Recherche avancée

Sur d’autres sites (10281)

• How to Increase Conversions With Form Analysis

  30 janvier 2024, par Erin

  Forms are one of the most important elements of your website. They are also one of the most difficult elements to analyse and improve. 

  Unlike a webpage, forms aren’t all that easy to analyse with standard web analytics tools. You need to learn how to conduct form analysis if you want to improve your forms’ conversion rates and increase revenue. 

  In this article, we’ll explain what form analysis is and why conducting a thorough form analysis is so important. 

  What is form analysis ?

  Form analysis is a process that measures the effectiveness of your forms. Form analysis uses several tools and techniques like a form analytics platform, heatmaps, and session recordings to collect user data and understand how visitors behave when filling in forms. 

  The goal is to improve the design and effectiveness of your forms, reducing abandonment rate and encouraging more users to submit them. 

  There are plenty of reasons visitors could be having trouble with your forms, from confusing form fields to poor design and lengthy verification processes. Form analytics can help you pinpoint why your form’s conversion rate is so low or why so many users abandon your form halfway through filling it in. 

  Why is form analysis important ?

  Website forms have some of the highest bounce rates and abandonments of any website element. By analysing your forms, you can achieve the following outcomes :

  

  Reduce form abandonment

  When it’s tough enough to get users to start filling in your form, the last thing you want them to do is abandon it halfway through. But that’s probably what your users are doing more than you’d like to think. 

  Why are they abandoning it ? Even if you’re humble enough to admit you didn’t create the greatest form the world’s ever seen, it can still be incredibly difficult to pin down why users give up on your form.

  That’s unless you conduct a form analysis. By analysing metrics and user behaviour, you can pinpoint and rectify the issues that cause users to abandon your form. 

  Improve the user experience

  Best practices will only take you so far. How users behave when filling in a form on your website may be completely different to how they behave on another site. That’s why you need to use form analysis to understand how users behave specifically on your website — and then use that information to optimise the design, layout, and content of the form to better suit them. 

  If one field is regularly left empty, for example, you can delete it. If users spend several minutes filling out a form with a high abandonment rate, you could shorten it. 

  The goal isn’t to make the best form ever but to make the best form for your audience. 

  Increase conversions

  Ultimately, form analysis helps you improve your form’s most important metric : conversions. Reducing your abandonment rate will naturally lead to more completions, but so will taking advantage of other optimisation opportunities that only become clear with form analysis. This can include optimisations like :

  • Moving the form higher up on the page
  • Shortening the form
  • Changing the heading and CTAs
  • Renaming field labels 

  A thorough form analysis process can ensure your forms generate as many conversions as possible. 

  Why do users abandon forms ?

  Are you already suffering from high form abandonment rates ? Don’t worry, you’re not alone. Marketers regularly make the same mistakes when creating forms that cause users to give up halfway through completion.

  Here are some of the most common reasons for form abandonment :

  • There are too many steps. If you’re telling users they’ve just completed step 2 of 12, you can bet they won’t bother finishing your form. 
  • They ask for too much information. No one wants to fill out a long form, and often, users won’t have the information on hand if you ask for too much. Just look at the rate left blank from the Unneeded Fields report in the screenshot below :

  

  • The form is confusing. Unclear form fields or directions can put users off. 
  • All the fields are free text and time-consuming. Filling out forms with long text fields takes too much time. To speed things up, use dropdown options in the fields, but keep the options to a minimum. This not only helps users finish the form faster but also makes it easier to analyse the data later because it keeps the data format consistent so you can organise the information more efficiently. 
  • Users don’t trust the form. This is a particular problem on checkout pages where users are entering sensitive information.

  How to conduct form analysis

  You need to collect user behaviour data to effectively analyse your forms. But a lot of traditional website analytics tools won’t have the required functionality. 

  Matomo is different. Our web analytics solution offers comprehensive web analytics as well as additional features like Heatmaps, Session Recordings, A/B Testing, and Form Analytics to provide all the functionality you need. 

  Now if you don’t use Matomo, you can try it free for 21 days (no credit card required) to see if it’s the right tool for you.

  Whether you use Matomo or not is up to you. But, once you have a suitable tool in place, just follow the steps below to conduct a form analysis. 

