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• Conversion Funnel Optimisation : 10 Ways to Convert More

  24 janvier 2024, par Erin

  Converting leads into happy customers is the ultimate goal of any sales and marketing team. But there are many steps in between those two events, or in other words, funnel stages. 

  Your sales funnel includes all the steps you take to make your audience aware of your product or services and convince them to purchase. Conversion funnel optimisation strategies can help you move users through the stages of your sales funnel. 

  This article will show you how to optimise your conversion funnel and boost sales — no matter how your funnel looks. We’ll go over practical tips you can implement and how you can analyse and measure results.

  Let’s get started.

  What is conversion funnel optimisation ? 

  Conversion funnel optimisation is the strategic and ongoing process of refining and improving the different stages of a sales or marketing funnel to increase the rate at which users complete desired actions.

  A sales funnel represents the stages a potential customer goes through before purchasing. 

  The typical stages of a sales funnel include :

  • Awareness : At the top of the funnel, potential customers become aware of your product or service. 
  • Consideration : In this stage, prospects evaluate the product or service against alternatives. They may compare features, prices and customer reviews to make an informed decision.
  • Conversion : The prospect completes the transaction and becomes an actual customer by purchasing.
  • Loyalty : You can turn one-time buyers into repeat customers and brand advocates. 

  It’s called a “funnel” because, similar to the shape of a funnel, the number of potential customers decreases as they progress through the various stages of the sales process — as you can see illustrated below.

  

  Sales funnels can vary across industries and business models, but the general concept remains the same. The goal is to guide potential customers through each funnel stage, addressing their needs and concerns at each step, ultimately leading to a successful conversion. 

  You can create and monitor a custom funnel for your site’s user journey with a web analytics solution like Matomo.

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  The importance of conversion funnel optimisation 

  At the heart of conversion funnel optimisation is the quest for higher conversion rates. 

  Refining the customer journey can increase the chances of turning visitors into customers who return repeatedly.

  Specifically, here’s how conversion funnel optimisation can benefit your business :

  • Increased conversions : Marketers can increase the likelihood of turning website visitors into customers by making the user journey more user-friendly and persuasive.
  • Higher revenue : Improved conversion rates aren’t just numbers on a chart ; they translate to tangible revenue. 
  • Increased ROI (return on investment) : By optimising the conversion funnel, you can get more value from your marketing and sales efforts. 
  • Improved customer satisfaction : When customers find it easy and enjoyable to interact with a website or service, it positively influences their satisfaction and likelihood of returning.
  • Data-driven decision-making : Businesses can make informed decisions on budgets and resources based on user behaviour and performance metrics by analysing and optimising conversion funnels.

  ​​Ultimately, conversion funnel optimisation efforts align the entire funnel with overarching business goals.

  10 ways to optimise your conversion funnel 

  Here are 10 ways to optimise your conversion funnel.

  1. Identify and segment your target audience

  The key to a successful conversion funnel begins with a deep understanding of your target audience. 

  Identifying and segmenting your audience lets you speak directly to their pain points, desires and motivations.

  One effective way to know your audience better is by creating detailed buyer personas. These are fictional representations of your ideal customers based on thorough market research and real data. Dive into demographics and behavioural patterns to craft personas that resonate with your audience.

  

  Note that consumer preferences are not static. They evolve, influenced by trends, technological advancements and shifts in societal values. Staying attuned to these changes is crucial as part of optimising your conversion funnel.

  Thus, you must regularly update your buyer personas and adjust your marketing strategies accordingly.

  2. Create content for every stage of the funnel

  Each funnel stage represents a different mindset and needs for your potential customers. Tailoring your content ensures you deliver the right message at the right time to the right audience. 

  Here’s how to tailor your content to fit prospective customers at every conversion funnel stage.

  Awareness-stage content

  Prospects here are seeking information. Your content should be educational and focused on addressing their pain points. Create blog posts, infographics and videos introducing them to your industry, product or service.

  This video we created at Matomo is a prime example of awareness-stage content, grabbing attention and educating viewers about Matomo.

  Consideration-stage content

  Prospects are evaluating their options. Provide content highlighting your product’s unique selling points, such as case studies, product demonstrations and customer testimonials.

  Here’s how we use a versus landing page at Matomo to persuade prospects at this funnel stage.

  

  Conversion-stage content

  This is the final push. Ensure a smooth transition to conversion with content like promotional offers, limited-time discounts and clear calls to action (CTA).

  Loyalty-stage content

  In this stage, you might express gratitude for the purchase through personalised thank-you emails. Follow up with additional resources, tips or exclusive offers to reinforce a positive post-purchase experience. This also positions your brand as a helpful resource beyond the initial sale.

