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• Marketing Cohort Analysis : How To Do It (With Examples)

  12 janvier 2024, par Erin

  The better you understand your customers, the more effective your marketing will become. 

  The good news is you don’t need to run expensive focus groups to learn much about how your customers behave. Instead, you can run a marketing cohort analysis using data from your website analytics.

  A marketing cohort groups your users by certain traits and allows you to drill down to discover why they take the actions on your website they do. 

  In this article, we’ll explain what a marketing cohort analysis is, show you what you can achieve with this analytical technique and provide a step-by-step guide to pulling it off. 

  What is cohort analysis in marketing ?

  A marketing cohort analysis is a form of behavioural analytics where you analyse the behavioural patterns of users who share a similar trait to better understand their actions. 

  These shared traits could be anything like the date they signed up for your product, users who bought your service through a paid ad or email subscribers from the United Kingdom.

  It’s a fantastic way to improve your marketing efforts, allowing you to better understand complex user behaviours, personalise campaigns accordingly and improve your ROI. 

  You can run marketing analysis using an analytics platform like Google Analytics or Matomo. With these platforms, you can measure how cohorts perform using traffic, engagement and conversion metrics.

  

  There are two types of cohort analysis : acquisition-based cohort analysis and behavioural-based cohort analysis.

  Acquisition-based cohort analysis

  An acquisition-based cohort divides users by the date they purchased your product or service and tracks their behaviour afterward. 

  For example, one cohort could be all the users who signed up for your product in November. Another could be the users who signed up for your product in October. 

  You could then run a cohort analysis to see how the behaviour of the two cohorts differed. 

  Did the November cohort show higher engagement rates, increased frequency of visits post-acquisition or quicker conversions compared to the October cohort ? Analysing these cohorts can help with refining marketing strategies, optimising user experiences and improving retention and conversion rates.

  As you can see from the example, acquisition-based cohorts are a great way to track the initial acquisition and how user behaviour evolves post-acquisition.

  Behavioural-based cohort analysis

  A behavioural-based cohort divides users by their actions on your site. That could be their bounce rate, the number of actions they took on your site, their average time on site and more.

  

  Behavioural cohort analysis gives you a much deeper understanding of user behaviour and how they interact with your website.

  What can you achieve with a marketing cohort analysis ?

  A marketing cohort analysis is a valuable tool that can help marketers and product teams achieve the following goals :

  

  Understand which customers churn and why

  Acquisition and behavioural cohort analyses help marketing teams understand when and why customers leave. This is one of the most common goals of a marketing cohort analysis. 

  Learn which customers are most valuable

  Want to find out which channels create the most valuable customers or what actions customers take that increase their loyalty ? You can use a cohort analysis to do just that. 

  For example, you may find out you retain users who signed up via direct traffic better than those that signed up from an ad campaign. 

  Discover how to improve your product

  You can even use cohort analysis to identify opportunities to improve your website and track the impact of your changes. For example, you could see how visitor behaviour changes after a website refresh or whether visitors who take a certain action make more purchases. 

  Find out how to improve your marketing campaign

  A marketing cohort analysis makes it easy to find out which campaigns generate the best and most profitable customers. For example, you can run a cohort analysis to determine which channel (PPC ads, organic search, social media, etc.) generates customers with the lowest churn rate. 

  If a certain ad campaign generates the low-churn customers, you can allocate a budget accordingly. Alternatively, if customers from another ad campaign churn quickly, you can look into why that may be the case and optimise your campaigns to improve them. 

  Measure the impact of changes

  You can use a behavioural cohort analysis to understand what impact changes to your website or product have on active users. 

  If you introduced a pricing page to your website, for instance, you could analyse the behaviour of visitors who interacted with that page compared to those who didn’t, using behavioural cohort analysis to gauge the impact of these website changes on engagemen or conversions.

  The problem with cohort analysis in Google Analytics

  Google Analytics is often the first platform marketers turn to when they want to run a cohort analysis. While it’s a free solution, it’s not the most accurate or easy to use and users often encounter various issues. 

  For starters, Google Analytics can’t process user visitor data if they reject cookies. This can lead to an inaccurate view of traffic and compromise the reliability of your insights.