  Check your analytics

  Tracking and analysing specific form metrics should be the first place you start. We recommend collecting data on the following metrics :

  • Form starter rate : the percentage of visitors who actually start to fill in your form
  • Completion rate : the percentage of visitors who complete the form
  • Form abandonment rate : the percentage of users who gave up filling in your form
  • Time spent completing your form : the average length of time users spend on your form

  Let’s look at these metrics are in Matomo’s Form Analytics :

  

  The dashboard shows an overview of these metrics over a given period, allowing you to see at a glance whether there are issues you need to rectify. 

  Next, deep dive into the performance of each form to see things like :

  • Drop off fields
  • Unused fields
  • Entry field
  • Most corrected fields 

  You can even use Matomo’s visitor log to see who’s behind every submission.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Use a heatmap

  A heatmap is a colour-based graphical representation of data. A heatmap will show what users to do on your website, including : 

  • How far they scroll
  • Which buttons they click on
  • Where they focus their attention

  When used on a webpage with a form, you’ll be able to see how often users interact with your form based on the heatmap colour, with warmer colours representing greater engagement levels.

  Let’s look at a heatmap in Matomo :

  

  This heatmap is showing us how far down users have scrolled. It’s clear that only 63% of visitors are reaching the point above our call to action to see all features. We might want to consider moving that call to action up in order to get more engagement. 

  A heatmap is a great way to see whether your form’s placement gets the level of attention you want from visitors and to what extent visitors interact with your field.

  Record user sessions

  Session replays go even further than heatmaps, recording a real-life user interacting with your site. It’s like looking over a visitor’s shoulder while they use your site.

  

  With Matomo, you can record any sessions where the user takes a certain action (like starting to fill in a form), allowing you to build a rich library of qualitative data. 

  You can then replay a recorded session at your leisure to understand exactly how users interact with your forms.

  Segment users

  If you really want to understand how visitors use your forms, then it’s essential to segment your data. 

  You can segment all Form Analytics reports by over 100 pre-built segments in Matomo.

  

  One way to segment your data is by comparing the average time on form of those who completed the form with those who abandoned it. 

  If users abandon a form quickly, that could indicate your form is irrelevant to this audience or too long. If users spend a lot of time on the form, however, it’s probably safe to assume that it is relevant but there is something wrong with the form itself. 

  Looking at the Field Timings report will help you pinpoint which field visitors are spending the most time on and causing frustration. 

  

  The Field Timings example report in Matomo above, it’s evident that the “Overview of your needs” field takes up the most time (avg. time spent is 1 min 40s). To improve this, we might want to change it to a dropdown field. This way, users can quickly select options, and if necessary, provide additional details.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Another way is to segment data by traffic source and compare each source’s conversion rate. This will show whether one traffic source converts better than another or if one source isn’t interested in your form at all.

  How to optimise web forms

  Want to implement what you’ve learnt from your form analysis ? Follow these steps to optimise your existing web forms. 

  Define your form’s purpose

  The first step in optimising your existing web forms is to give a clear and definitive purpose to every single one. 

  When you have a defined goal, creating a form users will complete is much easier. After all, if you don’t know why people should fill in one of your forms, how would a visitor possibly know ?

  Take a look at one of our forms below :

  

  The purpose of this form is to get users to sign up for a free trial of our web analytics platform, and every element works towards that goal :

  • The headline directs the user to take action
  • The copy explains that it’s a free trial that doesn’t require credit card details
  • The green call-to-action button reinforces the action and benefit 
  • There is validation to support this under the form – “Trusted on over 1 million websites in over 190+ countries”

  Our clear instructions leave users no doubt about why they should fill in the form or what will happen. 

  Choose the right type of form

  You can use several forms on your website, each with different designs, form fields, and goals.

  For example :

  • Registration forms are fairly minimalist and designed to collect the least amount of data possible. 
  • Contact forms are concise so that it’s easy for potential customers to reach your team. 
  • Checkout forms balance a need to collect important data with a streamlined design that doesn’t put users off.
  • Lead generation forms are compelling and usually include qualifying questions so sales teams can score leads.

  Make sure you are using the right type of form to avoid abandonments and other issues. For example, requiring users to fill in a lengthy lead generation-style form when you want them to sign up for a free trial will probably kill your conversion rate. 

  Test form elements

  If your form analysis has shed light on one or two issues, you can use A/B or multivariate testing to trial new elements or designs and see how they compare.

  There’s no shortage of elements you can test, including the form’s :

  • Headline
  • Placement
  • Design
  • CTA button
  • Colour-scheme
  • Length
  • Form fields

  

  Matomo makes it easy to create and run A/B tests on your website’s forms. 