  Reward customer loyalty with exclusive offers, discounts or membership in a loyalty program.

  3. Capture leads

  Lead magnets are incentives offered to potential customers in exchange for their contact information, typically their email addresses. 

  Examples of lead magnets include :

  • Ebooks and whitepapers : In-depth resources that delve into specific topics of interest to your target audience.
  • Webinars and workshops : Live or recorded sessions that offer valuable insights, training or demonstrations.
  • Free trials and demos : Opportunities for potential customers to experience your product or service firsthand.
  • Checklists and templates : Practical tools that help your audience solve specific challenges.
  • Exclusive offers and discounts : Special promotions are available to those who subscribe or provide their contact information.

  For instance, here’s how HubSpot uses templates as lead magnets.

  

  Similarly, you can incorporate your lead magnets into relevant articles or social media posts, email campaigns and other marketing channels.

  4. Optimise your landing pages

  Understanding how visitors interact with your landing pages is a game-changer. So, the first step in optimising your landing pages is to analyse them.

  Enter Matomo’s heatmaps — the secret weapon in landing page optimisation. They visually represent how users interact with your pages, revealing where they linger, what catches their attention and where they may encounter friction. 

  

  Here are a few landing page elements you should pay attention to :

  • Strategic visual elements : Integrate high-quality images, videos and graphics that support your message and guide visitors through the content.
  • Compelling copy : Develop concise and persuasive copy that emphasises the benefits of your offering, addressing user pain points.
  • Effective CTA : Ensure your CTA is prominently displayed, using compelling language and colours that stand out.
  • Mobile responsiveness : Optimise your landing pages for various devices, especially considering the prevalence of mobile users.
  • Minimal form fields : Reduce friction by keeping form fields to a minimum, requesting only essential information.
  • ​​Leverage social proof : Integrate testimonials, reviews and trust badges to build trust and credibility.
  • A/B testing : Experiment with variations in design, copy and CTAs through A/B testing, allowing data to guide your decisions.

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  5. ​​Use compelling Calls to Action (CTAs)

  Crafting compelling CTAs is an art that involves a careful balance of persuasion, clarity and relevance.

  Here are a few tips you can implement to write CTAs that support your goals :

  • Use language that compels action. Instead of generic phrases like “Click Here,” opt for more persuasive alternatives such as “Unlock Exclusive Access” or “Start Your Free Trial.”
  • Make sure your CTAs are clear and straightforward. Visitors should instantly understand what action you want them to take. 
  • Tailor CTAs to the specific content on the page. Whether it’s a blog post, landing page or email, the CTA should seamlessly connect with the surrounding context.
  • Position your CTAs strategically. They should be prominently displayed and easily noticeable, guiding visitors without intruding.
  • Create a sense of urgency. Encourage immediate action by incorporating language that instils a sense of urgency. Phrases like “Limited Time Offer” or “Act Now” can prompt quicker responses.

  6. Have an active social presence

  Social media platforms are bustling hubs of activity where your target audience spends a significant portion of their online time. Cultivating a social media presence allows you to meet your audience where they are, fostering a direct line of communication.

  Moreover, the integration of shopping features directly into social media platforms transforms them into seamless shopping experiences. Nearly half of Instagram users shop weekly through the platform. 

  Also, the US social commerce sales continue to grow each year and are expected to reach $79.64 billion by 2025.

  

  7. Build a brand community

  Four in five customers consider communities important to how engaged they are with a brand.

  A strong community fosters a sense of belonging and loyalty among members. When customers feel connected to your brand and each other, they are more likely to remain loyal over the long term. 

  Also, satisfied community members often share their positive experiences with others, expanding your brand’s reach without additional marketing efforts.

  For example, Nike’s community for runners is a digital space where individuals share their running journeys, accomplishments and challenges. 

  

  By strategically building and nurturing a community, you not only enhance retention and spur referrals but also create a space where your brand becomes an integral part of your customers’ lives. 

  8. Conduct A/B tests

  A/B testing systematically compares two versions of a webpage, email or other content to determine which performs better.

  Examples of elements to A/B test :

  • CTAs : The language, colour, size and placement of CTAs can significantly impact user engagement. A/B testing allows you to discover which variations prompt the desired actions.
  • Headlines : Crafting compelling headlines is an art. Test different versions to identify which headlines resonate best with your audience, whether they are more drawn to clarity, humour, urgency or curiosity.
  • Images : Test different images to understand your audience’s visual preferences. This could include product images, lifestyle shots or graphics.