  In addition, GA is also known for sampling data, meaning it provides a subset rather than the complete dataset. Without the complete view of your website’s performance, you might make the wrong decisions, leading to less effective campaigns, missed opportunities and difficulties in reaching marketing goals.

  How to analyse cohorts with Matomo

  Luckily, there is an alternative to Google Analytics. 

  As the leading open-source web analytics solution, Matomo offers a robust option for cohort analysis. With its 100% accurate data, thanks to the absence of sampling, and its privacy-friendly tracking, users can rely on the data without resorting to guesswork. It is a premium feature included with our Matomo Cloud or available to purchase on the Matomo Marketplace for Matomo On-Premise users.

  Below, we’ll show how you can run a marketing cohort analysis using Matomo.

  Set a goal

  Setting a goal is the first step in running a cohort analysis with any platform. Define what you want to achieve from your analysis and choose the metrics you want to measure. 

  For example, you may want to improve your customer retention rate over the first 90 days. 

  Define cohorts

  Next, create cohorts by defining segmentation criteria. As we’ve discussed above, this could be acquisition-based or behavioural. 

  Matomo makes it easy to define cohorts and create charts. 

  In the sidebar menu, click Visitors > Cohorts. You’ll immediately see Matomo’s standard cohort report (something like the one below).

  

  In the example above, we’ve created cohorts by bounce rate. 

  You can view cohorts by weekly, monthly or yearly periods using the date selector and change the metric using the dropdown. Other metrics you can analyse cohorts by include :

  • Unique visitors
  • Return visitors
  • Conversion rates
  • Revenue
  • Actions per visit

  Change the data selection to create your desired cohort, and Matomo will automatically generate the report. 

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  Analyse your cohort chart

  Cohort charts can be intimidating initially, but they are pretty easy to understand and packed with insights. 

  Here’s an example of an acquisition-based cohort chart from Matomo looking at the percentage of returning visitors :

  

  Cohorts run vertically. The oldest cohort (visitors between February 13 – 19) is at the top of the chart, with the newest cohort (April 17 – 23) at the bottom. 

  The period of time runs horizontally — daily in this case. The cells show the corresponding value for the metric we’re plotting (the percentage of returning visitors). 

  For example, 98.69% of visitors who landed on your site between February 13 – 19, returned two weeks later. 

  Usually, running one cohort analysis isn’t enough to identify a problem or find a solution. That’s why comparing several cohort analyses or digging deeper using segmentation is important.

  Segment your cohort chart

  Matomo lets you dig deeper by segmenting each cohort to examine their behaviour’s specifics. You can do this from the cohort report by clicking the segmented visitor log icon in the relevant row.

  

  

  Segmenting cohorts lets you understand why users behave the way they do. For example, suppose you find that users you purchased on Black Friday don’t return to your site often. In that case, you may want to rethink your offers for next year to target an audience with potentially better customer lifetime value. 

  Start using Matomo for marketing cohort analysis

  A marketing cohort analysis can teach you a lot about your customers and the health of your business. But you need the right tools to succeed. 

  Matomo provides an effective and privacy-first way to run your analysis. You can create custom customer segments based on almost anything, from demographics and geography to referral sources and user behaviour. 

  Our custom cohort analysis reports and colour-coded visualisations make it easy to analyse cohorts and spot patterns. Best of all, the data is 100% accurate. Unlike other web analytics solution or cohort analysis tools, we don’t sample data. 

  Find out how you can use Matomo to run marketing cohort analysis by trialling us free for 21 days. No credit card required.

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• Top 5 Customer Segmentation Software in 2024

  12 mars 2024, par Erin

  In marketing, we all know the importance of reaching the right customer with the right message at the right time. That’s how you cut through the noise.

  For that, you need data on your customers — even though gathering the data is not enough. You can have all the data worldwide, but that raises an ethical responsibility and the need to make sense of it.

  Enter customer segmentation software — the answer to delivering personalised customer experiences at scale. 

  This article lists some of the best customer segmentation tools currently in the market. 

