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• Web Analytics : The Quick Start Guide

  25 janvier 2024, par Erin

  You’ve spent ages carefully designing your website, crafting copy to encourage as many users as possible to purchase your product. 

  But they aren’t. And you don’t know why. 

  The good news is you don’t have to remain in the dark. Collecting and analysing web analytics lets you understand how your users behave on your site and why they aren’t converting. 

  But before you can do that, you need to know what those metrics and KPIs mean. That’s why this article is taking things back to basics. Below, we’ll show you which metrics to track, what they mean and how to choose the best web analytics platform. 

  What is web analytics ?

  Web analytics is the process of collecting, analysing and reporting website data to understand how users behave on your website. Web analytics platforms like Matomo collect this data by adding a code line to every site page. 

  Why is it important to track web analytics ?

  There are plenty of reasons you should start tracking web analytics, including the following :

  

  Analyse user behaviour

  Being able to analyse user behaviour is the most important reason to track website analytics. After all, you can’t improve your website’s conversion rate if you don’t know what users do on your site.

  A web analytics platform can show you how users move around your site, the links they click on and the forms they fill in. 

  Improve site experience

  Web analytics is a fantastic way to identify issues and find areas where your site could improve. You could look at your site’s exit pages, for example, and see why so many users leave your site when viewing one of these pages and what you can do to fix it.

  It can also teach you about your user’s preferences so you can improve the user experience in the future. Maybe they always click a certain type of button or prefer one page’s design over another. Whatever the case, you can use the data to make your site more user-friendly and increase conversions.

  Boost marketing efforts

  Web analytics is one of the best ways to understand your marketing efforts and learn how to improve them.

  A good platform can collect valuable data about your marketing campaigns, including :

  • Where users came from
  • What actions these users take on your site
  • Which traffic sources create the most conversions

  This information can help you decide which marketing campaigns send the best users to your site and generate the highest ROI. 

  Make informed decisions

  Ultimately, web analytics simplifies decision-making for your website and marketing efforts by relying on concrete data instead of guesswork.

  Rather than wonder why users aren’t adding products to their shopping cart or signing up for your newsletter, you can analyse how they behave and use that information to hypothesise how you can improve conversions. Web analytics will even give you the data to confirm whether you were right or wrong. 

  What are the key metrics you should track ?

  Getting your head around web analytics means knowing the most important metrics to track. Below are seven key metrics and how to track them using Matomo. 

  Traffic

  Traffic is the number of people visiting your website over a period of time. It is the lifeblood of your website since the more visits your site receives, the more revenue it stands to generate.

  However, simply having a high volume of visitors does not guarantee substantial revenue. To maximise your success, focus on attracting your ideal customers and generating quality traffic from those who are most likely to engage with your offerings.

  Ideally, you should be seeing an upward trend in traffic over time though. The longer your website has been published and the more quality and targeted content you create, the more traffic you should receive. 

  Matomo offers multiple ways to check your website’s traffic :

  • Visits log report
  • Real-time visitor map
  • Visits in real-time report

  The visits log report in Matomo is perfect if you want a granular view of your visitors.

  

  It shows you each user session and get a detailed picture of each user, including :

  • Their geographic location
  • The number of actions they took
  • How they found your site
  • The length of time they stayed
  • Their device type
  • What browser they are using
  • The keyword they used to find your site

  Traffic sources

  Traffic sources show how users access your website. They can enter via a range of traffic sources, including search engines, email and direct visits, for instance.

  Matomo has five default traffic source types :

  • Search engine – visitors from search platforms (like Google, Bing, etc.)
  • Direct traffic – individuals who directly type your website’s URL into their browser or have it bookmarked, bypassing search engines or external links
  • Websites – visits from other external sites
  • Campaigns – traffic resulting from specific marketing initiatives (like a newsletter or ad campaign, for instance)
  • Social networks  – visitors who access your website through various social media platforms (such as Facebook, LinkedIn, Instagram. etc.)

  But each of these can be broken into more granular sources. Take organic traffic from search engines, for example :

  

  Matomo tracks visits from each search engine, showing you how many visits you had in total, how many actions those visitors took, and the average amount of time those visitors spent on your site. 