  

  With Matomo’s A/B testing feature, you can test various elements to see which is successful in converting visitors or moving them to the next stage of the conversion funnel.

  9. Leverage social proof

  In an era where consumers are inundated with choices, the opinions, reviews and endorsements of others serve as beacons, guiding potential customers through the decision-making process. 

  Simply put — when people see that others have had positive experiences with your brand, it instils trust and confidence.

  

  You can proactively gather social proof and display it prominently across your marketing channels. Here are some examples of social proof you can leverage :

  • Customer reviews : Positive reviews and testimonials from satisfied customers serve as authentic endorsements of your products or services. 
  • Case studies : In-depth case studies that showcase successful collaborations or solutions provided to clients offer a detailed narrative of your brand’s capabilities. These are particularly effective in B2B scenarios or for complex products and services.
  • User-generated content : Encourage customers to share their experiences. This could include photos, videos or posts on social media platforms, providing a dynamic and genuine portrayal of your brand.
  • Influencer endorsements : Collaborating with influencers in your industry or niche can amplify your social proof. When influencers vouch for your products or services, their followers are more likely to take notice.

  10. Measure and analyse performance

  This is a continuous loop of refinement, where you should use analysis and data-driven insights to guide your conversion funnel optimisation efforts.

  Here’s a systematic approach you can take :

  1. Identify the path users take on your site using a feature like Users Flow.
  2. Map the customer journey using a Funnels feature like the one in Matomo. 
  3. Identify the metrics that align with your conversion goals at each stage of the funnel, such as website traffic, conversion rates, click-through rates and customer acquisition costs.
  4. Assess conversion rates at different stages of the funnel. Identify areas with significant drop-offs and investigate factors that might contribute to the decline.
  5. Use heatmaps and session recordings to see first-hand how users interact with your site.
  6. Create an experiment to test and improve a specific area within your funnel using insights from the heatmaps and session recordings.
  7. A/B test, analyse the results to understand which variations performed better. Use this data to refine elements within your funnel.

  See how Concrete CMS 3x their leads with conversion optimisation.

  Conclusion 

  The customer journey is not linear. However, it involves a few specific stages your audience will go through — from first learning about your product or services to considering whether to try it. The goal is to turn them into happy and loyal customers.

  In this article, we went over strategies and practical tips you can use to guide customers through the conversion funnel. From segmenting your audience to capturing leads, optimising landing pages and running A/B tests, there are steps you can take to ensure your audience will move to the next stage.

  And of course, you have to continuously measure and analyse your performance. That’s how you know whether you’re heading in the right direction and, if not, where to correct your course. 

  For that, you need a robust web analytics solution with conversion optimisation features. Try Matomo free for 21 days and start optimising your conversion funnel—no credit card required. 

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• 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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• FFMPEG = I tried resizing a video, but got different resolution than I wanted [closed]

  10 janvier 2024, par wakanasakai

  I downloaded a video that had some black bars (left & right), so I used the following command in FFmpeg to make various changes to it. I tested it on a 10 second clip to see what the result would look like.

  


  -ss 00:04:44 -to 00:04:54 -vf "crop=1870:20:20:0","scale=640x480:flags=lanczos","eq=gamma=1.5:saturation=1.3:contrast=1.2"

  


  The original video is an mp4, with a resolution of 1920 x 1080. Besides trying to crop it & adjust the gamma, saturation, & contrast, I also tried to resize it to 640 x 480. Instead, it's resulting resolution is 44880 x 480 ! I have a link to it for anybody who wants to examine it directly. (It's only 487 kb.)
text

  


  I've tried using FFmpeg before, & it never did anything so insane. (It cropped it, & adjusted the gamma a saturation (I didn't test the contrast until THIS time), but it did not resize it at all.)

  


  Here is FFmpeg's log file for it. Guesses as to the cause of the insane result, & advice on how to achieve the DESIRED result (in 1 pass, if possible) are requested.