  We’ll also go over the benefits of using such tools and how you can choose the best one for your business.

  Let’s get started !

  What is customer segmentation software ?

  Customer segmentation software is a tool that helps businesses analyse customer data and group them based on common characteristics like age, income, and buying habits.

  The main goal of customer segmentation is to gain deeper insights into customer behaviours and preferences. This helps create targeted marketing and product strategies that fit each group and makes it easier to predict how customers will behave in the future.

  

  Benefits of a customer segmentation software

  Understanding your customers is the cornerstone of effective marketing, and customer segmentation software plays a pivotal role in this endeavour. 

  You can deliver more targeted and relevant marketing campaigns by dividing your audience into distinct groups based on shared characteristics. 

  Specifically, here are the main benefits of using customer segmentation tools :

  • Understand your audience better : The software helps businesses group customers with common traits to better understand their preferences and behaviour.
  • Make data-driven decisions : Base your business and marketing decisions on data analytics.
  • Aid product development : Insights from segmentation analytics can guide the creation of products that meet specific customer group needs.
  • Allocate your resources efficiently : Focusing on the customer segments that generate the most revenue leads to more effective and strategic use of your marketing resources.

  Best customer segmentation software in 2024 

  In this section, we go over the top customer segmentation tools in 2024. 

  We’ll look at these tools’ key features and pros and cons.

  1. Matomo

  

  Matomo is a comprehensive web analytics tool that merges traditional web analytics, such as tracking pageviews and visitor bounce rates, with more advanced web analytics features for tracking user behaviour. 

  With robust segmentation features, users can filter website traffic based on criteria such as location and device type, enabling them to analyse specific visitor groups and their behaviour. Users can create custom segments to analyse specific groups of visitors and their behaviour.

  Presenting as the ethical alternative to Google Analytics, Matomo emphasises transparency, 100% accurate data, and compliance with privacy laws.

  Key features

  • Heatmaps and Session Recordings : Matomo provides tools that allow businesses to understand website user interactions visually. This insight is crucial for optimising user experience and increasing conversions.
  • Form Analytics : This feature in Matomo tracks how users interact with website forms, helping businesses understand user behaviour in detail and improve form design and functionality.
  • User Flow Analysis : The tool tracks the journey of a website’s visitors, highlighting the paths taken and where users drop off. This is key for optimising website structure for better user experience and more conversions.
  • A/B Testing : Businesses can use Matomo to test different versions of web pages, determining which is more effective in driving conversions.
  • Conversion Funnels : This feature allows businesses to visualise and optimise the steps customers take toward conversion, identifying areas for improvement.

  Pros 

  • Affordability : With plans starting at $19 per month, Matomo is a cost-effective solution for CRO.
  • Free support : Matomo provides free email support to all Matomo Cloud users.
  • Open-source benefits : Being open-source, Matomo offers enhanced security, privacy, customisation options, and a supportive community.
  • Hosting options : Matomo is available either as a self-hosted solution or cloud-hosted.

  Cons

  • Cost for advanced features : Access to advanced features may incur additional costs for Matomo On-Premise users, although the On-Premise solution itself is free.
  • Technical knowledge required : The self-hosted version of Matomo requires technical knowledge for effective management.

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  2. Google Analytics 

  

  Google Analytics 4 (GA4) comprehensively understands website and app performance. It focuses on event-based data collection, allowing businesses to understand user interactions across platforms. 

  Similarly to Matomo, GA4 provides features that allow businesses to segment their audience based on various criteria such as demographics, behaviours, events, and more.

  Key features

  • Event-based tracking : GA4’s shift to an event-based model allows for a flexible and predictive analysis of user behaviour. This includes a detailed view of user interactions on websites and apps.
  • Machine Learning and Smarter Insights : GA4 uses machine learning to automatically detect trends, estimate purchase probabilities and provide marketing insights.
  • Google Ads integration : The integration with Google Ads in GA4 enables tracking customer interactions from first ad engagement, providing a holistic view of the customer experience across various platforms.
  • Customer-centric measurements : GA4 collects data as events, covering a wide range of user interactions and offering a comprehensive view of customer behaviour.
  • Pathing reports : GA4 introduces new pathing reports, allowing detailed user flow analysis through websites and apps.
  • Audiences and filters : GA4 allows the creation of audiences based on specific criteria and the application of filters to segment and refine data analysis.

