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• Web Analytics Reports : 10 Key Types and How to Use Them

  29 janvier 2024, par Erin

  You can’t optimise your website to drive better results if you don’t know how visitors are engaging with your site.

  But how do you correctly analyse data and identify patterns ? With the right platform, you can use a wide range of web analytics reports to dive deep into the data.

  In this article, we’ll discuss what website analytics reports are, different types, why you need them, and how to use reports to find the insights you need.

  What is web analytics ?

  Website analytics is the process of gathering, processing, and analysing data that shows what users are doing when they visit your website. 

  You typically achieve this with web analytics tools by adding a tracking code that shares data with the analytics platform when someone visits the site.

  

  The visitors trigger the tracking code, which collects data on how they act while on your site and then sends that information to the analytics platform. You can then see the data in your analytics solution and create reports based on this data.

  While there are a lot of web analytics solutions available, this article will specifically demonstrate reports using Matomo.

  What are web analytics reports ?

  Web analytics reports are analyses that focus on specific data points within your analytics platform. 

  For example, this channel report in Matomo shows the top referring channels of a website.

  

  Your marketing team can use this report to determine which channels drive the best results. In the example above, organic search drives almost double the visits and actions of social campaigns. 

  If you’re investing the same amount of money, you’d want to move more of your budget from social to search.

  Why you need to get familiar with specific web analytics reports

  The default web analytics dashboard offers an overview of high-level trends in performance. However, it usually does not give you specific insights that can help you optimise your marketing campaigns.

  For example, you can see that your conversions are down month over month. But, at a glance, you do not understand why that is.

  To understand why, you need to go granular and wider — looking into qualifying data that separates different types of visitors from each other.

  Gartner predicts that 70% of organisations will focus on “small and wide” data by 2025 over “big data.” Most companies lack the data volume to simply let big data and algorithms handle the optimising.

  What you can do instead is dive deep into each visitor. Figure out how they engage with your site, and then you can adjust your campaigns and page content accordingly.

  Common types of web analytics reports

  There are dozens of different web analytics reports, but they usually fall into four separate categories :

  

  • Referral sources : These reports show where your visitors come from. They range from channel reports — search, social media — to specific campaigns and ads.
  • Engagement (on-site actions) : These reports dive into what visitors are doing on your site. They break down clicks, scrolling, completed conversion goals, and more.
  • E-commerce performance : These reports show the performance of your e-commerce store. They’ll help you dive into the sales of individual products, trends in cart abandonment and more.
  • Demographics : These reports help you understand more about your visitors — where they’re visiting from, their browser language, device, and more.

  You can even combine insights across all four using audience segmentation and custom reports. (We’ll cover this in more detail later.)

  How to use 10 important website analytics reports

  The first step is to install the website analytics code on your website. (We include more detailed information in our guide on how to track website visitors.)

  Then, you need to wait until you have a few days (or, if you have limited traffic, a few weeks) of data. Without sufficient website visitor data, none of the reports will be meaningful.

  Visitor Overview report

  First, let’s take a look at the Visitor Overview report. It’s a general report that breaks down the visits over a given time period.

  

  What this report shows :

  • Trends in unique visits month over month
  • Basic engagement trends like the average visit length and bounce rate
  • The number of actions taken per page

  In general, this report is more of a high-level indicator you can use to explore certain areas more thoroughly. For example, if most of your traffic comes from organic traffic or social media, you can dive deeper into those channels.

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  Location report

  Next up, we have the most basic type of demographic report — the Location report. It shows where your visitors tend to access your website from.

  

  What this report shows :

  • The country, state or city your visitors access your website from

  This report is most useful for identifying regional trends. You may notice that your site is growing in popularity in a country. You can take advantage of this by creating a regional campaign to double down on a high performing audience.

  Device report

  Next, we have the Device report, which breaks down your visitors’ devices.

  

  What this report shows :

  • Overall device types used by your visitors
  • Specific device models used

  Today, most websites are responsive or use mobile-first design. So, just seeing that many people access your site through smartphones probably isn’t all that surprising.

  But you should ensure your responsive design doesn’t break down on popular devices. The design may not work effectively because many phones have different screen resolutions. 

  Users Flow report

  The Users Flow report dives deeper into visitor engagement — how your visitors act on your site. It shows common landing pages — the first page visitors land on — and how they usually navigate your site from there.

  

  What this report shows :

  • Popular landing pages
  • How your visitors most commonly navigate your site

  You can use this report to determine which intermediary pages are crucial to keeping visitors engaged. For example, you can prioritise optimisation and rewriting for case study pages that don’t get a lot of direct search or campaign traffic.