  Move your form above the fold

  One of the simplest ways to optimise your web form is to move it above the fold — that’s the section of the screen users see when they load your page. 

  Why ? Well, the more people who see your form, the more people will fill it in. And when it’s above the fold, users can’t help but see it.

  Conclusion

  Forms are one of the most important elements on your website, so why not treat them as such and regularly run a thorough form analysis ? By doing so, you’ll identify ways to optimise your form, improve the user experience, and improve conversions. 

  Matomo is the best platform for conducting form analysis. Our combination of web analytics, Form Analytics, Session Recordings, and Heatmaps means you have all the tools you need to learn exactly how visitors interact with your forms. 

  See just how powerful Matomo’s tools are by starting a free 21-day trial, 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
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

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

  Start improving your websites now

  

• 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.

  Try Matomo for Free

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

  Start for free

  No credit card required

  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

  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
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

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

  Start improving your websites now

  

• "Error opening input" error when running ffmpeg via shell script

  15 octobre 2024, par Roni Yaniv

  I'm on a macbook running sonoma 14.7.

  


  I have the following ffmpeg command which runs just fine by itself in the same folder of the files I need to modify :

  


  ffmpeg -i "water-stream-90fps.mp4" -vf "drawtext=text='Frame\: %{frame_num}': start_number=1: x=(w-text_w): y=(h-text_h):fontsize=(h*10/100):fontcolor=yellow,drawtext=text='%{pts\:hms}':x=0:y=0:fontsize=(h*10/100):fontcolor=yellow" "water-stream-90fps-with-markers.mp4"

  


  However, when I try to use it in a shell script by running ./add_markers.sh in the same folder, I get an error.

  


  This is the add_markers.sh script :

  


  #!/bin/bash

# Replace '/path/to/your/folder' with the actual path to your folder
folder=$(pwd)

# Replace 'ffmpeg -i input.mp4 -vf scale=640:480 output.mp4' with your desired FFmpeg command
ffmpeg_command="ffmpeg -i input.mp4 -vf \"drawtext=text='Frame\: %{frame_num}': start_number=1: x=(w-text_w): y=(h-text_h):fontsize=(h*10/100):fontcolor=yellow,drawtext=text='%{pts\:hms}':x=0:y=0:fontsize=(h*10/100):fontcolor=yellow\" output.mp4"

echo "$ffmpeg_command"

# Loop through all files in the folder and execute the FFmpeg command

for file in "$folder"/*; do
    filename=$(basename "${file%.*}") #get only the first part of the file name without path or extension

    # Replace 'input.mp4' with the current filename and 'output.mp4' with the new filename. 
    # Added double quotes to manage filenames with spaces.
    new_command="${ffmpeg_command//input.mp4/\"$filename.mp4\"}"
    new_command="${new_command//output.mp4/\"$filename-with-markers.mp4\"}"

    echo "Running $new_command"

    $new_command

done


  


  This is the error I get (for one of the files, same error for all of them) :

  


  Running ffmpeg -i "water-stream-90fps.mp4" -vf "drawtext=text='Frame\: %{frame_num}': start_number=1: x=(w-text_w): y=(h-text_h):fontsize=(h*10/100):fontcolor=yellow,drawtext=text='%{pts\:hms}':x=0:y=0:fontsize=(h*10/100):fontcolor=yellow" "water-stream-90fps-with-markers.mp4"
ffmpeg version 7.0 Copyright (c) 2000-2024 the FFmpeg developers
  built with Apple clang version 15.0.0 (clang-1500.3.9.4)
  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/7.0 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libharfbuzz --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libssh --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopenvino --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon
  libavutil      59.  8.100 / 59.  8.100
  libavcodec     61.  3.100 / 61.  3.100
  libavformat    61.  1.100 / 61.  1.100
  libavdevice    61.  1.100 / 61.  1.100
  libavfilter    10.  1.100 / 10.  1.100
  libswscale      8.  1.100 /  8.  1.100
  libswresample   5.  1.100 /  5.  1.100
  libpostproc    58.  1.100 / 58.  1.100
[in#0 @ 0x6000015bc300] Error opening input: No such file or directory
Error opening input file "water-stream-90fps.mp4".
Error opening input files: No such file or directory


  


  I tried all kinds of things but my brain is starting to swell. Any guidance/help would be appreciated.