsing activity;
• reviews and feedback exploration;
• chat interactions;
• discount clicks;
• average decision-making time for clients.

Unlike the above-mentioned ‘algorithmic’ segmentation strategies mentioned above, this strategy takes into account not only previous purchases or engagement in some direct channel but also a host of other factors. All the data points related to a customer, such as web pages viewed, emails opened, banners clicked, and recent events, when considered together, can provide additional insight into their current state – whether they are ready to buy or likely to churn.

Once you realize that the customer is almost ready to finalize the deal, you can encourage them to complete it with some perks, such as free shipping or a promotional code for a discount on their next order, etc. Using this AI-powered customer segmentation tool, you’ll enhance CLV rate, showing consumers you care about their needs.

For example, by implementing customized predictive segmentation, the RetouchMe app was able to increase the number of VIP users and increase revenue. Yespo's Data Science team has developed algorithms that can identify potential VIP users among newcomers with 99% accuracy. They do this quite quickly – within a week from the first customer order. The algorithms analyze various parameters: the frequency of orders, customer preferences for photo editing, whether or not discounts are applied, the frequency of requests for re-editing, etc.

Artificial intelligence not only identifies the segment of the most valuable users but also forms the group of candidates to join the customer retention program. The algorithms predict when a particular user will place their next order. Thanks to Yespo's predictive user segmentation, the number of VIP customers of the app increased by 35% in 3 months, and revenue grew by 17%.

7. Parametric segmentation

Parametric segmentation offers a time-saving solution when creating campaigns for similar groups that differ only in a specific parameter. Traditionally, announcing promotions in different categories required separate segments and workflows for each product category. However, with parametric segmentation, only one segment is needed. For example, today, an event with one condition, such as a product section, is entered into the system, and tomorrow with another. Different contacts from the group are automatically selected for the campaign according to the event parameters. At the same time, the group itself and the workflow do not need to be changed.

Parametric groups are used only in workflows. You can set conditions directly in the segment or import them from events. This tool works with group blocks of sending messages across all media channels.

This streamlined approach eliminates the need for duplicating efforts and allows for efficient and automated campaign launches, saving valuable time and resources.

Measuring and Evaluating Results of Customer Segmentation

To understand whether your segmentation strategy is working, regularly measure the key KPIs important to your business. Watch their performance in the groups you've selected. These can be:

• Conversion rate (analyzing the number of contacts who took a conversion action, such as placing an order, using a promo code, etc.);
• Customer retention;
• Customer lifetime value;
• Engagement metrics (click-through rates, open rates);
• Customer churn rate;
• Customer satisfaction score, etc;
• Segment profitability (determining whether the profit is higher than budgeted).

By monitoring key performance indicators, businesses can gain insights into the effectiveness of their segmentation efforts. For example, tracking the conversion rate within each segment allows to know how effectively the targeted messaging and offers are driving customer actions, such as purchases, registrations, or other desired outcomes. Comparing conversion rates across different segments helps identify segments that respond most favorably to the tailored marketing efforts.

Customer segmentation is not a one-time task but an ongoing process that requires constant improvement. Based on the information gained from tracking campaign performance metrics, companies can make data-driven decisions to refine and improve their segmentation strategies.

Analyzing the performance of each segment allows to identify segments that are underperforming or have untapped potential. This analysis helps to find areas where segmentation strategies can be improved or changed.

Conducting A/B tests in specific segments allows companies to experiment with different approaches and messages to find out what resonates most deeply with each group. These experiments provide valuable insights to refine segmentation strategies and optimize customer engagement.

Continuous monitoring of campaign performance metrics and customer feedback is essential to ensure that segmentation strategies are always in line with changing customer preferences.

Conclusions

Customer segmentation is a powerful tool offering a solution to overcome non-personalized marketing, wastage of resources, customer churn, and challenges in acquiring new clients. Using the full potential of CDPs and various segmentation methods, companies can tailor their marketing efforts with accuracy and relevance.

For example, the Multiplex case study showed that emails with personalized content for a geographically segmented audience generated more sales than mass mailings. By implementing behavioral segmentation and personalization, Pokupon increased traffic to its website from the email channel and grew the number of active customers. Using event-based segmentation, an online women's apparel store doubled customer engagement and increased active customers by 20%.

Yespo's advanced segmentation based on AI and machine learning helps companies use sophisticated algorithms to gain richer insights and discover hidden patterns in customer data. This is confirmed by the case of the RetouchMe app, which showed that Yespo's AI algorithms are able to identify potential VIP customers among new users with extreme accuracy.

It is important to realize that the work doesn't end with the implementation. Measuring and evaluating the results of customer segmentation is crucial for continuous improvement. By analyzing the effectiveness of segmentation strategies, marketers can refine their approaches, adapt to changing customer needs, and increase the overall effectiveness of marketing efforts.

For more information on how our CDP can help your business, contact us at info@yespo.io, and we will be happy to answer any questions you may have. Or book a demo and see how easy it is to work with the platform.