  You can even integrate Google, Bing and Yahoo search consoles to monitor keyword performance and enhance your search engine optimisation efforts.

  Pageviews

  Whenever a browser loads a page, your web analytics tool records a pageview. This term, pageview, represents the count of unique times a page on your website is loaded.

  You can track pageviews in Matomo by opening the Pages tab in the Behaviour section of the main navigation. 

  

  You can quickly see your site’s most visited pages in this report in Matomo. 

  Be careful of deriving too much meaning from pageviews. Just because a page has lots of views, doesn’t necessarily mean it’s quality or valuable. There are a couple of reasons for this. First, the page might be confusing, so users have to keep revisiting it to understand the content. Second, it could be the default page most visitors land on when they enter your site, like the homepage. 

  While pageviews offer insights, it’s important to dig deeper into user behaviour and other metrics to truly gauge a page’s importance and impact.

  Average time on page

  Time on page is the amount of time users spend on the page on average. You can see average time on page in Matomo’s page analytics report.

  A low time on page score isn’t necessarily a bad thing. Users will naturally spend less time on gateway pages and checkout pages. A short time spent on checkout pages, especially if users are successfully completing their transactions, indicates that the checkout process is easy and seamless.

  Conversely, a longer time on blog posts is a positive indicator. It suggests that readers are genuinely engaged with the content.

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  Returning visitors

  Returning visitors measures the number of people who visit your site more than once. It can be expressed as a number or a percentage. 

  While some analytics tools only show returning visitors as a percentage, Matomo lets you learn more about each of them in the Visitor profile report. 

  

  This report offers a full summary of a user’s previous actions, including :

  • How many times they’ve visited your site
  • The pages they viewed on each visit
  • Where they visited from
  • The devices they used
  • How quickly pages loaded

  When people keep coming back to a website, it’s usually a positive sign and means they like the service, content or products. But, it depends on the type of website. If it’s the kind of site where people make one-off purchases, the focus might not be on getting visitors to return. For a site like this, a high number of returning visitors could indicate that the website is confusing or difficult to use. 

  It’s all about the context – different websites have different goals, and it’s important to keep this in mind when analysing your site.

  Conversions

  A conversion is when a user takes a desired action on your website. This could be :

  • Making a purchase
  • Subscribing to your newsletter
  • Signing up for a webinar

  You can track virtually any action as a conversion in Matomo by setting goals and analysing the goals report.

  

  As you can see in the screenshot above, Matomo shows your conversions plotted over time. You can also see your conversion rate to get a complete picture and assign a value to each conversion to calculate how much revenue each conversion generates. 

  Bounce rate

  A visitor bounces when they leave your website without taking an action or visiting another page. 

  Typically, you want bounce rate to be low because it means people are engaged with your site and more likely to convert. However, in some cases, a high bounce rate isn’t necessarily bad. It might mean that visitors found what they needed on the first page and didn’t feel the need to look further. 

  The impact of bounce rate depends on your website’s purpose and goals.

  You can view your website’s bounce rate using Matomo’s page analytics report — the same report that shows pageviews.

  Try Matomo for Free

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

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  Web analytics best practices

  You should follow several best practices to get the most from website analytics data. 

  Choose metrics that align with your goals

  Only some metrics your analytics platform tracks will be relevant to your business. So don’t waste time analysing all of them.

  Instead, focus on the ones that matter most to your business. A marketer for an e-commerce store, for example, might focus on conversion-related metrics like conversion rate and total number of transactions. They might also want to look at campaign-related metrics, like traffic sources and bounce rates, so they can optimise paid ad campaigns accordingly. 

  A marketer looking to improve their site’s SEO, on the other hand, will want to track SEO web analytics like bounce rate and broken links.

  Add context to your data

  Don’t take your data at face value. There could be dozens of factors that impact how visitors access and use your site — many of which are outside your control. 

  For example, you may think an update to your site has sent your conversions crashing when, in reality, a Google algorithm update has negatively impacted your search traffic.

  Adding annotations within Matomo can provide invaluable context to your data. These annotations can be used to highlight specific events, changes or external factors that might influence your website metrics.

  

  By documenting significant occurrences, such as website updates, marketing campaigns or algorithm changes, you create a timeline that helps explain fluctuations in your data.

