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Custom Segmentation Guide : How it Works & Segments to Test
Struggling to get the insights you’re looking for with premade reports and audience segments in your analytics?
Custom segmentation can help you better understand your customers, app users or website visitors, but only if you know what you’re doing.
You can derive false insights with the wrong segments, leading your marketing campaigns or product development in the wrong direction.
In this article, we’ll break down what custom segmentation is, useful custom segments to consider, how new privacy laws affect segmentation options and how to create these segments in an analytics platform.
What is custom segmentation?
Custom segmentation is when you divide your audience (customers, users, website visitors) into bespoke segments of your own design, not premade segments designed by the analytics or marketing platform provider.
To do this, you single out “custom segment input” — data points you will use to pinpoint certain users. For example, it could be everyone who has visited a certain page on your site.
Segmentation isn’t just useful for targeting marketing campaigns and also for analysing your customer data. Creating segments is a great way to dive deeper into your data beyond surface-level insights.
You can explore how various factors impact engagement, conversion rates, and customer lifetime value. These insights can help guide your higher-level strategy, not just campaigns.
How custom segments can help your business
As the global business world clamours to become more “data-driven,” even smaller companies collect all sorts of data on visitors, users, and customers.
However, inexperienced organisations often become “data hoarders” without meaningful insights. They have in-house servers full of data or gigabytes stored by Google Analytics and other third-party providers.
One way to leverage this data is with standard customer segmentation models. This can help you get insights into your most valuable customer groups and other standard segments.
Custom segments, in turn, can help you dive deeper. They help you unlock insights into the “why” of certain behaviours. They can help you segment customers and your audience to figure out:
- Why and how someone became a loyal customer
- How high-order-value customers interact with your site before purchases
- Which behaviours indicate audience members are likely to convert
- Which traffic sources drive the most valuable customers
This specific insight’s power led Gartner to predict that 70% of companies will shift focus from “big data” to “small and wide” by 2025. The lateral detail is what helps inform your marketing strategy.
You don’t need the same volume of data if you’re analysing and segmenting it effectively.
Custom segment inputs: 6 data points you can use to create valuable custom segments
To help you get started, here are six useful data points you can use as a basis to create segments — AKA customer segment inputs:
Visits to certain pages
A basic data point that’s great for custom segments is visits to certain pages. Create segments for popular middle-of-funnel pages and compare their engagement and conversion rates.
For example, if a user visits a case study page, you can compare their likelihood to convert vs. other visitors.
This is a type of behavioural segmentation, but it is the easiest custom segment to set up in terms of analysis and marketing efforts.
Visitors who perform certain actions
The other important type of behavioural segment is visitors or users who take certain actions. Think of things like downloading a file, clicking a link, playing a video or scrolling a certain amount.
For instance, you can create a segment of all visitors who have downloaded a white paper. This can help you explore, for example, what drives someone to download a white paper. You can look at the typical user journey and make it easier for them to access the white paper — especially if your sales reps indicate many inbound leads mention it as a key driver of their interest.
User devices
Device-based segmentation lets you compare engagement and conversion rates on mobile, desktop and tablets. You can also get insights into their usage patterns and potential issues with certain mobile elements.
This is one aspect of technographic segmentation, where you segment based on users’ hardware or software. You can also create segments based on browser software or even specific versions.
Loyal or high-value customers
The best way to get more loyal or high-value customers is to explore their journey in more detail. These types of segments can help you better understand your ideal customers and how they act on your site.
You can then use this insight to alter your campaigns or how you communicate with your target audience.
For example, you might notice that high-value customers tend to come from a certain source. You can then focus your marketing efforts on this source to reach more of your ideal customers.
Visitor or customer source
You need to track the results if you’re investing in marketing (like an influencer campaign or a sponsored post) outside platforms with their own analytics.
Before you can create a reliable segment, you need to make sure that you use campaign tracking parameters to reliably track the source. You can use our free campaign tracking URL builder for that.
Demographic segments — location (country, state) and more
Web analytics tools, such as Matomo, use visitors’ IP addresses to pinpoint their location more accurately by cross-referencing with a database of known and estimated IP locations. In addition, these tools can detect a visitor’s location through the language settings in their browser.
This can help create segments based on location or language. By exploring these trends, you can identify patterns in behaviour, tailor your content to specific audiences, and adapt your overall strategy to better meet the preferences and needs of your diverse visitor base.
How new privacy laws affect segmentation options
Over the past few years, new legislation regarding privacy and customer data has been passed globally. The most notable privacy laws are the GDPR in the EU, the CCPA in California and the VCDPA in Virginia.
For most companies, it can save a lot of work and future headaches to choose a GDPR-compliant web analytics solution not only streamlines operations, saving considerable effort and preventing future headaches, but also ensures peace of mind by guaranteeing the collection of compliant and accurate data. This approach allows companies to maintain compliance with privacy regulations while remaining firmly committed to a data-driven strategy.
Create your very own custom segments in Matomo (while ensuring compliance and data accuracy)
Crafting precise marketing messages and optimising ROI is crucial, but it becomes challenging without the right tools, especially when it comes to maintaining accurate data.
