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• 16 Website Metrics to Track If You Want to Grow Your Business

  9 avril 2024, par Erin

  Conversion rate.

  Bounce rate.

  Sessions.

  There are dozens of metrics to keep up with in web analytics. It can be confusing at times trying to keep up with everything.

  But, if you want to improve your website performance and grow your business, you need to know what they are and how they work.

  Why ?

  Because what you measure gets managed. This is true in your personal life and business. You must track various website metrics to help your business reach new heights.

  In this guide, you’ll learn about the most important website metrics, why they’re important and how to track them to grow your brand.

  What are website metrics ?

  Your website is your digital headquarters.

  It’s not a static place. Instead, it’s a vibrant, interactive hub your visitors and customers can engage with daily.

  Every time a user interacts with your website, you can track what’s happening.

  Website metrics help you measure how much your visitors and customers interact with your website. 

  These engagement metrics help you understand what your visitors are doing, where they’re coming from, how they’re moving on your website and how long they stay. They can even give you insights into what their goals are.

  

  If you aren’t tracking your website metrics, you won’t know how effective your website is.

  By paying close attention to your key metrics within a web analytics platform like Matomo, you’ll be able to see how well your marketing is doing and how your visitors are engaging so you can improve the user experience and increase conversions.

  16 website metrics to track

  Here are the top 16 website metrics you need to be tracking if you want to grow your business :

  1. Pageviews

  A pageview is the number of times a web page has been viewed. 

  Many pageviews can indicate a successful search engine optimisation (SEO) or marketing campaign — it can be used to show positive results for these initiatives.

  It can also help you determine various issues on individual pages. For instance, performance issues or poor website structure can cause visitors to get lost or confused while navigating your website.

  

  2. Average time on page

  Average time on a page is simply the time visitors spend on a specific page (not the entire website) ; tracking users’ time on various pages throughout your website can give you insights that can help you improve certain pages.

  If you get tons of traffic to a particular page, but the average time a visitor stays on that page is minimal, the content may need some work.

  Tracking this data can help determine if your website is engaging for your visitors or if you need to modify certain aspects to increase your visitors’ stay. Increasing the average time on the page will help boost your conversions and search engine rankings.

  3. Actions per visit

  Actions per visit is a key metric that tracks the average number of actions a visitor takes every time they visit your website. This data can help you track your audience engagement and the effectiveness of your content across your entire website.

  An action is any activity performed by your visitors on your website like :

  • Outlinks
  • Downloads
  • Page views
  • Internal site searches

  The higher your actions per visit, the more engaging your audience finds your website content. A side effect of increased actions is staying longer on the site and more likely to convert to your email list as a subscriber or pay for products as a customer.

  4. Bounce rate

  Like a bouncy ball, your website’s bounce rate measures how many users entered your site and “bounced” out without clicking on another page. This metric can be extremely helpful in determining user interest in your content. 

  You might be getting many visitors to your website, but if they “bounce” after visiting the first page they land on, that’s a great indicator that your content is not resonating with your audience.

  Remember, this metric should be taken with a grain of salt. 

  Your bounce rate may indicate that visitors are finding the exact information that they wanted and leaving pleased, so it’s not a black-and-white metric.

  For example, if you have a landing page with a high bounce rate, then that’s likely not a sign of a good user experience. But, if you have a knowledge base article and they just need to find some quick information, then it could be a good indicator.

  5. Conversions

  The first step in tracking conversions is defining what a conversion is for your website. 

  Do you want your audience to :

  • View a blog post
  • Purchase a product
  • Download an eBook
  • Sign up for a consultation call

  Determine what that conversion is and track how often users take that action on your website.

  This helps you understand if your marketing and content strategies are working toward your pre-defined conversion goal.

  

  6. Conversion rate

  A conversion rate is the percentage of visits that triggered a conversion. Knowing this metric lets you plan, budget, and forecast future growth.