  Go further with advanced web analytics features

  It’s clear that a web analytics platform is a necessary tool to understand your website’s performance.

  However, if you want greater confidence in decision-making, quicker insights and better use of budget and resources, you need an advanced solution with behavioural analytics features like heatmaps, A/B testing and session recordings. 

  Most web analytics solutions don’t offer these advanced features, but Matomo does, so we’ll be showcasing Matomo’s behavioural analytics features.

  Now, if you don’t have a Matomo account, you can try it free for 21-days to see if it’s the right tool for you.

  

  A heatmap, like the example above, makes it easy to discover where your users pay attention, which part of your site they have problems with, and how they convert. It adds a layer of qualitative data to the facts offered by your web analytics tool.

  Similarly, session recordings will offer you real-time playbacks of user interactions, helping you understand their navigation patterns, identify pain points and gain insights into the user experience.

  Then you can run experiments bu using A/B testing to compare different versions of your website or specific elements, allowing you to make informed decisions based on actual user preferences and behaviour. For instance, you can compare different headlines, images, page layouts or call-to-action buttons to see which resonates better with your audience. 

  Together, these advanced features will give you the confidence to optimise your website, improve user satisfaction and make data-driven decisions that positively impact your business.

  Try Matomo for Free

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

  Start for free

  No credit card required

  How to choose a web analytics tool

  A web analytics tool is the best way to track the above metrics. Choose the best one for your company by following the steps below. 

  Look for the right features

  Most popular web analytics platforms, like Google Analytics, will offer the same core features like tracking website traffic, monitoring conversions and generating reports. 

  But it’s the added features that set great tools apart. Do you need specific tools to measure the performance of your e-commerce store, for example ? What about paid ad performance, A/B testing or form analytics ?

  By understanding exactly what you need from an analytics platform, you can make an informed choice. 

  Think about data accuracy

  Data accuracy is one of the biggest issues with analytics tools. Many users block cookies or opt out of tracking, making it difficult to get a clear picture of user behaviour — and meaning that you have to think about how your user data will be collected with your chosen platform.

  Google Analytics, for instance, uses data sampling to make assumptions about traffic levels rather than relying on accurate data. This can lead to inaccurate reports and false conclusions. 

  It’s why Matomo doesn’t use data sampling and provides 100% accurate data. 

  Understand how you’ll deal with data privacy

  Data privacy is another big concern for analytics users. Several major analytics platforms aren’t compatible with regional data privacy laws like GDPR, which can impact your ability to collect data in these regions. 

  It’s why many companies trust privacy-focused analytics tools that abide by regulations without impacting your ability to collect data. Matomo is a market leader in this respect and is one of the few web analytics tools that the Centre for Data Privacy Protection in France has said is exempt from tracking consent requirements.

  Many government agencies across Europe, Asia, Africa and North America, including organisations like the United Nations and European Commission, rely on Matomo for web analytics.

  Conclusion

  Web analytics is a powerful tool that helps you better understand your users, improve your site’s performance and boost your marketing efforts. 

  If you want a platform that offers advanced features, 100% accurate data and protects your users’ privacy, then look no further than Matomo. 

  Try Matomo free for 21 days, no credit card required. 

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• Marketing Touchpoints : Examples, KPIs, and Best Practices

  11 mars 2024, par Erin

  The customer journey is rarely straightforward. Rather, each stage comprises numerous points of contact with your brand, known as marketing touchpoints. And each touchpoint is equally important to the customer experience. 

  This article will explore marketing touchpoints in detail, including how to analyse them with attribution models and which KPIs to track. It will also share tips on incorporating these touchpoints into your marketing strategy. 

  What are marketing touchpoints ? 

  Marketing touchpoints are the interactions that take place between brands and customers throughout the latter’s journey, either online or in person. 

  

  By understanding how customers interact with your brand before, during and after a purchase, you can identify the channels that contribute to starting, driving and closing buyer journeys. Not only that, but you’ll also learn how to optimise the customer experience. This can also help you : 

  • Promote customer loyalty through increased customer satisfaction
  • Improve your brand reputation and foster a more positive perception of your brand, supported by social proof 
  • Build brand awareness among prospective customers 
  • Reconnect with current customers to drive repeat business

  According to a 2023 survey, social media and video-sharing platforms are the leading digital touchpoints among US consumers.