That’s where Matomo comes in. Our privacy-friendly web analytics platform is GDPR-compliant and ensures accurate data, empowering you to effortlessly create and analyse precise custom segments.
If you want to improve your marketing campaigns while remaining GDPR-compliant, start your 21-day free trial of Matomo. No credit card required.
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Cohort Analysis 101 : How-To, Examples & Top Tools
13 novembre 2023, par Erin — Analytics TipsImagine that a farmer is trying to figure out why certain hens are laying large brown eggs and others are laying average-sized white eggs.
The farmer decides to group the hens into cohorts based on what kind of eggs they lay to make it easier to detect patterns in their day-to-day lives. After careful observation and analysis, she discovered that the hens laying big brown eggs ate more than the roost’s other hens.
With this cohort analysis, the farmer deduced that a hen’s body weight directly corresponds to egg size. She can now develop a strategy to increase the body weight of her hens to sell more large brown eggs, which are very popular at the weekly farmers’ market.
Cohort analysis has a myriad of applications in the world of web analytics. Like our farmer, you can use it to better understand user behaviour and reap the benefits of your efforts. This article will discuss the best practices for conducting an effective cohort analysis and compare the top cohort analysis tools for 2024.
What is cohort analysis?
By definition, cohort analysis refers to a technique where users are grouped based on shared characteristics or behaviours and then examined over a specified period.
Think of it as a marketing superpower, enabling you to comprehend user behaviours, craft personalised campaigns and allocate resources wisely, ultimately resulting in improved performance and better ROI.
Why does cohort analysis matter?
In web analytics, a cohort is a group of users who share a certain behaviour or characteristic. The goal of cohort analysis is to uncover patterns and compare the performance and behaviour of different cohorts over time.
An example of a cohort is a group of users who made their first purchase during the holidays. By analysing this cohort, you could learn more about their behaviour and buying patterns. You may discover that this cohort is more likely to buy specific product categories as holiday gifts — you can then tailor future holiday marketing campaigns to include these categories.
Types of cohort analysis
There are a few different types of notable cohorts:
- Time-based cohorts are groups of users categorised by a specific time. The example of the farmer we went over at the beginning of this section is a great example of a time-based cohort.
- Acquisition cohorts are users acquired during a specific time frame, event or marketing channel. Analysing these cohorts can help you determine the value of different acquisition methods.
- Behavioural cohorts consist of users who show similar patterns of behaviour. Examples include frequent purchases with your mobile app or digital content engagement.
- Demographic cohorts share common demographic characteristics like age, gender, education level and income.
- Churn cohorts are buyers who have cancelled a subscription/stopped using your service within a specific time frame. Analysing churn cohorts can help you understand why customers leave.
- Geographic cohorts are pretty self-explanatory — you can use them to tailor your marketing efforts to specific regions.
- Customer journey cohorts are based on the buyer lifecycle — from acquisition to adoption to retention.
- Product usage cohorts are buyers who use your product/service specifically (think basic users, power users or occasional users).
Best practices for conducting a cohort analysis
So, you’ve decided you want to understand your user base better but don’t know how to go about it. Perhaps you want to reduce churn and create a more engaging user experience. In this section, we’ll walk you through the dos and don’ts of conducting an effective cohort analysis. Remember that you should tailor your cohort analysis strategy for organisation-specific goals.
1. Preparing for cohort analysis:
- First, define specific goals you want your cohort analysis to achieve. Examples include improving conversion rates or reducing churn.
- Choosing the right time frame will help you compare short-term vs. long-term data trends.
2. Creating effective cohorts:
- Define your segmentation criteria — anything from demographics to location, purchase history or user engagement level. Narrowing in on your specific segments will make your cohort analysis more precise.
- It’s important to find a balance between cohort size and similarity. If your cohort is too small and diverse, you won’t be able to find specific behavioural patterns.
3. Performing cohort analysis:
- Study retention rates across cohorts to identify patterns in user behaviour and engagement over time. Pay special attention to cohorts with high retention or churn rates.
- Analysing cohorts can reveal interesting behavioural insights — how do specific cohorts interact with your website? Do they have certain preferences? Why?
4. Visualising and interpreting data:
- Visualising your findings can be a great way to reveal patterns. Line charts can help you spot trends, while bar charts can help you compare cohorts.
- Guide your analytics team on how to interpret patterns in cohort data. Watch for sudden drops or spikes and what they could mean.
5. Continue improving:
- User behaviour is constantly evolving, so be adaptable. Continuous tracking of user behaviour will help keep your strategies up to date.
- Encourage iterative analysis optimisation based on your findings.
The top cohort analysis tools for 2024
In this section, we’ll go over the best cohort analysis tools for 2024, including their key features, cohort analysis dashboards, cost and pros and cons.
1. Matomo
Matomo is an open-source, GDPR-compliant web analytics solution that offers cohort analysis as a standard feature in Matomo Cloud and is available as a plugin for Matomo On-Premise. Pairing traditional web analytics with cohort analysis will help you gain even deeper insights into understanding user behaviour over time.
