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• "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.

  


• CRO Audit : Increase Your Conversions in 10 Simple Steps

  25 mars 2024, par Erin

  You have two options if you’re unhappy with your website’s conversion rates.

  The first is to implement a couple of random tactics you heard on that marketing podcast, which worked for a business completely unrelated to yours. 

  The other is to take a more systematic, measured approach. An approach that finds specific problems with the pages on your site and fixes them one by one. 

  You’re choosing the second option, right ?

  Good, then let’s explain what a conversion rate optimisation audit is and how you can complete one using our step-by-step process.

  What is a CRO audit ?

  A conversion rate optimisation audit (CRO audit) systematically evaluates your website. It identifies opportunities to enhance your website’s performance and improve conversion rates. 

  During the audit, you’ll analyse your website’s entire customer journey, collect valuable user behaviour data and cross reference that with web analytics to find site elements (forms, calls-to-actions, etc.) that you can optimise.

  

  It’s one (and usually the first) part of a wider CRO strategy. 

  For example, an online retailer might run a CRO audit to discover why cart abandonment rates are high. The audit may throw up several potential problems (like a confusing checkout form and poor navigation), which the retailer can then spend time optimising using A/B tests. 

  Why run a CRO audit ?

  A CRO audit can be a lot of work, but it’s well worth the effort. Here are the benefits you can expect from running one.

  Generate targeted and relevant insights

  You’ve probably already tested some “best practice” conversion rate optimisations, like changing the colour of your CTA button, adding social proof or highlighting benefits to your headlines. 

  These are great, but they aren’t tailored to your audience. Running a CRO audit will ensure you find (and rectify) the conversion bottlenecks and barriers that impact your users, not someone else’s.

  Improve conversion rates

  Ultimately, CRO audits are about improving conversion rates and increasing revenue. Finding and eliminating barriers to conversion makes it much more likely that users will convert. 

  But that’s not all. CRO audits also improve the user experience and customer satisfaction. The audit process will help you understand how users behave on your website, allowing you to create a more user-friendly customer experience. 

  A 10-step process for running your first CRO audit 

  Want to conduct your first CRO audit ? Follow the ten-step process we outline below :

  

  1. Define your goals

  Start your CRO audit by setting conversion goals that marry with the wider goals of your business. The more clearly you define your goals, the easier it will be to evaluate your website for opportunities. 

  Your goals could include :

  • Booking more trials
  • Getting more email subscribers
  • Reducing cart abandonments

  You should also define the specific actions users need to take for you to achieve these goals. For example, users will have to click on your call-to-action and complete a form to book more trials. On the other hand, reducing cart abandonments requires users to add items to their cart and click through all of the forms during the checkout process. 

  If you’re unsure where to start, we recommend reading our CRO statistics roundup to see how your site compares to industry averages for metrics like conversion and click-through rates. 

  You’ll also want to ensure you track these conversion goals in your web analytics software. In Matomo, it only takes a few minutes to set up a new conversion goal, and the goals dashboard makes it easy to see your performance at a glance. 

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  2. Review your analytics

  With your goals in mind, the next step is to dive into your website analytics and identify pages that need improvement.

  Consider the following conversion metrics when analysing pages :

  • Conversion rate
  • Average time on page
  • Average order value
  • Click-through rate

  Ensure you’re analysing metrics aligning with the goals you set in step one. Average order value could be a great metric to track if you want to reduce cart abandonments, for example, but it’s unsuitable to get more email subscribers.

  3. Research the user experience

  Next, you’ll want to gather user experience data to better understand how potential customers use your website and why they aren’t converting as often as you’d like. 

  You can use several tools for user behaviour analysis, but we recommend heatmaps and session recordings.

  Heatmaps visually represent how users click, move and scroll your website. It will show where visitors place their attention and which page elements are ignored. 

  Take a look at this example below from our website. As you can see, the navigation, headline and CTA get the most attention. If we weren’t seeing as many conversions as we liked and our CTAs were getting ignored, that might be a sign to change their colour or placement. 

  

  Session recordings capture the actions users take as they browse your website. They let you watch a video playback of how visitors behave, capturing clicks and scrolls so you can see each visitor’s steps in order. 

  Session recordings will show you how users navigate and where they drop off. 

  4. Analyse your forms

  Whether your forms are too confusing or too long, there are plenty of reasons for users to abandon your forms. 

  But how many forms are they abandoning exactly and which forms are there ?

  That’s what form analysis is for. 

  Running a form analysis will highlight which forms need work and reveal whether forms could be contributing to a page’s poor conversion rate. It’s how Concrete CMS tripled its leads in just a few days.

  Matomo’s Form Analytics feature makes running form analysis easy.