  

  With the customer journey divided into three stages — awareness, consideration, and decision — we can group these interactions into three touchpoint segments, depending on whether they occur before, during or after a purchase. 

  Touchpoints before a purchase

  Touchpoints before a purchase are those initial interactions between potential customers and brands that occur during the awareness stage — before they’ve made a purchase decision. 

  Here are some key touchpoints at the pre-purchase stage : 

  • Customer reviews, forums, and testimonials 
  • Social media posts
  • Online ads 
  • Company events and product demos
  • Other digital touchpoints, like video content, blog posts, or infographics
  • Peer referral 

  In PwC’s 2024 Global Consumer Insights Pulse Survey, 54% of consumers listed search engines as their primary source of pre-purchase information, followed by Amazon (35%) and retailer websites (33%). 

  Here are the survey’s findings in Western Europe, specifically : 

  

  Social channels are another major pre-purchase touchpoint ; 25% of social media users aged 18 to 44 have made a purchase through a social media app over the past three months. 

  Touchpoints during a purchase

  Touchpoints during a purchase occur when the prospective customer has made their purchase decision. It’s the beginning of a (hopefully) lasting relationship with them. 

  It’s important to involve both marketing and sales teams here — and to keep track of conversion metrics. 

  Here are the main touchpoints at this stage : 

  • Company website pages 
  • Product pages and catalogues 
  • Communication between customers and sales reps 
  • Product packaging and labelling 
  • Point-of-sale (POS) — the final touchpoint the prospective customer will reach before making the final purchasing decision 

  Touchpoints after a purchase

  You can use touchpoints after a purchase to maintain a positive relationship and keep current customers engaged. Examples of touchpoints that contribute to a good post-purchase experience for the customer include the following : 

  • Thank-you emails 
  • Email newsletters 
  • Customer satisfaction surveys 
  • Cross-selling emails 
  • Renewal options 
  • Customer loyalty programs

  Email marketing remains significant across all touchpoint segments, with 44% of CMOs agreeing that it’s essential to their marketing strategy — and it also plays a particularly important role in the post-purchase experience. For 61.1% of marketing teams, email open rates are higher than 20%.

  

  Sixty-nine percent of consumers say they’ve stopped doing business with a brand following a bad experience, so the importance of customer service touchpoints shouldn’t be overlooked. Live chat, chatbots, self-service resources, and customer service teams are integral to the post-purchase experience.

  Attribution models : Assigning value to marketing touchpoints 

  Determining the most effective touchpoints — those that directly contribute to conversions — is a process known as marketing attribution. The goal here is to identify the specific channels and points of contact with prospective customers that result in revenue for the company.

  

  You can use these insights to understand — and maximise — marketing return on investment (ROI). Otherwise, you risk allocating your budget to the wrong channels. 

  It’s possible to group attribution models into two categories — single-touch and multi-touch — depending on whether you assign value to one or more contributing touchpoints.

  Single-touch attribution models, where you’re giving credit for the conversion to a single touchpoint, include the following :

  • First-touch attribution : This assigns credit for the conversion to the first interaction a customer had with a brand ; however, it fails to consider lower-funnel touchpoints.
  • Last-click attribution : This focuses only on bottom-of-funnel marketing and credits the last interaction the customer had with a brand before completing a purchase.
  • Last non-direct : Credits the touchpoint immediately preceding a direct touchpoint with all the credit.

  Multi-touch attribution models are more complex and distribute the credit for conversion across multiple relevant touchpoints throughout the customer journey :

  • Linear attribution : The simplest multi-touch attribution model assigns equal values to all contributing touchpoints.
  • Position-based or U-shaped attribution : This assigns the greatest value to the first and last touchpoint — with 40% of the conversion credit each — and then divides the remaining 20% across all the other touchpoints.
  • Time-decay attribution : This model assigns the most credit to the customer’s most recent interactions with a brand, assuming that the touchpoints that occur later in the journey have a bigger impact on the conversion.