You can use the data you get from web analytics to identify patterns in user behaviour and target your marketing strategies to specific cohorts.
Key features
- Matomo offers a cohorts table that lets you compare cohorts side-by-side, and it comes with a time series.
- All core session and conversion metrics are also available in the Cohorts report.
- Create custom segments based on demographics, geography, referral sources, acquisition date, device types or user behaviour.
- Matomo provides retention analysis so you can track how many users from a specific cohort return to your website and when.
- Flexibly analyse your cohorts with custom reports. Customise your reports by combining metrics and dimensions specific to different cohorts.
- Create cohorts based on events or interactions with your website.
- Intuitive, colour-coded data visualisation, so you can easily spot patterns.
Pros
- No setup is needed if you use the JavaScript tracker
- You can fetch cohort without any limit
- 100% accurate data, no AI or Machine Learning data filling, and without the use of data sampling
Cons
- Matomo On-Premise (self-hosted) is free, but advanced features come with additional charges
- Servers and technical know-how are required for Matomo On-Premise. Alternatively, for those not ready for self-hosting, Matomo Cloud presents a more accessible option and starts at $19 per month.
Price:
- Matomo Cloud: 21-day free trial, then starts at $19 per month (includes Cohorts).
- Matomo On-Premise: Free to self-host; Cohorts plugin: 30-day free trial, then $99 per year.
2. Mixpanel
Mixpanel is a product analytics tool designed to help teams better understand user behaviour. It is especially well-suited for analysing user behaviour on iOS and Android apps. It offers various cohort analytics features that can be used to identify patterns and engage your users.
Key features
- Create cohorts based on criteria such as sign-up date, first purchase date, referral source, geographic location, device type or another custom event/property.
- Compare how different cohorts engage with your app with Mixpanel’s comparative analysis features.
- Create interactive dashboards, charts and graphs to visualise data.
- Mixpanel provides retention analysis tools to see how often users return to your product over time.
- Send targeted messages and notifications to specific cohorts to encourage user engagement, announce new features, etc.
- Track and analyse user behaviours within cohorts — understand how different types of users engage with your product.
Pros
- Easily export cohort analysis data for further analysis
- Combined with Mixpanel reports, cohorts can be a powerful tool for improving your product
Cons
- With the free Mixpanel plan, you can’t save cohorts for future use
- Enterprise-level pricing is expensive
- Time-consuming cohort creation process
Price: Free basic version. The growth version starts at £16/month.
3. Amplitude
Amplitude is another product analytics solution that can help businesses track user interactions across digital platforms. Amplitude offers a standard toolkit for in-depth cohort analysis.
Key features
- Create cohorts based on criteria such as sign-up date, first purchase date, referral source, geographic location, device type or another custom event/property.
- Conduct behavioural, time-based and retention analyses.
- Create custom reports with custom data.
- Segment cohorts further based on additional criteria and compare multiple cohorts side-by-side.
Pros
- Highly customisable and flexible
- Quick and simple setup
Cons
- Steep learning curve — requires significant training
- Slow loading speed
- High price point compared to other tools
Price: Free basic version. Plus version starts at £40/month (billed annually).
4. Kissmetrics
Kissmetrics is a customer engagement automation platform that offers powerful analytics features. Kissmetrics provides behavioural analytics, segmentation and email campaign automation.
Key features
- Create cohorts based on demographics, user behaviour, referral sources, events and specific time frames.
- The user path tool provides path visualisation so you can identify common paths users take and spot abandonment points.
- Create and optimise conversion funnels.
- Customise events, user properties, funnels, segments, cohorts and more.
Pros
- Powerful data visualisation options
- Highly customisable
Cons
- Difficult to install
- Not well-suited for small businesses
- Limited integration with other tools
Price: Starting at £21/month for 10k events (billed monthly).
Improve your cohort analysis with Matomo
When choosing a cohort analysis tool, consider factors such as the tool’s ease of integration with your existing systems, data accuracy, the flexibility it offers in defining cohorts, the comprehensiveness of reporting features, and its scalability to accommodate the growth of your data and analysis needs over time. Moreover, it’s essential to confirm GDPR compliance to uphold rigorous privacy standards.
If you’re ready to understand your user’s behaviour, take Matomo for a test drive. Paired with web analytics, this powerful combination can advance your marketing efforts. Start your 21-day free trial today — no credit card required.
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Top 4 CRO Tools to Boost Your Conversion Rates in 2024
31 octobre 2023, par ErinAre you tired of watching potential customers leave your website without converting? You’ve spent countless hours creating an engaging website, but those high bounce rates keep haunting you.
The good news? The solution lies in the transformative power of Conversion Rate Optimisation (CRO) tools. In this guide, we’ll dive deep into the world of CRO tools. We will equip you with strategies to turn those bounces into conversions.
Why are conversion rate optimisation tools so crucial?