  Pros 

  • Integration with various platforms, including Google Ads, enhances cross-platform user journey analysis.
  • GA4 has a clean reporting interface, making it easier for marketers to identify key trends and data irregularities.
  • Google Analytics has an active community with an abundance of educational resources available for users.

  Cons

  • Complexity for beginners : The wide range of features and new event-based model might overwhelm users new to analytics tools.
  • Dependence on machine learning : Reliance on machine learning for insights and predictions may require trust in the tool’s data processing and large volumes of traffic for accuracy.
  • Transition from UA to GA4 : Users familiar with Universal Analytics (UA) might find the transition to GA4 challenging due to differences in features and data models.

  3. HubSpot

  

  HubSpot is a marketing and sales software that helps businesses attract visitors and turn them into paying customers. 

  It supports various business processes, from social media posts to email marketing, sales, and customer service. HubSpot organises and tracks user interactions across different channels, providing a unified and efficient approach to customer relationship management (CRM) and customer segmentation.

  Businesses can leverage HubSpot’s customer segmentation through lists, workflows, and smart content.

  Key features

  • Integration capabilities : HubSpot offers over 1,000 integrations in its ecosystem, ensuring seamless connectivity across various marketing, sales, and service tools, which helps maintain data consistency and reduces manual efforts.
  • Segmentation and personalisation : HubSpot allows businesses to deliver personalised content and interactions based on customer behaviour and preferences, using its robust CRM features and advanced automation capabilities.

  Pros 

  • Comprehensive support : HubSpot offers a range of support options, including a knowledge base, real-time chat, and more.
  • User-friendly interface : The platform is designed for ease of use, ensuring a smooth experience even for less tech-savvy users.
  • Personalisation capabilities : HubSpot provides personalised marketing, sales and service experiences, leveraging customer data effectively.

  Cons

  • High price point : HubSpot can be expensive, especially as you scale up and require more advanced features.
  • Steep learning curve : For businesses new to such comprehensive platforms, there might be an initial learning curve to utilise its features effectively.

  4. Klaviyo

  

  Klaviyo is a marketing automation software primarily focused on email and SMS messaging for e-commerce businesses. It’s designed to personalise and optimise customer communication. 

  Klaviyo integrates with e-commerce platforms like Shopify, making it a go-to solution for online stores. Its strength lies in its ability to use customer data to deliver targeted and effective marketing campaigns.

  Key features

  • Email marketing automation : Klaviyo allows users to send automated and personalised emails based on customer behaviour and preferences. This feature is crucial for e-commerce businesses in nurturing leads and maintaining customer engagement.
  • SMS marketing : It includes SMS messaging capabilities, enabling businesses to engage customers directly through text messages.
  • Segmentation and personalisation : Klaviyo offers advanced segmentation tools that enable businesses to categorise customers based on their behaviour, preferences and purchase history, facilitating highly targeted marketing efforts.
  • Integration with e-commerce platforms : Klaviyo integrates with popular e-commerce platforms like Shopify, Magento, and WooCommerce, allowing easy data synchronisation and campaign management.

  Pros 

  • Enhanced e-commerce integration : Klaviyo’s deep integration with e-commerce platforms greatly benefits online retailers regarding ease of use and campaign effectiveness.
  • Advanced segmentation and personalisation : The platform’s strong segmentation capabilities enable businesses to tailor their marketing messages more effectively.
  • Robust automation features : Klaviyo’s automation tools are powerful and user-friendly, saving time and improving marketing efficiency.

  Cons

  • Cost : Klaviyo can be more expensive than other options in this list, particularly as you scale up and add more contacts.
  • Complexity for beginners : The platform’s wide range of features and advanced capabilities might overwhelm beginners or small businesses with simpler needs.

  5. UserGuiding

  

  UserGuiding is a no-code product adoption tool that lets businesses create in-app user walkthroughs, guides, and checklists to onboard, engage, and retain users.