  Consider the following when choosing the most appropriate attribution model for your business :

  • The length of your typical sales cycle
  • Your marketing goals : increasing awareness, lead generation, driving revenue, etc.
  • How many stages and touchpoints make up your sales funnel

  Sometimes, it even makes sense to measure marketing performance using more than one attribution model.

  With the sheer volume of data that’s constantly generated across numerous online touchpoints, from your website to social media channels, it’s practically impossible to collect and analyse it manually.

  You’ll need an advanced web analytics platform to identify key touchpoints and assign value to them.

  Matomo’s Marketing Attribution feature can accurately measure the performance of different touchpoints to ensure that you’re allocating resources to the right channels. This is done in a compliant manner, without the need of data sampling or requiring cookie consent screens (excluding in Germany and the UK), ensuring both accuracy and privacy compliance.

  Try Matomo for Free

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

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  Customer journey KPIs for measuring marketing campaign performance 

  Measuring the impact of different touchpoints on marketing campaign performance can help you understand how customer interactions drive conversions — and how to optimise your future efforts. 

  

  Clearly, this is not a one-time effort. You should continuously reevaluate the crucial touchpoints that drive the most engagement at different stages of the customer journey. 

  Web analytics platforms can provide valuable insights into ever-changing consumer behaviours and trends and help you make informed decisions. 

  At the moment, Google is the most popular solution in the web analytics industry, with a combined market share of more than 70%. 

  However, if privacy, data accuracy, and GDPR compliance are a priority for you, Matomo is an alternative worth considering. 

  Try Matomo for Free

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

  Start for free

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  KPIs to track before a purchase 

  During the pre-purchase stage, focus on the KPIs that measure the effectiveness of marketing activities across various online touchpoints — landing pages, email campaigns, social channels and ad placement on SERPs, for instance. 

  KPIs to track during the consideration stage include the following : 

  • Cost-per-click (CPC) : The CPC, the total cost of paid online advertising divided by the number of clicks those ads get, indicates whether you’re getting a good ROI. In the UK, the average CPC for search advertising is $1.22. Globally, it averages $0.62.
  • Engagement rate : The engagement rate, which is the total number of interactions divided by the number of followers, is useful for measuring the performance of social media touchpoints. Customer engagement also applies to other channels, like tracking average time on-page, form conversions, bounce rates, and other website interactions. 
  • Click-through rate (CTR) : The CTR — or the number of clicks your ads receive compared to the number of times they’re shown — helps you measure the performance of CTAs, email newsletters and pay-per-click (PPC) advertising.

  KPIs to track during a purchase 

  As a potential customer moves further down the sales funnel and reaches the decision stage, where they’re ready to make the choice to purchase, you should be tracking the following : 

  • Conversion rate : This is the percentage of leads that convert into customers by completing the desired action relative to the total number of website visitors. It shows you whether you’re targeting the right people and providing a frictionless checkout experience.
  • Sales revenue : This refers to the quantity of products sold multiplied by the product’s price. It helps you track the company’s ability to generate profit. 
  • Cost per conversion : This KPI is the total cost of online advertising in relation to the number of conversions. It measures the effectiveness of different marketing channels and the costs of converting prospective customers into buyers. It also forecasts future ad spend.

  KPIs to track after purchase 

  At the post-purchase stage, your priority should be gathering feedback : 

  Customer feedback surveys are great for collecting insights into customers’ post-purchase experience, opinions about your brand, products and services, and needs and expectations. 

  In addition to measuring customer satisfaction, these insights can help you identify points of friction, forecast future growth and revenue and spot customers at risk of churning. 

  Focus on the following customer satisfaction and retention metrics : 

  • Customer Satisfaction Score (CSAT) : This metric, which is gathered through customer satisfaction surveys, helps you gauge satisfaction levels. After all, 77% of consumers consider great customer service an important driver of brand loyalty.
  • Net Promoter Score (NPS) : Based on single-question customer surveys, NPS indicates how likely a customer is to recommend your business.
  • Customer Lifetime Value (CLV) : The CLV is the profit you can expect to generate from one customer throughout their relationship with your company. 
  • Customer Health Score (CHS) : This score can assess how “healthy” the customer’s relationship with your brand is and identify at-risk customers.

  Marketing touchpoints : Tips and best practices 

  Customer experience is more important today than ever. 