CRO tools can be assets in digital marketing, playing a pivotal role in enhancing online businesses’ performance. CRO tools empower businesses to improve website conversion rates by analysing user behaviour. You can then leverage this user data to optimise web elements.
Improving website conversion rates is paramount because it increases revenue and customer satisfaction. A study by VentureBeat revealed an average return on investment (ROI) of 223% thanks to CRO tools.
173 marketers out of the surveyed group reported returns exceeding 1,000%. Both of these data points highlight the impact CRO tools can have.
Coupled with CRO tools, certain testing tools and web analytics tools play a crucial role. They offer insight into user behaviour patterns, enabling businesses to choose effective strategies. By understanding what resonates with users, these tools help inform data-driven decisions. This allows businesses to refine online strategies and enhance the customer experience.
CRO tools enhance user experiences and ensure business sustainability. Integrating these tools is crucial for staying ahead. CRO and web analytics work together to optimise digital presence.
Real-world examples of CRO tools in action
In this section, we’ll explore real case studies showcasing CRO tools in action. See how businesses enhance conversion rates, user experiences, and online performance. These studies reveal the practical impact of data-driven decisions and user-focused strategies.
Case study: How Matomo’s Form Analytics helped Concrete CMS 3x leads
Concrete CMS, is a content management system provider that helps users build and manage websites. They used Matomo’s Form Analytics to uncover that users were getting stuck at the address input stage of the onboarding process. Using these insights to make adjustments to their onboarding form, Concrete CMS was able to achieve 3 times the amount of leads in just a few days.
Read the full Concrete CMS case study.
Best analytics tools for enhancing conversion rate optimisation in 2023
Jump to the comparison table to see an overview of each tool.
1. Matomo
Matomo stands out as an all-encompassing tool that seamlessly combines traditional web analytics features (like pageviews and bounce rates) with advanced behavioural analytics capabilities, providing a full spectrum of insights for effective CRO.
Key features
- Heatmaps and Session Recordings:
These features empower businesses to see their websites through the eyes of their visitors. By visually mapping user engagement and observing individual sessions, businesses can make informed decisions, enhance user experience and ultimately increase conversions. These tools are invaluable assets for businesses aiming to create user-friendly websites.
- Form Analytics:
Matomo’s Form Analytics offers comprehensive tracking of user interactions within forms. This includes covering input fields, dropdowns, buttons and submissions. Businesses can create custom conversion funnels and pinpoint form abandonment reasons.
- Users Flow:
Matomo’s Users Flow feature tracks visitor paths, drop-offs and successful routes, helping businesses optimise their websites. This insight informs decisions, enhances user experience, and boosts conversion rates.
- Surveys plugin:
The Matomo Surveys plugin allows businesses to gather direct feedback from users. This feature enhances understanding by capturing user opinions, adding another layer to the analytical depth Matomo offers.
- A/B testing:
The platform allows you to conduct A/B tests to compare different versions of web pages. This helps determine which performs better in conversions. By conducting experiments and analysing the results within Matomo, businesses can iteratively refine their content and design elements.
- Funnels:
Matomo’s Funnels feature empower businesses to visualise, analyse and optimise their conversion paths. By identifying drop-off points, tailoring user experiences and conducting A/B tests within the funnel, businesses can make data-driven decisions that significantly boost conversions and enhance the overall user journey on their websites.
Pros
- Starting at $19 per month, Matomo is an affordable CRO solution.
- Matomo guarantees accurate data, eliminating the need to fill gaps with artificial intelligence (AI) or machine learning.
- Matomo’s open-source framework ensures enhanced security, privacy, customisation, community support and long-term reliability.
Cons
- The On-Premise (self-hosted) version is free, with additional charges for advanced features.
- Managing Matomo On-Premise requires servers and technical know-how.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
2. Google Analytics
Google Analytics provides businesses and website owners valuable insights into their online audience. It tracks website traffic, user interactions and analyses conversion data to enhance the user experience.
While Google Analytics may not provide the extensive CRO-specific features found in other tools on this list, it can still serve as a valuable resource for basic analysis and optimisation of conversion rates.
Key features
- Comprehensive Data Tracking:
Google Analytics meticulously tracks website traffic, user behaviour and conversion rates. These insights form the foundation for CRO efforts. Businesses can identify patterns, user bottlenecks and high-performing areas.
- Real-Time Reporting:
Access to real-time data is invaluable for CRO efforts. Monitor current website activity, user interactions, and campaign performance as they unfold. This immediate feedback empowers businesses to make instant adjustments, optimising web elements and content for maximum conversions.
- User flow analysis
Visualise and understand how visitors navigate through your website. It provides insights into the paths users take as they move from one page to another, helping you identify the most common routes and potential drop-off points in the user journey.
- Event-based tracking:
GA4’s event-based reporting offers greater flexibility and accuracy in data collection. By tracking various interactions, including video views and checkout processes, businesses can gather more precise insights into user behaviour.
- Funnels:
GA4 offers multistep funnels, path analysis, custom metrics that integrate with audience segments. These user behaviour insights help businesses to tailor their websites, marketing campaigns and user experiences.