  For example, 5% of your website visitors take action and convert to customers. With this information, you can make better informed financial decisions regarding your marketing efforts on your website to help increase traffic and future conversions.

  While there are basic conversion rate benchmarks to strive toward, it ultimately depends on your goals and the specific conversions you decide to track that are best for your business. 

  That being said, Matomo has some best practices to help you optimise your conversion rates, no matter what conversion metric you are tracking.

  7. Exit rate

  While “bounce rate” and “exit rate” are similar, “exit rate” is the percentage of visits to a website that ended on a particular page.

  Knowing which pages have the highest percentage of visitors exiting your website gives you key information on the pages that may need to be improved.

  If you see that your “exit rate” is highest on pages before the checkout (or other CTA’s you have established), you will want to dive into what’s causing visitors to leave from that page. For example, maybe it’s the content, the copy or even a broken link.

  This is a great metric to help determine where you have breakdowns between you and your visitors. Improving your exit rate can help guide visitors through your website funnel more easily and boost your conversion rates. 

  

  8. Top pages

  The top pages on your website are the pages that receive the most visits. Understanding what your top pages are can be crucial in planning and guiding your marketing strategies moving forward.

  Your top pages can help you determine the most engaging content for your audience. This can be extremely helpful in guiding your visitors to certain pages that other users find more valuable.

  It also helps you determine if you need to focus more attention on different parts of your website to increase user engagement in those areas.

  For example, maybe your most-viewed pages have less copy and more photos or videos. Understanding this lets you know that incorporating more media into other pages will boost future engagement.

  9. Traffic sources

  Your traffic sources are the channels that are driving visitors to your website. The four most common traffic sources are :

  • Direct Entry : Typing your website URL into their browser or visiting via a bookmark they saved
  • Websites/Referral : Clicking on a link to your site from another website
  • Search Engines : Using search engines (Google, Bing or Yahoo) to find your website
  • Campaigns : Visitors directed to your website through specific marketing campaigns, such as email newsletters, Google Ads, promotional links, etc.
  • Social Networks : Visitors accessing your website by clicking on links shared on social media platforms like Facebook, X (Twitter), LinkedIn, etc.

  Understanding where your visitors are coming from can help you focus your marketing efforts on the traffic sources with the highest conversion rates. 

  Suppose your email marketing campaign isn’t driving any traffic to your website, but your ad campaign is responsible for over 25% of your conversions. In that case, you might consider doubling your advertising efforts.

  10. Form average time spent

  Forms are a crucial part of your website’s marketing strategy. Forms can help you :

  • Learn more about your visitors
  • Gather feedback from your audience
  • Convert visitors into email subscribers
  • And more

  Form average time spent is the average amount of time a visitor spends on a specific form on your website. The time is calculated as the difference between the first interaction with a form field (for example, a field focus) and the last interaction with a form.

  Want to convert more visitors into leads ? Then, you need to understand your form analytics better. Learn more here.

  11. Play rate

  If you want to keep your audience engaged (and convert more visitors), you need to publish different types of media.

  But if your video or audio content isn’t performing well, then you’re wasting your time.

  That’s where play rate comes in. It’s calculated by analysing visitors who watched or listened to a specific media after they have visited a web page.

  With play rate, you can track any video, podcast, or audiobook plays.

  You can easily track it within Matomo’s Media Analytics. The best part ? This feature works out of the box, so you don’t need to configure it to start leveraging the analytics.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  12. Returning visitors

  Returning visitors are users who visit your website more than once over a specific time.

  You will want to measure the number of returning visitors to your website, as this information can give you additional insights into your marketing strategies, company branding and content.

  It can also help you better understand your customer base, giving you a clearer sense of their top desires and pain points.

  13. Device type

  Device type tracks the different devices visitors use to visit your website. These could be :

  • Tablets
  • Mobile phones
  • Desktop computers

  Knowing what your visitors are using to access your website can help you improve the overall user experience.