  

  Salesforce’s 2022 State of the Connected Consumer report indicated that, for 88% of customers, the experience the brand provides is just as important as the product itself. 

  Here’s how you can build your customer touchpoint strategy and use effective touchpoints to improve customer satisfaction, build a loyal customer base, deliver better digital experiences and drive growth : 

  Understand the customer’s end-to-end experience 

  The typical customer’s journey follows a non-linear path of individual experiences that shape their awareness and brand preference. 

  Seventy-three percent of customers expect brands to understand their needs. So, personalising each interaction and delivering targeted content at different touchpoint segments — supported by customer segmentation and tools like Matomo — should be a priority. 

  Try to put yourself in the prospective customer’s shoes and understand their motivation and needs, focusing on their end-to-end experience rather than individual interactions. 

  Create a customer journey map 

  Once you understand how prospective customers interact with your brand, it becomes easier to map their journey from the pre-purchase stage to the actual purchase and beyond. 

  By creating these visual “roadmaps,” you make sure that you’re delivering the right content on the right channels at the right times and to the right audience — the key to successful marketing.

  Identify best-performing digital touchpoints 

  You can use insights from marketing attribution to pinpoint areas that are performing well. 

  By analysing the data provided by Matomo’s Marketing Attribution feature, you can determine which digital touchpoints are driving the most conversions or engagement, allowing you to focus your resources on optimising these channels for even greater success. 

  This targeted approach helps maximise the effectiveness of your marketing efforts and ensures a higher return on investment.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Discover key marketing touchpoints with Matomo 

  The customer’s journey rarely follows a direct route. If you hope to reach more customers and improve their experience, you’ll need to identify and manage individual marketing touchpoints every step of the way.

  While this process looks different for every business, it’s important to remember that your customers’ experience begins long before they interact with your brand for the first time — and carries on long after they complete the purchase. 

  In order to find these touchpoints and measure their effectiveness across multiple marketing channels, you’ll have to rely on accurate data — and a powerful web analytics tool like Matomo can provide those valuable marketing insights. 

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

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• FFmpeg stops encoding after x minutes when using Mjpeg

  31 janvier 2018, par Rune Aspvik

  I’m using ffmpeg in a node application with this command :

  ffmpeg -seekable 0 -i http://127.0.0.1:8100/Mjpeg/1?authToken=xxx -video_size 1280x720 -r 30 -pix_fmt yuv420p -y D:\Video\pflyers\test.mp4

  The encoding would stop after 28:53 every time. After some reading I figured I had to spawn the child instead of exec because of the large sterr output.

  Before doing that I wanted to see if that was in fact the issue so I tried doing :

  -nostats -hide_banner -loglevel panic

  to avoid the large output to sterr. FFmpeg still stopped after 28:53. Further I tried to write the sterr to log.txt instead of using the above code. I did so adding this to the end :

  2> log.txt

  Still it would stop at 28:53.

  Finally I tried running the command in cmd.exe resulting in the encoding stopping at 29:14.

  What I realized comparing the outputs from ffmpeg run from node and run from cmd.exe was that the encoding stopped when the log.txt reached 388kB.

  How can I fix this ?

  Here’s the full output :

  C:\Users\VossVind>ffmpeg -seekable 0 -i http://127.0.0.1:8100/Mjpeg/1?authToken=xxx -video_size 1280x720 -r 30 -pix_fmt yuv420p -y D:\Video\pflyers\test.mp4
  
  ffmpeg version 3.4 Copyright (c) 2000-2017 the FFmpeg developers
  
    built with gcc 7.2.0 (GCC)
  
    configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-bzlib --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvidstab --enable-libvorbis --enable-cuda --enable-cuvid --enable-d3d11va --enable-nvenc --enable-dxva2 --enable-avisynth --enable-libmfx
  
    libavutil      55. 78.100 / 55. 78.100
  
    libavcodec     57.107.100 / 57.107.100
  
    libavformat    57. 83.100 / 57. 83.100
  
    libavdevice    57. 10.100 / 57. 10.100
  
    libavfilter     6.107.100 /  6.107.100
  
    libswscale      4.  8.100 /  4.  8.100
  
    libswresample   2.  9.100 /  2.  9.100
  
    libpostproc    54.  7.100 / 54.  7.100
  
  Input #0, mpjpeg, from 'http://127.0.0.1:8100/Mjpeg/1?authToken=xxx':
  