  


  ffmpeg -hwaccel auto -y -i "/storage/emulated/0/bluetooth/Barbie & the Rockers=1080-Out of this world (1987).mp4" -ss 00:04:44 -to 00:04:54 -vf "crop=1870:20:20:0","scale=640x480:flags=lanczos","eq=gamma=1.5:saturation=1.3:contrast=1.2" "/storage/emulated/0/Movies/Barbie.mp4"

ffmpeg version 6.0 Copyright (c) 2000-2023 the FFmpeg developers
  built with gcc 4.9.x (GCC) 20150123 (prerelease)
  configuration: --enable-version3 --enable-gpl --enable-nonfree --disable-indev=v4l2 --enable-libmp3lame --enable-libx264 --enable-libx265 --enable-libvpx --enable-libvorbis --enable-libtheora --enable-libopus --enable-libfdk-aac --enable-libfreetype --enable-libass --enable-libfribidi --enable-fontconfig --enable-pthreads --enable-libxvid --enable-filters --enable-openssl --enable-librtmp --disable-protocol='udp,udplite' --enable-libopencore-amrwb --enable-libopencore-amrnb --enable-libvo-amrwbenc --enable-libspeex --enable-libsoxr --enable-libwebp --enable-libxml2 --enable-libopenh264 --enable-jni --prefix=/home/silentlexx/AndroidstudioProjects/ffmpeg/ffmpeg/build/arm-api18-r13b --sysroot=/home/silentlexx/Android/android-ndk-r13b/platforms/android-18/arch-arm --arch=arm --disable-shared --enable-static --enable-pic --enable-ffmpeg --disable-ffplay --disable-ffprobe --disable-ffnvcodec --disable-avdevice --disable-debug --disable-doc --disable-htmlpages --disable-manpages --disable-podpages --disable-txtpages --disable-symver --cross-prefix=/home/silentlexx/Android/android-ndk-r13b/toolchains/arm-linux-androideabi-4.9/prebuilt/linux-x86_64/bin/arm-linux-androideabi- --target-os=android --enable-cross-compile --pkg-config-flags=--static --extra-libs='-lgnustl_static -lm -lpng -l:libz.so -lpthread' --enable-asm --enable-neon --enable-small
  libavutil      58.  2.100 / 58.  2.100
  libavcodec     60.  3.100 / 60.  3.100
  libavformat    60.  3.100 / 60.  3.100
  libavfilter     9.  3.100 /  9.  3.100
  libswscale      7.  1.100 /  7.  1.100
  libswresample   4. 10.100 /  4. 10.100
  libpostproc    57.  1.100 / 57.  1.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/storage/emulated/0/bluetooth/Barbie & the Rockers=1080-Out of this world (1987).mp4':
  Metadata:
    major_brand     : mp42
    minor_version   : 512
    compatible_brands: mp41isomiso2
    creation_time   : 2024-01-04T01:46:07.000000Z
  Duration: 00:45:33.10, start: 0.000000, bitrate: 3404 kb/s
  Stream #0:0[0x1](und): Video: h264 (avc1 / 0x31637661), yuv420p(tv, bt709, progressive), 1920x1080 [SAR 1:1 DAR 16:9], 3272 kb/s, 30 fps, 30 tbr, 15360 tbn (default)
    Metadata:
      creation_time   : 2023-06-25T13:25:03.000000Z
      vendor_id       : [0][0][0][0]
  Stream #0:1[0x2](eng): Audio: aac (mp4a / 0x6134706D), 44100 Hz, stereo, fltp, 128 kb/s (default)
    Metadata:
      creation_time   : 2023-06-25T13:25:03.000000Z
      vendor_id       : [0][0][0][0]
Stream mapping:
  Stream #0:0 -> #0:0 (h264 (native) -> h264 (libx264))
  Stream #0:1 -> #0:1 (aac (native) -> aac (native))
Press [q] to stop, [?] for help
[libx264 @ 0xf38cd180] using SAR=561/8
[libx264 @ 0xf38cd180] using cpu capabilities: ARMv6 NEON
[libx264 @ 0xf38cd180] profile High, level 3.0, 4:2:0, 8-bit
[libx264 @ 0xf38cd180] 264 - core 158 r2984 3759fcb - H.264/MPEG-4 AVC codec - Copyleft 2003-2019 - http://www.videolan.org/x264.html - options: cabac=1 ref=3 deblock=1:0:0 analyse=0x3:0x113 me=hex subme=7 psy=1 psy_rd=1.00:0.00 mixed_ref=1 me_range=16 chroma_me=1 trellis=1 8x8dct=1 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=-2 threads=12 lookahead_threads=2 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=3 b_pyramid=2 b_adapt=1 b_bias=0 direct=1 weightb=1 open_gop=0 weightp=2 keyint=250 keyint_min=25 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=23.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