  UserGuiding facilitates customer segmentation by enabling businesses to create segmented onboarding flows, analyse behavioural insights, deliver personalised guidance, and collect feedback tailored to different user segments.

  Key features

  • In-app walkthroughs, guides and checklists : UserGuiding has multiple features that can promote product adoption early in the user journey.
  • In-app messaging : UserGuiding offers in-app messaging to help users learn more about the product and various ways to get value.
  • User feedback : UserGuiding allows businesses to gather qualitative feedback to streamline the adoption journey for users.

  Pros 

  • User-friendly interface
  • Customisable onboarding checklists
  • Retention analytics

  Cons

  • Need for technical expertise to maximise all features
  • Limited customisation options for less tech-savvy users

  What to look for in a customer segmentation software 

  When choosing a customer segmentation software, choosing the right one for your specific business needs is important. 

  Here are a few factors to consider when choosing your customer segmentation tool :

  1. Ease of use : Select a tool with an intuitive interface that simplifies navigation. This enhances the user experience, making complex tasks more manageable. Additionally, responsive customer support is crucial. It ensures that issues are promptly resolved, contributing to a smoother operation.
  2. Scalability and flexibility : Your chosen tool should adjust to your needs. A flexible tool like Matomo can adjust to your growing requirements, offering capabilities that evolve as your business expands.
  3. Integration capabilities : The software should seamlessly integrate with your existing systems, such as CRM, marketing, and automation platforms. 
  4. Advanced analytics and reporting : Assess the software’s capability to analyse and interpret complex data sets, without relying on machine learning to fill data gaps. A robust tool should provide accurate insights and detailed reports, enabling you to make informed decisions based on real data.
  5. Privacy and security considerations : Data security is paramount in today’s digital landscape. Look for features like data encryption, security storage, and adherence to privacy standards like GDPR and CCPA compliance. 
  6. Reviews and recommendations : Before making a decision, consider the reputation of the software providers. Look for reviews and recommendations from other users, especially those in similar industries. This can provide real-world insights into the software’s performance and reliability.

  

  Leverage Matomo’s segmentation capabilities to deliver personalised experiences

  Segmentation is the best place to start if you want to deliver personalised customer experiences. There are several customer segmentation software in the market. But they’re not all the same.

  In this article, we reviewed the top segmentation tools — based on factors like their user base, features, and ethical data privacy considerations.

  Ideally, you want a tool to support your evolving business and segmentation needs. Not to mention one that cares about your customers’ privacy and ensures you stay compliant. 

  Enter Matomo at the top of the list. You can leverage Matomo’s accurate insights and comprehensive segmentation capabilities without compromising on privacy. Try it free for 21-days. No credit card required.

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• 10 Customer Segments Examples and Their Benefits

  9 mai 2024, par Erin

  Now that companies can segment buyers, the days of mass marketing are behind us. Customer segmentation offers various benefits for marketing, content creation, sales, analytics teams and more. Without customer segmentation, your personalised marketing efforts may fall flat. 

  According to the Twilio 2023 state of personalisation report, 69% of business leaders have increased their investment in personalisation. There’s a key reason for this — customer retention and loyalty directly benefit from personalisation. In fact, 62% of businesses have cited improved customer retention due to personalisation efforts. The numbers don’t lie. 

  Keep reading to learn how customer segments can help you fine-tune your personalised marketing campaigns. This article will give you a better understanding of customer segmentation and real-world customer segment examples. You’ll leave with the knowledge to empower your marketing strategies with effective customer segmentation. 

  What are customer segments ?

  Customer segments are distinct groups of people or organisations with similar characteristics, needs and behaviours. Like different species of plants in a garden, each customer segment has specific needs and care requirements. Customer segments are useful for tailoring personalised marketing campaigns for specific groups.

  Personalised marketing has been shown to have significant benefits — with 56% of consumers saying that a personalised experience would make them become repeat buyers. 