    Duration: N/A, bitrate: N/A
  
      Stream #0:0: Video: mjpeg, yuvj420p(pc, bt470bg/unknown/unknown), 1280x720 [SAR 96:96 DAR 16:9], 25 tbr, 25 tbn, 25 tbc
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (mjpeg (native) -> h264 (libx264))
  
  Press [q] to stop, [?] for help
  
  [swscaler @ 0000019639b27fc0] deprecated pixel format used, make sure you did set range correctly
  
  [libx264 @ 0000019639944040] using SAR=1/1
  
  [libx264 @ 0000019639944040] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2
  
  [libx264 @ 0000019639944040] profile High, level 3.1
  
  [libx264 @ 0000019639944040] 264 - core 152 r2851 ba24899 - H.264/MPEG-4 AVC codec - Copyleft 2003-2017 - 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=18 lookahead_threads=3 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 'D:\Video\pflyers\test.mp4':
  
    Metadata:
  
      encoder         : Lavf57.83.100
  
      Stream #0:0: Video: h264 (libx264) (avc1 / 0x31637661), yuv420p, 1280x720 [SAR 1:1 DAR 16:9], q=-1--1, 30 fps, 15360 tbn, 30 tbc
  
      Metadata:
  
        encoder         : Lavc57.107.100 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: -1
  
  More than 1000 frames duplicated  114432kB time=00:03:17.80 bitrate=4739.3kbits/s dup=1000 drop=0 speed=0.95x
  
  frame=52544 fps= 29 q=-1.0 Lsize= 1050136kB time=00:29:11.36 bitrate=4912.0kbits/s dup=8757 drop=0 speed=0.972x
  
  video:1049508kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 0.059803%
  
  [libx264 @ 0000019639944040] frame I:261   Avg QP:20.59  size: 51862
  
  [libx264 @ 0000019639944040] frame P:15400 Avg QP:23.72  size: 33007
  
  [libx264 @ 0000019639944040] frame B:36883 Avg QP:24.55  size: 14989
  
  [libx264 @ 0000019639944040] consecutive B-frames:  0.9% 15.8%  2.5% 80.8%
  
  [libx264 @ 0000019639944040] mb I  I16..4: 17.1% 82.1%  0.8%
  
  [libx264 @ 0000019639944040] mb P  I16..4:  4.3% 48.4%  0.2%  P16..4: 12.3%  7.5%  4.8%  0.0%  0.0%    skip:22.5%
  
  [libx264 @ 0000019639944040] mb B  I16..4:  2.7% 15.6%  0.0%  B16..8: 22.3%  7.0%  1.8%  direct: 3.8%  skip:46.8%  L0:52.3% L1:34.0% BI:13.8%
  
  [libx264 @ 0000019639944040] 8x8 transform intra:88.6% inter:92.9%
  
  [libx264 @ 0000019639944040] coded y,uvDC,uvAC intra: 59.4% 33.6% 2.6% inter: 19.3% 10.9% 0.6%
  
  [libx264 @ 0000019639944040] i16 v,h,dc,p: 57% 30% 12%  1%
  
  [libx264 @ 0000019639944040] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 25% 18% 45%  2%  1%  1%  2%  2%  3%
  
  [libx264 @ 0000019639944040] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 52% 24% 12%  2%  2%  2%  2%  2%  2%
  
  [libx264 @ 0000019639944040] i8c dc,h,v,p: 63% 17% 20%  1%
  
  [libx264 @ 0000019639944040] Weighted P-Frames: Y:0.0% UV:0.0%
  
  [libx264 @ 0000019639944040] ref P L0: 43.8%  7.5% 29.1% 19.6%
  
  [libx264 @ 0000019639944040] ref B L0: 71.8% 21.2%  7.0%
  
  [libx264 @ 0000019639944040] ref B L1: 93.9%  6.1%
  
  [libx264 @ 0000019639944040] kb/s:4908.78

  Link to -v 48 verbose logging : https://pastebin.com/YwQx8bB2