  Improving this flow can improve conversion rates and the impact of your marketing efforts.

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  Exit Pages report

  The Exit Pages report complements the Users Flow report well. It highlights the most common pages visitors leave your website from.

  

  What this report shows :

  • The most common exit pages on your website
  • The exit rates of these pages

  Pages with high exit rates fall into two categories. The first are pages where it makes sense that visitors leave, like a post-purchase thank-you page. The second are pages where you’d want your visitors to stay and keep flowing down the funnel. When the rates are unusually high on product pages, category pages, or case study pages, you may have found a problem.

  By combining insights from the Users Flow and Exit Pages reports, you can find valuable candidates for optimisation. This is a key aspect of effective conversion rate optimisation.

  Traffic Acquisition Channel report

  The Acquisition Channels report highlights the channels that drive the most visitors to your site.

  

  What this report shows :

  • Top referring traffic sources by channel type
  • The average time on site, bounce rates, and actions taken by the source

  Because of increasingly privacy-sensitive browsers and apps, the best way to reliably track traffic sources is to use campaign tracking URL. Matomo offers an easy-to-use campaign tracking URL builder to simplify this process.

  Search Engines and Keywords report

  The Search Engines and Keywords report shows which keywords are driving the most organic search traffic and from what search engines.

  

  What this report shows :

  • Search engine keywords that drive traffic
  • The different search engines that refer visitors

  One of the best ways to use this report is to identify low-hanging fruit. You want to find keywords driving some traffic where your page isn’t ranked in the top three results. If the keyword has high traffic potential, you should then work to optimise that page to rank higher and get more traffic. This technique is an efficient way to improve your SEO performance.

  Ecommerce Products report

  If you sell products directly on your website, the Ecommerce Products report is a lifesaver. It shows you exactly how all your products are performing.

  

  What this report shows :

  • How your products are selling
  • The average sale price (with coupons) and quantity

  This report could help an online retailer identify top-selling items, adjust pricing based on average sale prices, and strategically allocate resources to promote or restock high-performing products for maximum profitability.

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  Ecommerce Log report

  If you want to explore every single ecommerce interaction, the Ecommerce Log report is for you. It breaks down the actions of visitors who add products to their cart in real time.

  

  What this report shows :

  • The full journey of completed purchases and abandoned carts
  • The exact actions your potential customers take and how long their journeys last

  If you suspect that the user experience of your online store isn’t perfect, this report helps you confirm or deny that suspicion. By closely examining individual interactions, you can identify common exit pages or other issues.

• What is a Cohort Report ? A Beginner’s Guide to Cohort Analysis

  3 janvier 2024, par Erin

  Handling your user data as a single mass of numbers is rarely conducive to figuring out meaningful patterns you can use to improve your marketing campaigns.

  A cohort report (or cohort analysis) can help you quickly break down that larger audience into sequential segments and contrast and compare based on various metrics. As such, it is a great tool for unlocking more granular trends and insights — for example, identifying patterns in engagement and conversions based on the date users first interacted with your site.

  In this guide, we explain the basics of the cohort report and the best way to set one up to get the most out of it.

  What is a cohort report ?

  In a cohort report, you divide a data set into groups based on certain criteria — typically a time-based cohort metric like first purchase date — and then analyse the data across those segments, looking for patterns.

  Date-based cohort analysis is the most common approach, often creating cohorts based on the day a user completed a particular action — signed up, purchased something or visited your website. Depending on the metric you choose to measure (like return visits), the cohort report might look something like this :

  

  Note that this is not a universal benchmark or anything of the sort. The above is a theoretical cohort analysis based on app users who downloaded the app, tracking and comparing the retention rates as the days go by. 

  The benchmarks will be drastically different depending on the metric you’re measuring and the basis for your cohorts. For example, if you’re measuring returning visitor rates among first-time visitors to your website, expect single-digit percentages even on the second day.

  Your industry will also greatly affect what you consider positive in a cohort report. For example, if you’re a subscription SaaS, you’d expect high continued usage rates over the first week. If you sell office supplies to companies, much less so.

  What is an example of a cohort ?

  As we just mentioned, a typical cohort analysis separates users or customers by the date they first interacted with your business — in this case, they downloaded your app. Within that larger analysis, the users who downloaded it on May 3 represent a single cohort.

  

  In this case, we’ve chosen behaviour and time — the app download day — to separate the user base into cohorts. That means every specific day denotes a specific cohort within the analysis.

  Diving deeper into an individual cohort may be a good idea for important holidays or promotional events like Black Friday.