Output #0, mp4, to '/storage/emulated/0/Movies/Barbie.mp4':
  Metadata:
    major_brand     : mp42
    minor_version   : 512
    compatible_brands: mp41isomiso2
    encoder         : Lavf60.3.100
  Stream #0:0(und): Video: h264 (avc1 / 0x31637661), yuv420p(tv, bt709, progressive), 640x480 [SAR 561:8 DAR 187:2], q=2-31, 30 fps, 15360 tbn (default)
    Metadata:
      creation_time   : 2023-06-25T13:25:03.000000Z
      vendor_id       : [0][0][0][0]
      encoder         : Lavc60.3.100 libx264
    Side data:
      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A
  Stream #0:1(eng): Audio: aac (mp4a / 0x6134706D), 44100 Hz, stereo, fltp, 128 kb/s (default)
    Metadata:
      creation_time   : 2023-06-25T13:25:03.000000Z
      vendor_id       : [0][0][0][0]
      encoder         : Lavc60.3.100 aac
frame=    0 fps=0.0 q=0.0 size=       0kB time=-577014:32:22.77 bitrate=  -0.0kbits/s speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=00:00:00.16 bitrate=   2.4kbits/s speed=0.00197x    
frame=    0 fps=0.0 q=0.0 size=       0kB time=00:00:00.71 bitrate=   0.5kbits/s speed=0.00867x    
frame=   13 fps=0.2 q=29.0 size=       0kB time=00:00:01.48 bitrate=   0.3kbits/s speed=0.0178x    
frame=   45 fps=0.5 q=29.0 size=       0kB time=00:00:02.55 bitrate=   0.2kbits/s speed=0.0304x    
frame=   78 fps=0.9 q=29.0 size=       0kB time=00:00:03.66 bitrate=   0.1kbits/s speed=0.0434x    
frame=  114 fps=1.3 q=29.0 size=       0kB time=00:00:04.85 bitrate=   0.1kbits/s speed=0.057x    
frame=  146 fps=1.7 q=29.0 size=       0kB time=00:00:05.92 bitrate=   0.1kbits/s speed=0.0692x    
frame=  178 fps=2.1 q=29.0 size=       0kB time=00:00:07.03 bitrate=   0.1kbits/s speed=0.0817x    
frame=  209 fps=2.4 q=29.0 size=     256kB time=00:00:08.03 bitrate= 261.1kbits/s speed=0.0928x    
frame=  240 fps=2.8 q=29.0 size=     256kB time=00:00:09.07 bitrate= 231.0kbits/s speed=0.104x    
frame=  300 fps=3.4 q=-1.0 Lsize=     445kB time=00:00:09.98 bitrate= 365.2kbits/s speed=0.114x    
video:275kB audio:159kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 2.692692%
[libx264 @ 0xf38cd180] frame I:10    Avg QP:20.34  size:  2434
[libx264 @ 0xf38cd180] frame P:129   Avg QP:21.89  size:  1292
[libx264 @ 0xf38cd180] frame B:161   Avg QP:21.69  size:   555
[libx264 @ 0xf38cd180] consecutive B-frames: 20.0% 18.7% 20.0% 41.3%
[libx264 @ 0xf38cd180] mb I  I16..4: 30.2% 66.5%  3.2%
[libx264 @ 0xf38cd180] mb P  I16..4: 14.3% 17.7%  0.2%  P16..4: 12.7%  2.7%  0.4%  0.0%  0.0%    skip:52.1%
[libx264 @ 0xf38cd180] mb B  I16..4:  2.1%  1.1%  0.0%  B16..8: 21.9%  1.7%  0.0%  direct: 1.5%  skip:71.6%  L0:46.0% L1:53.0% BI: 1.0%
[libx264 @ 0xf38cd180] 8x8 transform intra:54.9% inter:98.2%
[libx264 @ 0xf38cd180] coded y,uvDC,uvAC intra: 10.3% 14.9% 1.5% inter: 2.2% 5.4% 0.0%
[libx264 @ 0xf38cd180] i16 v,h,dc,p: 93%  2%  2%  4%
[libx264 @ 0xf38cd180] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 69%  1% 28%  0%  0%  1%  0%  0%  0%
[libx264 @ 0xf38cd180] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 76%  3% 17%  1%  1%  2%  0%  1%  0%
[libx264 @ 0xf38cd180] i8c dc,h,v,p: 45%  2% 53%  1%
[libx264 @ 0xf38cd180] Weighted P-Frames: Y:0.8% UV:0.8%
[libx264 @ 0xf38cd180] ref P L0: 57.0%  8.7% 24.0% 10.4%
[libx264 @ 0xf38cd180] ref B L0: 79.7% 17.3%  3.0%
[libx264 @ 0xf38cd180] ref B L1: 95.6%  4.4%
[libx264 @ 0xf38cd180] kb/s:224.32
[aac @ 0xf38cd880] Qavg: 457.489