  Successful marketing teams typically focus on these types of customer segmentation :

  

  1. Geographic segmentation : groups buyers based on their physical location — country, city, region or climate — and language.
  2. Purchase history segmentation : categorises buyers based on their purchasing habits — how often they make purchases — and allows brands to distinguish between frequent, occasional and one-time buyers. 
  3. Product-based segmentation : groups buyers according to the products they prefer or end up purchasing. 
  4. Customer lifecycle segmentation : segments buyers based on where they are in the customer journey. Examples include new, repeat and lapsed buyers. This segmentation category is also useful for understanding the behaviour of loyal buyers and those at risk of churning. 
  5. Technographic segmentation : focuses on buyers’ technology preferences, including device type, browser type, and operating system. 
  6. Channel preference segmentation : helps us understand why buyers prefer to purchase via specific channels — whether online channels, physical stores or a combination of both. 
  7. Value-based segmentation : categorises buyers based on their average purchase value and sensitivity to pricing, for example. This type of segmentation can provide insights into the behaviours of price-conscious buyers and those willing to pay premium prices. 

  Customer segmentation vs. market segmentation

  Customer segmentation and market segmentation are related concepts, but they refer to different aspects of the segmentation process in marketing. 

  Market segmentation is the broader process of dividing the overall market into homogeneous groups. Market segmentation helps marketers identify different groups based on their characteristics or needs. These market segments make it easier for businesses to connect with new buyers by offering relevant products or new features. 

  On the other hand, customer segmentation is used to help you dig deep into the behaviour and preferences of your current customer base. Marketers use customer segmentation insights to create buyer personas. Buyer personas are essential for ensuring your personalised marketing efforts are relevant to the target audience. 

  10 customer segments examples

  Now that you better understand different customer segmentation categories, we’ll provide real-world examples of how customer segmentation can be applied. You’ll be able to draw a direct connection between the segmentation category or categories each example falls under.

  One thing to note is that you’ll want to consider privacy and compliance when you are considering collecting and analysing types of data such as gender, age, income level, profession or personal interests. Instead, you can focus on these privacy-friendly, ethical customer segmentation types :

  1. Geographic location (category : geographic segmentation)

  The North Face is an outdoor apparel and equipment company that relies on geographic segmentation to tailor its products toward buyers in specific regions and climates. 

  For instance, they’ll send targeted advertisements for insulated jackets and snow gear to buyers in colder climates. For folks in seasonal climates, The North Face may send personalised ads for snow gear in winter and ads for hiking or swimming gear in summer. 

  The North Face could also use geographic segmentation to determine buyers’ needs based on location. They can use this information to send targeted ads to specific customer segments during peak ski months to maximise profits.

  2. Preferred language (category : geographic segmentation)

  Your marketing approach will likely differ based on where your customers are and the language they speak. So, with that in mind, language may be another crucial variable you can introduce when identifying your target customers. 

  Language-based segmentation becomes even more important when one of your main business objectives is to expand into new markets and target international customers — especially now that global reach is made possible through digital channels. 

  Coca-Cola’s “Share a Coke” is a multi-national campaign with personalised cans and bottles featuring popular names from countries around the globe. It’s just one example of targeting customers based on language.

  3. Repeat users and loyal customers (category : customer lifecycle segmentation)

  Sephora, a large beauty supply company, is well-known for its Beauty Insider loyalty program. 

  It segments customers based on their purchase history and preferences and rewards their loyalty with gifts, discounts, exclusive offers and free samples. And since customers receive personalised product recommendations and other perks, it incentivises them to remain members of the Beauty Insider program — adding a boost to customer loyalty.

  By creating a memorable customer experience for this segment of their customer base, staying on top of beauty trends and listening to feedback, Sephora is able to keep buyers coming back.

  

  4. New customers (category : customer lifecycle segmentation)

  Subscription services use customer lifecycle segmentation to offer special promotions and trials for new customers. 

  HBO Max is a great example of a real company that excels at this strategy : 

  They offer 40% savings on an annual ad-free plan, which targets new customers who may be apprehensive about the added monthly cost of a recurring subscription.

  This marketing strategy prioritises fostering long-term customer relationships with new buyers to avoid high churn rates. 