  Of course, cohorts don’t have to be based on specific behaviour within certain periods. You can also create cohorts based on other dimensions :

  • Transactional data — revenue per user
  • Churn data — date of churn
  • Behavioural cohort — based on actions taken on your website, app or e-commerce store, like the number of sessions per user or specific product pages visited
  • Acquisition cohort — which channel referred the user or customer

  For more information on different cohort types, read our in-depth guide on cohort analysis.

  How to create a cohort report (and make sense of it)

  Matomo makes it easy to view and analyse different cohorts (without the privacy and legal implications of using Google Analytics).

  Here are a few different ways to set up a cohort report in Matomo, starting with our built-in cohorts report.

  Cohort reports

  With Matomo, cohort reports are automatically compiled based on the first visit date. The default metric is the percentage of returning visitors.

  

  Changing the settings allows you to create multiple variations of cohort analysis reports.

  Break down cohorts by different metrics

  The percentage of returning visits can be valuable if you’re trying to improve early engagement in a SaaS app onboarding process. But it’s far from your only option.

  You can also compare performance by conversion, revenue, bounce rate, actions per visit, average session duration or other metrics.

  

  Change the time and scope of your cohort analysis

  Splitting up cohorts by single days may be useless if you don’t have a high volume of users or visitors. If the average cohort size is only a few users, you won’t be able to identify reliable patterns. 

  Matomo lets you set any time period to create your cohort analysis report. Instead of the most recent days, you can create cohorts by week, month, year or custom date ranges. 

  

  Cohort sizes will depend on your customer base. Make sure each cohort is large enough to encapsulate all the customers in that cohort and not so small that you have insignificant cohorts of only a few customers. Choose a date range that gives you that without scaling it too far so you can’t identify any seasonal trends.

  Cohort analysis can be a great tool if you’ve recently changed your marketing, product offering or onboarding. Set the data range to weekly and look for any impact in conversions and revenue after the changes.

  Using the “compare to” feature, you can also do month-over-month, quarter-over-quarter or any custom date range comparisons. This approach can help you get a rough overview of your campaign’s long-term progress without doing any in-depth analysis.

  You can also use the same approach to compare different holiday seasons against each other.

  If you want to combine time cohorts with segmentation, you can run cohort reports for different subsets of visitors instead of all visitors. This can lead to actionable insights like adjusting weekend or specific seasonal promotions to improve conversion rates.

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  Easily create custom cohort reports beyond the time dimension

  If you want to split your audience into cohorts by focusing on something other than time, you will need to create a custom report and choose another dimension. In Matomo, you can choose from a wide range of cohort metrics, including referrers, e-commerce signals like viewed product or product category, form submissions and more.

  

  Then, you can create a simple table-based report with all the insights you need by choosing the metrics you want to see. For example, you could choose average visit duration, bounce rate and other usage metrics.

  

  If you want more revenue-focused insights, add metrics like conversions, add-to-cart and other e-commerce events.

  Custom reports make it easy to create cohort reports for almost any dimension. You can use any metric within demographic and behavioural analytics to create a cohort. (You can explore the complete list of our possible segmentation metrics.)

  We cover different types of custom reports (and ideas for specific marketing campaigns) in our guide on custom segmentation.

  Create your first cohort report and gain better insights into your visitors

  Cohort reports can help you identify trends and the impact of short-term marketing efforts like events and promotions.

  With Matomo cohort reports you have the power to create complex custom reports for various cohorts and segments. 

  If you’re looking for a powerful, easy-to-use web analytics solution that gives you 100% accurate data without compromising your users’ privacy, Matomo is a great fit. Get started with a 21-day free trial today. No credit card required. 

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• Clickstream Data : Definition, Use Cases, and More

  15 avril 2024, par Erin

  Gaining a deeper understanding of user behaviour — customers’ different paths, digital footprints, and engagement patterns — is crucial for providing a personalised experience and making informed marketing decisions. 

  In that sense, clickstream data, or a comprehensive record of a user’s online activities, is one of the most valuable sources of actionable insights into users’ behavioural patterns. 

  This article will cover everything marketing teams need to know about clickstream data, from the basic definition and examples to benefits, use cases, and best practices. 

  What is clickstream data ? 

  As a form of web analytics, clickstream data focuses on tracking and analysing a user’s online activity. These digital breadcrumbs offer insights into the websites the user has visited, the pages they viewed, how much time they spent on a page, and where they went next.

  

  Your clickstream pipeline can be viewed as a “roadmap” that can help you recognise consistent patterns in how users navigate your website. 