  For example, if 80% of your visitors use mobile phones, you could think about optimising your web pages to format with mobile devices. 

  

  14. Top exit pages

  Top exit pages are the pages that a visitor leaves your website from the most.

  Each web page will have a specific exit rate percentage based on how many people leave the website on a particular page.

  This can be quite helpful in understanding how visitors interact with your website. It can also help you uncover and fix any issues with your website you may not be aware of.

  For instance, one of your product pages has the highest exit rate on your website. By looking into why that is, you discover that your “Add to Cart” button isn’t functioning correctly, and your visitors can’t buy that particular product, so they exit out of frustration.

  15. Marketing attribution

  Marketing attribution (multi-touch attribution) helps you see which touchpoints have the greatest impact on conversions.

  Within Matomo, revenue attribution involves assigning credit for revenue across multiple touchpoints that contribute to a conversion.

  Matomo’s multi-touch attribution models use different weighting factors, like linear or time decay, to allocate credit to each touchpoint based on its influence.

  Matomo’s multi-touch attribution reports provide insights into how revenue is distributed across different touchpoints, marketing channels, campaigns, and actions. These reports allow you to analyse the contribution of each touchpoint to revenue generation and identify the most influential interactions in the customer journey.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  16. Event tracking

  Every website has multiple actions a user can perform called “events”. These could be downloading a template, submitting contact information, signing up for a newsletter or clicking a link.

  Tracking events can give you additional context into what your visitors are interested in or don’t care about. This allows you to target them better through those events, potentially creating new, unique conversions and boosting the growth of your business.

  It can also lead to discovering potential issues within your website if you notice visitors aren’t taking action on certain CTAs, such as broken links or lack of content on certain pages. By uncovering these issues, you can quickly fix them to increase your conversions.

  

  Start tracking your website metrics with Matomo today

  There’s much to consider when creating and running your website, such as the design, copy and flow. 

  While these are necessary, tracking your website’s data is one of the most important aspects of running a site. It’s crucial in helping you optimise your site’s performance and create a great experience for your visitors.

  Every interaction a visitor has on your site is unique and leaves valuable clues you can use to improve all aspects of your site experience. 

  Understanding what your visitors like, what website performance issues they’re running into and how they interact across your website is crucial to improving your marketing and sales efforts.

  While tracking this much data can feel overwhelming, having all your key metrics in one place and broken down into easy-to-understand benchmarks can help alleviate the stress and headache of data tracking. 

  That’s where a web analytics platform like Matomo comes in.

  With Matomo, you can easily track, store and analyse every piece of data on your website automatically to improve your site performance and user experience and drive conversions. 

  With Matomo, you can take back control with a platform that gives you 100% data ownership.

  Used on over 1 million websites in over 190 countries, Matomo gives you :

  • Accurate data (no data sampling)
  • Privacy-friendly and GDPR-compliant analytics
  • Open-source access to create a custom solution for you

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

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• How Media Analytics for Piwik gives you the insights you need to measure how effective your video and audio marketing is – Part 2

  
  2 février 2017, par InnoCraft — Community

  In Part 1 we have covered some of the Media Analytics features and explained why you cannot afford to not measure the media usage on your website. Chances are, you are wasting or losing money and time by not making the most out of your marketing strategy this very second. In this part, we continue showing you some more insights you can expect to get from Media Analytics and how nicely it is integrated into Piwik.

  Video, Audio and Media Player reports

  Media Analytics adds several new reports around videos, audios and media players. They are all quite similar and give you similar insights so we will mainly focus on the Video Titles report.