  

  Just open up the forms dashboard to get a snapshot of your forms’ key metrics, including average hesitation time, starter rate and submission rates. 

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

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  5. Analyse your conversion funnel

  Next, analyse the conversion funnel to see if there’s an obvious bottleneck or several pages where visitors abandon your desired action. Common conversion abandonment points are shopping carts and forms.

  

  For example, you could find there is a drop-off in conversions between checking out and making a purchase or between booking a demo and signing up for a subscription. Understanding where these drop-offs occur lets you dig deeper and make targeted improvements.

  Don’t worry if you’ve got a very long funnel. Start at the bottom and work backward. Problems with the pages at the very end of your funnel tasked with converting customers (landing pages, checkout pages, etc.) will have the biggest impact on your conversion rate. So, it makes sense to start there. 

  6. Analyse campaigns and traffic sources (marketing attribution)

  It’s now time to analyse traffic quality to ensure you’re powering your conversion optimisation efforts with the best traffic possible. 

  This can also help you find your best customers so you can focus on acquiring more of them and tailoring your optimisation efforts to their preferences. 

  Run a marketing attribution report to see which traffic sources generate the most conversions and have the highest conversion rates. 

  

  Using marketing attribution is crucial here because it gives a fuller picture of how customers move through their journey, recognising the impact of various touchpoints in making a decision, unlike last-click attribution, which only credits the final touchpoint before a conversion.

  7. Use surveys and other qualitative data sources

  Increase the amount of qualitative data you have access to by speaking directly to customers. Surveys, interviews and other user feedback methods add depth and context to your user behaviour research.

  Sure, you aren’t getting feedback from hundreds of customers like you do with heatmaps or session recordings, but the information can sometimes be much richer. Users will often tell you outright why they didn’t take a specific action in a survey response (or what convinced them to convert). 

  Running surveys is now even easier in Matomo, thanks to the Matomo Surveys third-party plugin. This lets you add a customisable survey popup to your site, the data from which is automatically added to Matomo and can be combined with Matomo segments.

  8. Develop a conversion hypothesis

  Using all of the insights you’ve gathered up to this point, you can now hypothesise what’s wrong and how you can fix it. 

  Here’s a template you can use :

  

  This could end up looking something like the following :

  Based on evidence gathered from web analytics and heatmaps, moving our signup form above the fold will fix our lack of free trial signups, improving signups by 50%.

  

  Make sure you write your hypothesis down somewhere. Matomo lets you document your hypothesis when creating an A/B test, so it’s easy to reflect on when the test finishes. 

  9. Run A/B tests

  Now, it’s time to put your theory into practice by running an A/B test.

  Create an experiment using a platform like Matomo that creates two different versions of your page : the original and one with the change you mentioned in your hypothesis. 

  There’s no set time for you to run an A/B test. Just keep running it until the outcome is statistically significant. This is something your A/B testing platform should do automatically. 

  A statistically significant result means it would be very unlikely the outcome doesn’t happen in the long term.

  

  As you can see in the image above, the wide header variation has significantly outperformed both the original and the other variation. So we can be pretty confident about making the change permanent. 

  If the outcome of your A/B test also validates your conversion hypothesis, you can implement the change. If not, analyse the data, brainstorm another hypothesis and run another A/B test. 

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

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  10. Monitor and iterate

  You need to develop a culture of continuous improvement to succeed with conversion rate optimisation. That means constantly monitoring your conversion goals and running tests to improve your metrics. 

  While you don’t need to run a conversion audit every month, you should run audits regularly throughout the year.

  How often should you conduct a CRO audit ? 

  You should conduct a CRO audit fairly regularly. 

  We recommend creating a CRO schedule that sees you run a CRO audit every six to 12 months. That will ensure you continue identifying problem pages and keeping your conversion rates competitive. 

  Regular CRO audits will also account for evolving consumer behaviours, changes in your industry and your own business goals, all of which can impact your approach conversion rate optimisation. 

  Run your CRO audit with Matomo

  A CRO audit process is the only way you can identify conversion optimisation methods that will work for your site and your target audience. It’s a methodical, data-backed strategy for making targeted improvements to send conversion rates soaring. 

  There are a lot of steps to complete, but you don’t need dozens of tools to run a CRO audit process. 

  Just one : Matomo.

  Unlike other web analytics platforms, like Google Analytics, Matomo has the built-in tools and plugins to help with every step of the CRO audit process, from web analytics to conversion funnel analysis and A/B testing. With its accurate, unsampled data and privacy-friendly tracking, Matomo is the ideal choice for optimising conversions. 

  Learn how to increase your conversions with Matomo, and start a free 21-day trial today. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

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

  Start for free

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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

  21 day free trial. No credit card required.

  
  

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