  With that said, you won’t be able to learn much by analysing clickstream data collected from one user’s session. However, a proper analysis of large clickstream datasets can provide a wealth of information about consumers’ online behaviours and trends — which marketing teams can use to make informed decisions and optimise their digital marketing strategy. 

  Clickstream data collection can serve numerous purposes, but the main goal remains the same — gaining valuable insights into visitors’ behaviours and online activities to deliver a better user experience and improve conversion likelihood. 

  Depending on the specific events you’re tracking, clickstream data can reveal the following : 

  • How visitors reach your website 
  • The terms they type into the search engine
  • The first page they land on
  • The most popular pages and sections of your website
  • The amount of time they spend on a page 
  • Which elements of the page they interact with, and in what sequence
  • The click path they take 
  • When they convert, cancel, or abandon their cart
  • Where the user goes once they leave your website

  As you can tell, once you start collecting this type of data, you’ll learn quite a bit about the user’s online journey and the different ways they engage with your website — all without including any personal details about your visitors.

  Types of clickstream data 

  While all clickstream data keeps a record of the interactions that occur while the user is navigating a website or a mobile application — or any other digital platform — it can be divided into two types : 

  • Aggregated (web traffic) data provides comprehensive insights into the total number of visits and user interactions on a digital platform — such as your website — within a given timeframe 
  • Unaggregated data is broken up into smaller segments, focusing on an individual user’s online behaviour and website interactions 

  One thing to remember is that to gain valuable insights into user behaviour and uncover sequential patterns, you need a powerful tool and access to full clickstream datasets. Matomo’s Event Tracking can provide a comprehensive view of user interactions on your website or mobile app — everything from clicking a button and completing a form to adding (or removing) products from their cart. 

  On that note, based on the specific events you’re tracking when a user visits your website, clickstream data can include : 

  • Web navigation data : referring URL, visited pages, click path, and exit page
  • User interaction data : mouse movements, click rate, scroll depth, and button clicks
  • Conversion data : form submissions, sign-ups, and transactions 
  • Temporal data : page load time, timestamps, and the date and time of day of the user’s last login 
  • Session data : duration, start, and end times and number of pages viewed per session
  • Error data : 404 errors and network or server response issues 

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  Clickstream data benefits and use cases 

  Given the actionable insights that clickstream data collection provides, it can serve a wide range of use cases — from identifying behavioural patterns and trends and examining competitors’ performance to helping marketing teams map out customer journeys and improve ROI.

  

  According to the global Clickstream Analytics Market Report 2024, some key applications of clickstream analytics include click-path optimisation, website and app optimisation, customer analysis, basket analysis, personalisation, and traffic analysis. 

  

  The behavioural patterns and user preferences revealed by clickstream analytics data can have many applications — we’ve outlined the prominent use cases below. 

  Customer journey mapping 

  Clickstream data allows you to analyse the e-commerce customer’s online journey and provides insights into how they navigate your website. With such a comprehensive view of their click path, it becomes easier to understand user behaviour at each stage — from initial awareness to conversion — identify the most effective touchpoints and fine-tune that journey to improve their conversion likelihood. 

  Identifying customer trends 

  Clickstream data analytics can also help you identify trends and behavioural patterns — the most common sequences and similarities in how users reached your website and interacted with it — especially when you can access data from many website visitors. 

  Think about it — there are many ways in which you can use these insights into the sequence of clicks and interactions and recurring patterns to your team’s advantage. 

  Here’s an example : 

  It can reveal that some pieces of content and CTAs are performing well in encouraging visitors to take action — which shows how you should optimise other pages and what you should strive to create in the future, too. 

  Preventing site abandonment 

  Cart abandonment remains a serious issue for online retailers : 

  According to a recent report, the global cart abandonment rate in the fourth quarter of 2023 was at 83%. 

  That means that roughly eight out of ten e-commerce customers will abandon their shopping carts — most commonly due to additional costs, slow website loading times and the requirement to create an account before purchasing. 

  In addition to cart abandonment predictions, clickstream data analytics can reveal the pages where most visitors tend to leave your website. These drop-off points are clear indicators that something’s not working as it should — and once you can pinpoint them, you’ll be able to address the issue and increase conversion likelihood.

  Improving marketing campaign ROI 

  As previously mentioned, clickstream data analysis provides insights into the customer journey. Still, you may not realise that you can also use this data to keep track of your marketing effectiveness. 

  Global digital ad spending continues to grow — and is expected to reach $836 billion by 2026. It’s easy to see why relying on accurate data is crucial when deciding which marketing channels to invest in. 

  You want to ensure you’re allocating your digital marketing and advertising budget to the channels — be it SEO, pay-per-click (PPC) ads, or social media campaigns — that impact driving conversions. 