  Metrics

  The above mentioned reports give you all the same insights and features so we will mainly focus on the “Video Titles” report. When you open such a report for the first time, you will see a report like this with the following metrics :

  

  • “Impressions”, the number of times a visitor has viewed a page where this media was included.
  • “Plays”, the number of times a visitor watched or listened to this media.
  • “Play rate”, the percentage of visitors that watched or listened to a media after they have visited a page where this media was included.
  • “Finishes”, the percentage of visitors who played a media and finished it.
  • “Avg. time spent”, the average amount of time a visitor spent watching or listening to this media.
  • “Avg. media length” the average length of a video or audio media file. This number may vary for example if the media is a stream.
  • “Avg completion” the percentage of how much visitors have watched of a video.

  If you are not sure what a certain metric means, simply hover the metric title in the UI and you will get a detailed explanation. By changing the visualization to the “All Columns Table” in the bottom of the report, you get to see even more metrics like “Plays by unique visitors”, “Impressions by unique visitors”, “Finish rate”, “Avg. time to play aka hesitation time”, “Fullscreen rate” and we are always adding more metrics.

  These metrics are available for the following reports :

  • “Video / Audio Titles” shows you all metrics aggregated by video or audio title
  • “Video / Audio Resource URLs” shows you all metrics aggregated by the video or audio resource URL, for example “https://piwik.org/media.mp4”.
  • “Video / Audio Resource URLs grouped” removes some information from the URLs like subdomain, file extensions and other information to get aggregated metrics when you provide the same media in different formats.
  • “Videos per hour in website’s timezone” lets you find out how your media content is consumed depending on the hour of the day. You might realize that your media is consumed very differently in the morning vs at night.
  • “Video Resolutions” lets you discover how your video is consumed depending on the resolution.
  • “Media players” report is useful if you use different media players on your websites or apps and want to see how engagement with your media compares by media player.

  Row evolution

  At InnoCraft, we understand that static numbers are not so useful. When you see for example that yesterday 20 visitors played a certain media, would you know whether this is good or bad ? This is why we always give you the possibility to see the data in relation to the recorded data in the past. To see how a specific media performs over time, simply hover a media title or media resource URL and click on the “Row Evolution” icon.

  

  Now you can see whether actually more or less visitors played your chosen video for the selected period. Simply click on any metric name and the chosen metrics will be plotted in the big evolution graph.

  This feature is similar to the Media Overall evolution graph introduced in Part 1, but shows you a detailed evolution for an individual media title or resource.

  Media details

  Now that you know some of the most important media metrics, you might want to look a bit deeper into the user behaviour. For example we mentioned before the “Avg time spent on media” metric. Such an average number doesn’t let you know whether most visitors spent about the same time watching the video, or whether there were many more visitors that watched it only for a few seconds and a few that watched it for very long.

  One of the ways to get this insight is by again hovering any media title or resource URL and clicking on the “Media details” icon. It will open a new popup showing you a new set of reports like these :

  

  The “Time spent watching” and “How far visitors reached in the media” bar charts show you on the X-Axis how much time each visitor spent on watching a video and how far in the video they reached. On the Y-Axis you see the number of visitors. This lets you discover whether your users for example jump often to the middle or end of the video and which parts of your video was seen most often.

  

  The “How often the media was watched in a certain hour” and “Which resolutions the media was watched” is similar to the reports introduced in Part 1 of the blog post. However, this time instead of showing aggregated video or audio content data, they display data for a specific media title or media resource URL.

  Segmented audience log

  In Part 1 we have already introduced the Audience Log and explained that it is useful to better understand the user behaviour. Just a quick recap : The Audience Log shows you chronologically every action a specific visitor has performed on your website : Which pages they viewed, how they interacted with your media, when they clicked somewhere, and much more.

  By hovering a media title or a media resource and then selecting “Segmented audience log” you get to see the same log, but this time it will show only visitors that have interacted with the selected media. This will be useful for you for example when you notice an unusual value for a metric and then want to better understand why a metric is like that.