Pros
- Flexible audience management across products, regions or brands allow businesses to analyse data from multiple source properties.
- Google Analytics integrates with other Google services and third-party platforms. This enables a comprehensive view of online activities.
- Free to use, although enterprises may need to switch to the paid version to accommodate higher data volumes.
Cons
- Google Analytics raises privacy concerns, primarily due to its tracking capabilities and the extensive data it collects.
- Limitations imposed by thresholding can significantly hinder efforts to enhance user experience and boost conversions effectively.
- Property and sampling limits exist. This creates problems when you’re dealing with extensive datasets or high-traffic websites.
- The interface is difficult to navigate and configure, resulting in a steep learning curve.
3. Contentsquare
Contentsquare is a web analytics and CRO platform. It stands out for its in-depth behavioural analytics. Contentsquare offers detailed data on how users interact with websites and mobile applications.
Key features
- Heatmaps and Session Replays:
Users can visualise website interactions through heatmaps, highlighting popular areas and drop-offs. Session replay features enable the playback of user sessions. These provide in-depth insights into individual user experiences.
- Conversion Funnel Analysis:
Contentsquare tracks users through conversion funnels, identifying where users drop off during conversion. This helps in optimising the user journey and increasing conversion rates.
- Segmentation and Personalisation:
Businesses can segment their audience based on various criteria. Segments help create personalised experiences, tailoring content and offers to specific user groups.
- Integration Capabilities:
Contentsquare integrates with various third-party tools and platforms, enhancing its functionality and allowing businesses to leverage their existing tech stack.
Pros
- Comprehensive support and resources.
- User-friendly interface.
- Personalisation capabilities.
Cons
- High price point.
- Steep learning curve.
4. Hotjar
Hotjar is a robust tool designed to unravel user behaviour intricacies. With its array of features including visual heatmaps, session recordings and surveys, it goes beyond just identifying popular areas and drop-offs.
Hotjar provides direct feedback and offers an intuitive interface, enabling seamless experience optimisation.
Key features
- Heatmaps:
Hotjar provides visual heatmaps that display user interactions on your website. Heatmaps show where users click, scroll, and how far they read. This feature helps identify popular areas and points of abandonment.
- Session Recordings:
Hotjar allows you to record user sessions and watch real interactions on your site. This insight is invaluable for understanding user behaviour and identifying usability issues.
- Surveys and Feedback:
Hotjar offers on-site surveys and feedback forms that can get triggered based on user behaviour. These tools help collect qualitative data from real users, providing valuable insights.
- Recruitment Tool:
Hotjar’s recruitment tool lets you recruit participants from your website for user testing. This feature streamlines the process of finding participants for usability studies.
- Funnel and Form Analysis:
Hotjar enables the tracking of user journeys through funnels. It provides insights into where users drop off during the conversion process. It also offers form analysis to optimise form completion rates.
- User Polls:
You can create customisable polls to engage with visitors. Gather specific feedback on your website, products, or services.
Pros
- Starting at $32 per month, Hotjar is a cost-effective solution for most businesses.
- Hotjar provides a user-friendly interface that is easy for the majority of users to pick up quickly.
Cons
- Does not provide traditional web analytics and requires combining with another tool, potentially creating a less streamlined and cohesive user experience, which can complicate conversion rate optimization efforts.
- Hotjar’s limited integrations can hinder its ability to seamlessly work with other essential tools and platforms, potentially further complicating CRO.
Comparison Table
Please note: We aim to keep this table accurate and up to date. However, if you see any inaccuracies or outdated information, please email us at marketing@matomo.org
To make comparing these tools even easier, we’ve put together a table for you to compare features and price points:
Conclusion
CRO tools and web analytics are essential for online success. Businesses thrive by investing wisely, understanding user behaviour and using targeted strategies. The key: generate traffic and convert it into leads and customers. The right tools and strategies lead to remarkable conversions and online success. Each click, each interaction, becomes an opportunity to create an engaging user journey. This careful orchestration of data and insight separates thriving businesses from the rest.
Are you ready to embark on a journey toward improved conversions and enhanced user experiences? Matomo offers analytics solutions meticulously designed to complement your CRO strategy. Take the next step in your CRO journey. Start your 21-day free trial today—no credit card required.
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21 day free trial. No credit card required.
- Heatmaps and Session Recordings:
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A Comprehensive Guide to Robust Digital Marketing Analytics
30 octobre 2023, par ErinFirst impressions are everything. This is not only true for dating and job interviews but also for your digital marketing strategy. Like a poorly planned resume getting tossed in the “no thank you” pile, 38% of visitors to your website will stop engaging with your content if they find the layout unpleasant. Thankfully, digital marketers can access data that can be harnessed to optimise websites and turn those “no thank you’s” into “absolutely’s.”
So, how can we transform raw data into valuable insights that pay off? The key is web analytics tools that can help you make sense of it all while collecting data ethically. In this article, we’ll equip you with ways to take your digital marketing strategy to the next level with the power of web analytics.
What are the different types of digital marketing analytics?