  When you combine clickstream e-commerce data with conversion rates, you’ll find the latter in Matomo’s goal reports and have a solid, data-driven foundation for making better marketing decisions.

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  Delivering a better user experience (UX) 

  Clickstream data analysis allows you to identify specific “pain points” — areas of the website that are difficult to use and may cause customer frustration. 

  It’s clear how this would be beneficial to your business : 

  Once you’ve identified these pain points, you can make the necessary changes to your website’s layout and address any technical issues that users might face, improving usability and delivering a smoother experience to potential customers. 

  Collecting clickstream data : Tools and legal implications 

  Your team will need a powerful tool capable of handling clickstream analytics to reap the benefits we’ve discussed previously. But at the same time, you need to respect users’ online privacy throughout clickstream data collection.

  

  Generally speaking, there are two ways to collect data about users’ online activity — web analytics tools and server log files.

  Web analytics tools are the more commonly used solution. Specifically designed to collect and analyse website data, these tools rely on JavaScript tags that run in the browser, providing actionable insights about user behaviour. Server log files can be a gold mine of data, too — but that data is raw and unfiltered, making it much more challenging to interpret and analyse. 

  That brings us to one of the major clickstream challenges to keep in mind as you move forward — compliance.

  While Google remains a dominant player in the web analytics market, there’s one area where Matomo has a significant advantage — user privacy. 

  Matomo operates according to privacy laws — including the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), making it an ethical alternative to Google Analytics. 

  It should go without saying, but compliance with data privacy laws — the most talked-about one being the GDPR framework introduced by the EU — isn’t something you can afford to overlook. 

  The GDPR was first implemented in the EU in 2018. Since then, several fines have been issued for non-compliance — including the record fine of €1.2 billion that Meta Platforms, Inc. received in 2023 for transferring personal data of EU-based users to the US.

  Clickstream analytics data best practices 

  

  As valuable as it might be, processing large amounts of clickstream analytics data can be a complex — and, at times, overwhelming — process. 

  Here are some best practices to keep in mind when it comes to clickstream analysis : 

  Define your goals 

  It’s essential to take the time to define your goals and objectives. 

  Once you have a clear idea of what you want to learn from a given clickstream dataset and the outcomes you hope to see, it’ll be easier to narrow down your scope — rather than trying to tackle everything at once — before moving further down the clickstream pipeline. 

  Here are a few examples of goals and objectives you can set for clickstream analysis : 

  • Understanding and predicting users’ behavioural patterns 
  • Optimising marketing campaigns and ROI 
  • Attributing conversions to specific marketing touchpoints and channels

  Analyse your data 

  Collecting clickstream analytics data is only part of the equation ; what you do with raw data and how you analyse it matters. You can have the most comprehensive dataset at your disposal — but it’ll be practically worthless if you don’t have the skill set to analyse and interpret it. 

  In short, this is the stage of your clickstream pipeline where you uncover common sequences and consistent patterns in user behaviour. 

  Clickstream data analytics can extract actionable insights from large datasets using various approaches, models, and techniques. 

  Here are a few examples : 

  • If you’re working with clickstream e-commerce data, you should perform funnel or conversion analyses to track conversion rates as users move through your sales funnel. 
  • If you want to group and analyse users based on shared characteristics, you can use Matomo for cohort analysis. 
  • If your goal is to predict future trends and outcomes — conversion and cart abandonment prediction, for example — based on available data, prioritise predictive analytics.

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  Organise and visualise your data

  As you reach the end of your clickstream pipeline, you need to start thinking about how you will present and communicate your data. And what better way to do that than to transform that data into easy-to-understand visualisations ? 

  Here are a few examples of easily digestible formats that facilitate quick decision-making : 

  • User journey maps, which illustrate the exact sequence of interactions and user flow through your website 
  • Heatmaps, which serve as graphical — and typically colour-coded — representations of a website visitor’s activity 
  • Funnel analysis, which are broader at the top but get increasingly narrower towards the bottom as users flow through and drop off at different stages of the pipeline 

  Collect clickstream data with Matomo 

  Clickstream data is hard to beat when tracking the website visitor’s journey — from first to last interaction — and understanding user behaviour. By providing real-time insights, your clickstream pipeline can help you see the big picture, stay ahead of the curve and make informed decisions about your marketing efforts. 

  Matomo accurate data and compliance with GDPR and other data privacy regulations — it’s an all-in-one, ethical platform that can meet all your web analytics needs. That’s why over 1 million websites use Matomo for their web analytics.

  Try Matomo free for 21 days. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

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  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

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