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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.

• 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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• A Complete Guide to Metrics in Google Analytics

  11 janvier 2024, par Erin

  There’s no denying that Google Analytics is the most popular web analytics solution today. Many marketers choose it to understand user behaviour. But when it offers so many different types of metrics, it can be overwhelming to choose which ones to focus on. In this article, we’ll dive into how metrics work in Google Analytics 4 and how to decide which metrics may be most useful to you, depending on your analytics needs.

  However, there are alternative web analytics solutions that can provide more accurate data and supplement GA’s existing features. Keep reading to learn how to overcome Google Analytics limitations so you can get the more out of your web analytics.

  What is a metric in Google Analytics ?

  In Google Analytics, a metric is a quantitative measurement or numerical data that provides insights into specific aspects of user behaviour. Metrics represent the counts or sums of user interactions, events or other data points. You can use GA metrics to better understand how people engage with a website or mobile app. 

  Unlike the previous Universal Analytics (the previous version of GA), GA4 is event-centric and has automated and simplified the event tracking process. Compared to Universal Analytics, GA4 is more user-centric and lets you hone in on individual user journeys. Some examples of common key metrics in GA4 are : 

  • Sessions : A group of user interactions on your website that occur within a specific time period. A session concludes when there is no user activity for 30 minutes.
  • Total Users : The cumulative count of individuals who accessed your site within a specified date range.
  • Engagement Rate : The percentage of visits to your website or app that included engagement (e.g., one more pageview, one or more conversion, etc.), determined by dividing engaged sessions by sessions.

  

  Metrics are invaluable when it comes to website and conversion optimisation. Whether you’re on the marketing team, creating content or designing web pages, understanding how your users interact with your digital platforms is essential.

  GA4 metrics vs. dimensions

  GA4 uses metrics to discuss quantitative measurements and dimensions as qualitative descriptors that provide additional context to metrics. To make things crystal clear, here are some examples of how metrics and dimensions are used together : 

  • “Session duration” = metric, “device type” = dimension 
    • In this situation, the dimension can segment the data by device type so you can optimise the user experience for different devices.
  • “Bounce rate” = metric, “traffic source/medium” = dimension 
    • Here, the dimension helps you segment by traffic source to understand how different acquisition channels are performing. 
  • “Conversion rate” = metric, “Landing page” = dimension 
    • When the conversion rate data is segmented by landing page, you can better see the most effective landing pages. 

  You can get into the nitty gritty of granular analysis by combining metrics and dimensions to better understand specific user interactions.

  How do Google Analytics metrics work ?

  Before diving into the most important metrics you should track, let’s review how metrics in GA4 work. 

  

  1. Tracking code implementation

  The process begins with implementing Google Analytics 4 tracking code into the HTML of web pages. This tracking code is JavaScript added to each website page — it collects data related to user interactions, events and other important tidbits.

  2. Data collection

  As users interact with the website or app, the Google Analytics 4 tracking code captures various data points (i.e., page views, clicks, form submissions, custom events, etc.). This raw data is compiled and sent to Google Analytics servers for processing.

  3. Data processing algorithms

  When the data reaches Google Analytics servers, data processing algorithms come into play. These algorithms analyse the incoming raw data to identify the dataset’s trends, relationships and patterns. This part of the process involves cleaning and organising the data.

  4. Segmentation and customisation

  As discussed in the previous section, Google Analytics 4 allows for segmentation and customisation of data with dimensions. To analyse specific data groups, you can define segments based on various dimensions (e.g., traffic source, device type). Custom events and user properties can also be defined to tailor the tracking to the unique needs of your website or app.

  5. Report generation

  Google Analytics 4 can make comprehensive reports and dashboards based on the processed and segmented data. These reports, often in the form of graphs and charts, help identify patterns and trends in the data.

  What are the most important Google Analytics metrics to track ? 

  In this section, we’ll identify and define key metrics for marketing teams to track in Google Analytics 4. 