Digital marketing analytics are like a cipher into the complex behaviour of your buyers. Digital marketing analytics help collect, analyse and interpret data from any touchpoint you interact with your buyers online. Whether you’re trying to gauge the effectiveness of a new email marketing campaign or improve your mobile app layout, there’s a way for you to make use of the insights you gain.
As we go through the eight commonly known types of digital marketing analytics, please note we’ll primarily focus on what falls under the umbrella of web analytics.
- Web analytics help you better understand how users interact with your website. Good web analytics tools will help you understand user behaviour while securely handling user data.
- Learn more about the effectiveness of your organisation’s social media platforms with social media analytics. Social media analytics include user engagement, post reach and audience demographics.
- Email marketing analytics help you see how email campaigns are being engaged with.
- Search engine optimisation (SEO) analytics help you understand your website’s visibility in search engine results pages (SERPs).
- Pay-per-click (PPC) analytics measure the performance of paid advertising campaigns.
- Content marketing analytics focus on how your content is performing with your audience.
- Customer analytics helps organisations identify and examine buyer behaviour to retain the biggest spenders.
- Mobile app analytics track user interactions within mobile applications.
Choosing which digital marketing analytics tools are the best fit for your organisation is not an easy task. When making these decisions, it’s critical to remember the ethical implications of data collection. Although data insights can be invaluable to your organisation, they won’t be of much use if you lose the trust of your users.
Tips and best practices for developing robust digital marketing analytics
So, what separates top-notch, robust digital marketing analytics from the rest? We’ve already touched on it, but a big part involves respecting user privacy and ethically handling data. Data security should be on your list of priorities, alongside conversion rate optimisation when developing a digital marketing strategy. In this section, we will examine best practices for using digital marketing analytics while retaining user trust.
Clear objectives
Before comparing digital marketing analytics tools, you should define clear and measurable goals. Try asking yourself what you need your digital marketing analytics strategy to accomplish. Do you want to improve conversion rates while remaining data compliant? Maybe you’ve noticed users are not engaging with your platform and want to fix that. Save yourself time and energy by focusing on the most relevant pain points and areas of improvement.
Choose the right tools for the job
Don’t just base your decision on what other people tell you. Take the tool for a test drive — free trials allow you to test features and user interfaces and learn more about the platform before committing. When choosing digital marketing analytics tools, look for ones that ensure compliance with privacy laws like GDPR.
Don’t overlook data compliance
GDPR ensures organisations prioritise data protection and privacy. You could be fined up to €20 million, or 4% of the previous year’s revenue for violations. Without data compliance practices, you can say goodbye to the time and money spent on digital marketing strategies.
Don’t sacrifice data quality and accuracy
Inaccurate and low-quality data can taint your analysis, making it hard to glean valuable insights from your digital marketing analytics efforts. Regularly audit and clean your data to remove inaccuracies and inconsistencies. Address data discrepancies promptly to maintain the integrity of your analytics. Data validation measures also help to filter out inaccurate data.
Communicate your findings
Having insights is one thing; effectively communicating complex data findings is just as important. Customise dashboards to display key metrics aligned with your objectives. Make sure to automate reports, allowing stakeholders to stay updated without manual intervention.
Understand the user journey
To optimise your conversion rates, you need to understand the user journey. Start by analysing visitors interactions with your website — this will help you identify conversion bottlenecks in your sales or lead generation processes. Implement A/B testing for landing page optimisation, refining elements like call-to-action buttons or copy, and leverage Form Analytics to make informed, data-driven improvements to your forms.
Continuous improvement
Learn from the data insights you gain, and iterate your marketing strategies based on the findings. Stay updated with evolving web analytics trends and technologies to leverage new growth opportunities.
Why you need web analytics to support your digital marketing analytics toolbox
You wouldn’t set out on a roadtrip without a map, right? Digital marketing analytics without insights into how users interact with your website are just as useless. Used ethically, web analytics tools can be an invaluable addition to your digital marketing analytics toolbox.
The data collected via web analytics reveals user interactions with your website. These could include anything from how long visitors stay on your page to their actions while browsing your website. Web analytics tools help you gather and understand this data so you can better understand buyer preferences. It’s like a domino effect: the more you understand your buyers and user behaviour, the better you can assess the effectiveness of your digital content and campaigns.
Web analytics reveal user behaviour, highlighting navigation patterns and drop-off points. Understanding these patterns helps you refine website layout and content, improving engagement and conversions for a seamless user experience.
Concrete CMS harnessed the power of web analytics, specifically Form Analytics, to uncover a crucial insight within their user onboarding process. Their data revealed a significant issue: the “address” input field was causing visitors to drop off and not complete the form, severely impacting the overall onboarding experience and conversion rate.
Armed with these insights, Concrete CMS made targeted optimisations to the form, resulting in a substantial transformation. By addressing the specific issue identified through Form Analytics, they achieved an impressive outcome – a threefold increase in lead generation.
This case is a great example of how web analytics can uncover customer needs and preferences and positively impact conversion rates.