  

  Applying segments

  Media Analytics lets you apply any Piwik segment to the media reports allowing you to dice your visitors or personas multiplying the value that you get out of Media Analytics. For example you may want to apply a segment and analyze the media usage for visitors that have visited your website or mobile app for the first time vs. recurring visitors. Sometimes it may be interesting how visitors that converted a specific goal or purchased something consume your media, the possibilities are endless. We really recommend to take advantage of segments to understand your different target groups even better.

  The plugin also adds a lot of new segments to your Piwik letting you segment any Piwik report by visitors that have viewed or interacted with your media. For example you could go to the “Visitors => Devices” report and apply a media segment to see which devices were used the most to view your media. You can also combine segments to see for example how often your goals were converted when a visitor viewed media for longer than 10 seconds after waiting for at least 20 seconds before playing your media and when they played at least 3 videos during their visit.

  Widgets, Scheduled Reports, and more.

  This is not where the fun ends. Media Analytics defines more than 15 new widgets that you can add to your dashboard or export it into a third party website. You can set up Scheduled Reports to receive the Media reports automatically via email or sms or download the report to share it with your colleagues. It works also very well with Custom Alerts and you can view the Media reports in the Piwik Mobile app for Android and iOS. Via the HTTP Reporting API you can fetch any report in various formats. The plugin is really nicely integrated into Piwik we would need some more blog posts to fully cover all the ways Media Analytics advances your Piwik experience and how you can use and dig into all the data to increase your conversions and sales.

  How to get Media Analytics and related features

  You can get Media Analytics on the Piwik Marketplace. If you want to learn more about this feature, you might be also interested in the Media Analytics User Guide and the Media Analytics FAQ.

• Parsing The Clue Chronicles

  30 décembre 2018, par Multimedia Mike — Game Hacking

  A long time ago, I procured a 1999 game called Clue Chronicles : Fatal Illusion, based on the classic board game Clue, a.k.a. Cluedo. At the time, I was big into collecting old, unloved PC games so that I could research obscure multimedia formats.

  
  
  

  Surveying the 3 CD-ROMs contained in the box packaging revealed only Smacker (SMK) videos for full motion video which was nothing new to me or the multimedia hacking community at the time. Studying the mix of data formats present on the discs, I found a selection of straightforward formats such as WAV for audio and BMP for still images. I generally find myself more fascinated by how computer games are constructed rather than by playing them, and this mix of files has always triggered a strong “I could implement a new engine for this !” feeling in me, perhaps as part of the ScummVM project which already provides the core infrastructure for reimplementing engines for 2D adventure games.

  Tying all of the assets together is a custom high-level programming language. I have touched on this before in a blog post over a decade ago. The scripts are in a series of files bearing the extension .ini (usually reserved for configuration scripts, but we’ll let that slide). A representative sample of such a script can be found here :

  clue-chronicles-scarlet-1.txt

  What Is This Language ?
  At the time I first analyzed this language, I was still primarily a C/C++-minded programmer, with a decent amount of Perl experience as a high level language, and had just started to explore Python. I assessed this language to be “mildly object oriented with C++-type comments (‘//’) and reliant upon a number of implicit library functions”. Other people saw other properties. When I look at it nowadays, it reminds me a bit more of JavaScript than C++. I think it’s sort of a Rorschach test for programming languages.

  Strangely, I sort of had this fear that I would put a lot of effort into figuring out how to parse out the language only for someone to come along and point out that it’s a well-known yet academic language that already has a great deal of supporting code and libraries available as open source. Google for “spanish dolphins far side comic” for an illustration of the feeling this would leave me with.

  It doesn’t matter in the end. Even if such libraries exist, how easy would they be to integrate into something like ScummVM ? Time to focus on a workable approach to understanding and processing the format.

  Problem Scope
  So I set about to see if I can write a program to parse the language seen in these INI files. Some questions :

  1. How large is the corpus of data that I need to be sure to support ?
  2. What parsing approach should I take ?
  3. What is the exact language format ?
  4. Other hidden challenges ?