  

  1. Pageviews are the total number of times a specific page or screen on your website or app is viewed by visitors. Pageviews are calculated each time a web page is loaded or reloaded in a browser. You can use this metric to measure the popularity of certain content on your website and what users are interested in. 
  2. Event tracking monitors user interactions with content on a website or app (i.e., clicks, downloads, video views, etc.). Event tracking provides detailed insights into user engagement so you can better understand how users interact with dynamic content. 
  3. Retention rate can be analysed with a pre-made overview report that Google Analytics 4 provides. This user metric measures the percentage of visitors who return to your website or app after their first visit within a specific time period. Retention rate = (users with subsequent visits / total users in the initial cohort) x 100. Use this information to understand how relevant or effective your content, user experience and marketing efforts are in retaining visitors. You probably have more loyal/returning buyers if you have a high retention rate. 
  4. Average session duration calculates the average time users spend on your website or app per session. Average session duration = total duration of all sessions / # of sessions. A high average session duration indicates how interested and engaged users are with your content. 
  5. Site searches and search queries on your website are automatically tracked by Google Analytics 4. These metrics include search terms, number of searches and user engagement post-search. You can use site search metrics to better understand user intent and refine content based on users’ searches. 
  6. Entrance and exit pages show where users first enter and leave your site. This metric is calculated by the percentage of sessions that start or end on a specific page. Knowing where users are entering and leaving your site can help identify places for content optimisation. 
  7. Device and browser info includes data about which devices and browsers websites or apps visitors use. This is another metric that Google Analytics 4 automatically collects and categorises during user sessions. You can use this data to improve the user experience on relevant devices and browsers. 
  8. Bounce rate is the percentage of single-page sessions where users leave your site or app without interacting further. Bounce rate = (# of single-page sessions / total # of sessions) x 100. Bounce rate is useful for determining how effective your landing pages are — pages with high bounce rates can be tweaked and optimised to enhance user engagement.

  Examples of how Matomo can elevate your web analytics

  Although Google Analytics is a powerful tool for understanding user behaviour, it also has privacy concerns, limitations and a list of issues. Another web analytics solution like Matomo can help fill those gaps so you can get the most out of your analytics.

  

  1. Cross-verify and validate your observations from Google Analytics by comparing data from Matomo’s Heatmaps and Session Recordings for the same pages. This process grants you access to these advanced features that GA4 does not offer.

  

  1. Matomo provides you with greater accuracy thanks to its privacy-friendly design. Unlike GA4, Matomo can be configured to operate without cookies. This means increased accuracy without intrusive cookie consent screens interrupting the user experience. It’s a win for you and for your users. Matomo also doesn’t apply data sampling so you can rest assured that the data you see is 100% accurate.

  3. Unlike GA4, Matomo offers direct access to customer support so you can save time sifting through community forum threads and online documentation. Gain personalised assistance and guidance for your analytics questions, and resolve issues efficiently.

  

  4. Matomo’s Form Analytics and Media Analytics extend your analytics capabilities beyond just pageviews and event tracking.

     Tracking user interactions with forms can tell you which fields users struggle with, common drop-off points, in addition to which parts of the form successfully guide visitors towards submission.

     See first-hand how Concrete CMS 3x their leads using Matomo’s Form Analytics.

     Media Analytics can provide insight into how users interact with image, video, or audio content on your website. You can use this feature to assess the relevance and popularity of specific content by knowing what your audience is engaged by.

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  Final thoughts

  Although Google Analytics is a powerful tool on its own, Matomo can elevate your web analytics by offering advanced features, data accuracy and a privacy-friendly design. Don’t play a guessing game with your data — Matomo provides 100% accurate data so you don’t have to rely on AI or machine learning to fill in the gaps. Matomo can be configured cookieless which also provides you with more accurate data and a better user experience. 

  Lastly, Matomo is fully compliant with some of the world’s strictest privacy regulations like GPDR. You won’t have to sacrifice compliance for accurate, high quality data. 

  Start your 21-day free trial of Matomo — no credit card required.

  Try Matomo for Free

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