Ethical implications of digital marketing analytics
As we’ve touched on, digital marketing analytics are a powerful tool to help better understand online user behaviour. With great power comes great responsibility, however, and it’s a legal and ethical obligation for organisations to protect individual privacy rights. Let’s get into the benefits of practising ethical digital marketing analytics and the potential risks of not respecting user privacy:
- If someone uses your digital platform and then opens their email one day to find it filled with random targeted ad campaigns, they won’t be happy. Avoid losing user trust — and facing a potential lawsuit — by informing users what their data will be used for. Give them the option to consent to opt-in or opt-out of letting you use their personal information. If users are also assured you’ll safeguard personal information against unauthorised access, they’ll be more likely to trust you to handle their data securely.
- Protecting data against breaches means investing in technology that will let you end-to-end encrypt and securely store data. Other important data-security best practices include access control, backing up data regularly and network and physical security of assets.
- A fine line separates digital marketing analytics and misusing user data — many companies have gotten into big trouble for crossing it. (By big trouble, we mean millions of dollars in fines.) When it comes to digital marketing analytics, you should never cut corners when it comes to user privacy and data security. This balance involves understanding what data can be collected and what should be collected and respecting user boundaries and preferences.
Learn more
We discussed a lot of facets of digital marketing analytics, namely how to develop a robust digital marketing strategy while prioritising data compliance. With Matomo, you can protect user data and respect user privacy while gaining invaluable insights into user behaviour. Save your organisation time and money by investing in a web analytics solution that gives you the best of both worlds.
If you’re ready to begin using ethical and robust digital marketing analytics on your website, try Matomo. Start your 21-day free trial now — no credit card required.
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Segmentation Analytics : How to Leverage It on Your Site
27 octobre 2023, par Erin — Analytics TipsThe deeper you go with your customer analytics, the better your insights will be.
The result? Your marketing performance soars to new heights.
Customer segmentation is one of the best ways businesses can align their marketing strategies with an effective output to generate better results. Marketers know that targeting the right people is one of the most important aspects of connecting with and converting web visitors into customers.
By diving into customer segmentation analytics, you’ll be able to transform your loosely defined and abstract audience into tangible, understandable segments, so you can serve them better.
In this guide, we’ll break down customer segmentation analytics, the different types, and how you can delve into these analytics on your website to grow your business.What is customer segmentation?
Before we dive into customer segmentation analytics, let’s take a step back and look at customer segmentation in general.
Customer segmentation is the process of dividing your customers up into different groups based on specific characteristics.
These groups could be based on demographics like age or location or behaviours like recent purchases or website visits.
By splitting your audience into different segments, your marketing team will be able to craft highly targeted and relevant marketing campaigns that are more likely to convert.
Additionally, customer segmentation allows businesses to gain new insights into their audience. For example, by diving deep into different segments, marketers can uncover pain points and desires, leading to increased conversion rates and return on investment.
But, to grasp the different customer segments, organisations need to know how to collect, digest and interpret the data for usable insights to improve their business. That’s where segmentation analytics comes in.
What is customer segmentation analytics?
Customer segmentation analytics splits customers into different groups within your analytics software to create more detailed customer data and improve targeting.
With customer segmentation, you’re splitting your customers into different groups. With customer segmentation analytics, you’re doing this all within your analytics platform so you can understand them better.
One example of splitting your customers up is by country. For example, let’s say you have a global customer base. So, you go into your analytics software and find that 90% of your website visitors come from five countries: the UK, the US, Australia, Germany and Japan.
In this area, you could then create customer segmentation subsets based on these five countries. Moving forward, you could then hop into your analytics tool at any point in time and analyse the segments by country.
For example, if you wanted to see how well your recent marketing campaign impacted your Japanese customers, you could look at your Japanese subset within your analytics and dive into the data.
The primary goal of customer segmentation analytics is to gather actionable data points to give you an in-depth understanding of your customers. By gathering data on your different audience segments, you’ll discover insights on your customers that you can use to optimise your website, marketing campaigns, mobile apps, product offerings and overall customer experience.
Rather than lumping your entire customer base into a single mass, customer segmentation analytics allows you to meet even more specific and relevant needs and pain points of your customers to serve them better.
By allowing you to “zoom in” on your audience, segmentation analytics helps you offer more value to your customers, giving you a competitive advantage in the marketplace.
5 types of segmentation
There are dozens of different ways to split up your customers into segments. The one you choose depends on your goals and marketing efforts. Each type of segmentation offers a different view of your customers so you can better understand their specific needs to reach them more effectively.
While you can segment your customers in almost endless ways, five common types the majority fall under are:
Geographic
Another way to segment is by geography.
This is important because you could have drastically different interests, pain points and desires based on where you live.
If you’re running a global e-commerce website that sells a variety of clothing products, geographic segmentation can play a crucial role in optimising your website.
For instance, you may observe that a significant portion of your website visitors are from countries in the Southern Hemisphere, where it’s currently summer. On the other hand, visitors from the Northern Hemisphere are experiencing winter. Utilising this information, you can tailor your marketing strategy and website accordingly to increase sells.