  To figure out how large the data corpus is, I counted all of the INI files on all of the discs. There are 138 unique INI files between the 3 discs. However, there are 146 unique INI files after installation. This leads to a hidden challenge described a bit later.

  What parsing approach should I take ? I worried a bit too much that I might not be doing this the “right” way. I’m trying to ignore doubts like this, like how “SQL Shame” blocked me on a task for a little while a few years ago as I concerned myself that I might not be using the purest, most elegant approach to the problem. I know I covered language parsing a lot time ago in university computer science education and there is a lot of academic literature to the matter. But sometimes, you just have to charge in and experiment and prototype and see what falls out. In doing so, I expect to have a better understanding of the problems that need to solved and the right questions to ask, not unlike that time that I wrote a continuous integration system from scratch because I didn’t actually know that “continuous integration” was the keyword I needed.

  Next, what is the exact language format ? I realized that parsing the language isn’t the first and foremost problem here– I need to know exactly what the language is. I need to know what the grammar are keywords are. In essence, I need to reverse engineer the language before I write a proper parser for it. I guess that fits in nicely with the historical aim of this blog (reverse engineering).

  Now, about the hidden challenges– I mentioned that there are 8 more INI files after the game installs itself. Okay, so what’s the big deal ? For some reason, all of the INI files are in plaintext on the CD-ROM but get compressed (apparently, according to file size ratios) when installed to the hard drive. This includes those 8 extra INI files. I thought to look inside the CAB installation archive file on the CD-ROM and the files were there… but all in compressed form. I suspect that one of the files forms the “root” of the program and is the launching point for the game.

  Parsing Approach
  I took a stab at parsing an INI file. My approach was to first perform lexical analysis on the file and create a list of 4 types : symbols, numbers, strings, and language elements ([]{}()=., :). Apparently, this is the kind of thing that Lex/Flex are good at. This prototyping tool is written in Python, but when I port this to ScummVM, it might be useful to call upon the services of Lex/Flex, or another lexical analyzer, for there are many. I have a feeling it will be easier to use better tools when I understand the full structure of the language based on the data available.
  
  The purpose of this tool is to explore all the possibilities of the existing corpus of INI files. To that end, I ran all 138 of the plaintext files through it, collected all of the symbols, and massaged the results, assuming that the symbols that occurred most frequently are probably core language features. These are all the symbols which occur more than 1000 times among all the scripts :

     6248 false
     5734 looping
     4390 scripts
     3877 layer
     3423 sequentialscript
     3408 setactive
     3360 file
     3257 thescreen
     3239 true
     3008 autoplay
     2914 offset
     2599 transparent
     2441 text
     2361 caption
     2276 add
     2205 ge
     2197 smackanimation
     2196 graphicscript
     2196 graphic
     1977 setstate
     1642 state
     1611 skippable
     1576 desc
     1413 delayscript
     1298 script
     1267 seconds
     1019 rect
  

  About That Compression
  I have sorted out at least these few details of the compression :

  bytes 0-3    "COMP" (a pretty strong sign that this is, in fact, compressed data)
  bytes 4-11   unknown
  bytes 12-15  size of uncompressed data
  bytes 16-19  size of compressed data (filesize - 20)
  bytes 20-    compressed payload
  

  The compression ratios are on the same order of gzip. I was hoping that it was stock zlib data. However, I have been unable to prove this. I wrote a Python script that scrubbed through the first 100 bytes of payload data and tried to get Python’s zlib.decompress to initialize– no luck. It’s frustrating to know that I’ll have to reverse engineer a compression algorithm that deals with just 8 total text files if I want to see this effort through to fruition.

  Update, January 15, 2019
  Some folks expressed interest in trying to sort out the details of the compression format. So I have posted a followup in which I post some samples and go into deeper details about things I have tried :

  Reverse Engineering Clue Chronicles Compression

  The post Parsing The Clue Chronicles first appeared on Breaking Eggs And Making Omelettes.