  5. Cart abandonment (category : purchase history segmentation)

  With a rate of 85% among US-based mobile users, cart abandonment is a huge issue for ecommerce businesses. One way to deal with this is to segment inactive customers and cart abandoners — those who showed interest by adding products to their cart but haven’t converted yet — and send targeted emails to remind them about their abandoned carts.

  E-commerce companies like Ipsy, for example, track users who have added items to their cart but haven’t followed through on the purchase. The company’s messaging often contains incentives — like free shipping or a limited-time discount — to encourage passive users to return to their carts. 

  Research has found that cart abandonment emails with a coupon code have a high 44.37% average open rate. 

  6. Website activity (category : technographic segmentation)

  It’s also possible to segment customers based on website activity. Now, keep in mind that this is a relatively broad approach ; it covers every interaction that may occur while the customer is browsing your website. As such, it leaves room for many different types of segmentation. 

  For instance, you can segment your audience based on the pages they visited, the elements they interacted with — like CTAs and forms — how long they stayed on each page and whether they added products to their cart. 

  Matomo’s Event Tracking can provide additional context to each website visit and tell you more about the specific interactions that occur, making it particularly useful for segmenting customers based on how they spend their time on your website. 

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  Amazon segments its customers based on browsing behaviour — recently viewed products and categories, among other things — which, in turn, allows them to improve the customer’s experience and drive sales.

  7. Traffic source (category : channel segmentation) 

  You can also segment your audience based on traffic sources. For example, you can determine if your website visitors arrived through Google and other search engines, email newsletters, social media platforms or referrals. 

  In other words, you’ll create specific audience segments based on the original source. Matomo’s Acquisition feature can provide insights into five different types of traffic sources — search engines, social media, external websites, direct traffic and campaigns — to help you understand how users enter your website.

  You may find that most visitors arrive at your website through social media ads or predominantly discover your brand through search engines. Either way, by learning where they’re coming from, you’ll be able to determine which conversion paths you should prioritise and optimise further. 

  8. Device type (category : technographic segmentation)

  Device type is customer segmentation based on the devices that potential customers may use to access your website and view your content. 

  It’s worth noting that, on a global level, most people (96%) use mobile devices — primarily smartphones — for internet access. So, there’s a high chance that most of your website visitors are coming from mobile devices, too. 

  However, it’s best not to assume anything. Matomo can detect the operating system and the type of device — desktop, mobile device, tablet, console or TV, for example. 

  By introducing the device type variable into your customer segmentation efforts, you’ll be able to determine if there’s a preference for mobile or desktop devices. In return, you’ll have a better idea of how to optimise your website — and whether you should consider developing an app to meet the needs of mobile users.

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  9. Browser type (category : technographic segmentation)

  Besides devices, another type of segmentation that belongs to the technographic category and can provide valuable insights is browser-related. In this case, you’re tracking the internet browser your customers use. 

  Many browser types are available — including Google Chrome, Microsoft Edge, Safari, Firefox and Brave — and each may display your website and other content differently. 

  So, keeping track of your customers’ preferred choices is important. Otherwise, you won’t be able to fully understand their online experience — or ensure that these browsers are displaying your content properly. 

  

  10. Ecommerce activity (category : purchase history, value based, channel or product based segmentation) 

  Similar to website activity, looking at ecommerce activity can tell your sales teams more about which pages the customer has seen and how they have interacted with them. 

  With Matomo’s Ecommerce Tracking, you’ll be able to keep an eye on customers’ on-site behaviours, conversion rates, cart abandonment, purchased products and transaction data — including total revenue and average order value.

  Considering that the focus is on sales channels — such as your online store — this approach to customer segmentation can help you improve the sales experience and increase profitability. 

  Start implementing these customer segments examples

  With ever-evolving demographics and rapid technological advancements, customer segmentation is increasingly complex. The tips and real-world examples in this article break down and simplify customer segmentation so that you can adapt to your customer base. 

  Customer segmentation lays the groundwork for your personalised marketing campaigns to take off. By understanding your users better, you can effectively tailor each campaign to different segments. 

  If you’re ready to see how Matomo can elevate your personalised marketing campaigns, try it for free for 21 days. No credit card required.

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