Where someone comes from can significantly impact how they will respond to your messaging, brand and offer.
Geographic segmentation typically includes the following subtypes:
- Cities (i.e., Austin, Paris, Berlin, etc.)
- State (i.e., Massachusetts)
- Country (i.e., Thailand)
Psychographic
Another key segmentation type of psychographic. This is where you split your customers into different groups based on their lifestyles.
Psychographic segmentation is a method of dividing your customers based on their habits, attitudes, values and opinions. You can unlock key emotional elements that impact your customers’ purchasing behaviours through this segmentation type.
Psychographic segmentation typically includes the following subtypes:
- Values
- Habits
- Opinions
Behavioural
While psychographic segmentation looks at your customers’ overall lifestyle and habits, behavioural segmentation aims to dive into the specific individual actions they take daily, especially when interacting with your brand or your website.
Your customers won’t all interact with your brand the same way. They’ll act differently when interacting with your products and services for several reasons.
Behavioural segmentation can help reveal certain use cases, like why customers buy a certain product, how often they buy it, where they buy it and how they use it.
By unpacking these key details about your audience’s behaviour, you can optimise your campaigns and messaging to get the most out of your marketing efforts to reach new and existing customers.
Behavioural segmentation typically includes the following subtypes:
- Interactions
- Interests
- Desires
Technographic
Another common segmentation type is technographic segmentation. As the name suggests, this technologically driven segment seeks to understand how your customers use technology.
While this is one of the newest segmentation types marketers use, it’s a powerful method to help you understand the types of tech your customers use, how often they use it and the specific ways they use it.
Technographic segmentation typically includes the following subtypes:
- Smartphone type
- Device type: smartphone, desktop, tablet
- Apps
- Video games
Demographic
The most common approach to segmentation is to split your customers up by demographics.
Demographic segmentation typically includes subtypes like language, job title, age or education.
This can be helpful for tailoring your content, products, and marketing efforts to specific audience segments. One way to capture this information is by using web analytics tools, where language is often available as a data point.
However, for accurate insights into other demographic segments like job titles, which may not be available (or accurate) in analytics tools, you may need to implement surveys or add fields to forms on your website to gather this specific information directly from your visitors.
How to build website segmentation analytics
With Matomo, you can create a variety of segments to divide your website visitors into different groups. Matomo’s Segments allows you to view segmentation analytics on subsets of your audience, like:
- The device they used while visiting your site
- What channel they entered your site from
- What country they are located
- Whether or not they visited a key page of your website
- And more
While it’s important to collect general data on every visitor you have to your website, a key to website growth is understanding each type of visitor you have.
For example, here’s a screenshot of how you can segment all of your website’s visitors from New Zealand:
The criteria you use to define these segments are based on the data collected within your web analytics platform.
Here are some popular ways you can create some common themes on Matomo that can be used to create segments:
Visit based segments
Create segments in Matomo based on visitors’ patterns.
For example:
- Do returning visitors show different traits than first-time visitors?
- Do people who arrive on your blog experience your website differently than those arriving on a landing page?
This information can inform your content strategy, user interface design and marketing efforts.
Demographic segments
Create segments in Matomo based on people’s demographics.
For example:
- User’s browser language
- Location
This can enable you to tailor your approach to specific demographics, improving the performance of your marketing campaigns.
Technographic segments
Create segments in Matomo based on people’s technographics.
For example:
- Web browser being used (i.e., Chrome, Safari, Firefox, etc.)
- Device type (i.e., smartphone, tablet, desktop)
This can inform how to optimise your website based on users’ technology preferences, enhancing the effectiveness of your website.
Interaction based segments
Create segments in Matomo based on interactions.
For example:
- Events (i.e., when someone clicks a specific URL on your website)
- Goals (i.e., when someone stays on your site for a certain period)
Insights from this can empower you to fine-tune your content and user experience for increasing conversion rates.
Visitor profile view in Matomo with behavioural, location and technographic insights Campaign-based segments
Create segments in Matomo based on campaigns.
For example:
- Visitors arriving from specific traffic sources
- Visitors arriving from specific advertising campaigns
With these insights, you can assess the performance of your marketing efforts, optimise your ad spend and make data-driven decisions to enhance your campaigns for better results.
Ecommerce segments
Create segments in Matomo based on ecommerce.
For example:
- Visitors who purchased vs. those who didn’t
- Visitors who purchased a specific product
This allows you to refine your website and marketing strategy for increased conversions and revenue.
Leverage Matomo for your segmentation analytics
By now, you can see the power of segmentation analytics and how they can be used to understand your customers and website visitors better. By breaking down your audience into groups, you’ll be able to gain insights into those segments to know how to serve them better with improved messaging and relevant products.
If you’re ready to begin using segmentation analytics on your website, try Matomo. Start your 21-day free trial now — no credit card required.
Matomo is an ideal choice for marketers looking for an easy-to-use, out-of-the-box web analytics solution that delivers accurate insights while keeping privacy and compliance at the forefront.
