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• Conversion Rate Optimisation Statistics for 2024 and Beyond

  21 novembre 2023, par Erin — Analytics Tips

  Driving traffic to your website is only half the battle. The real challenge — once you’ve used a web analytics solution to understand how users behave — is turning more of those visitors into customers.

  That doesn’t happen by accident. You need to employ conversion rate optimisation strategies and tools to see even a small lift in conversion rates. The good news is that it doesn’t take much to see massive results. Raising your conversion rate from 1% to 3% can triple your revenue. 

  In even better news, you don’t have to guess at the best ways to improve your conversion rate. We’ve done the hard work and collected the most recent and relevant conversion rate optimisation statistics to help you. 

  General conversion rate optimisation statistics

  It appears the popularity of conversion rate optimisation is soaring. According to data collected by Google Trends, there were more people searching for the term “conversion rate optimization” in September 2023 than ever before. 

  As you can see from the chart below, the term’s popularity is on a clear upward trajectory, meaning even more people could be searching for it in the near future. (Source)

  

  Do you want to know what the average landing page conversion rate is ? According to research by WordStream, the average website conversion rate across all industries is 2.35%. 

  That doesn’t paint the whole picture, however. Better-performing websites have significantly higher conversion rates. The top 25% of websites across all industries convert at a rate of 5.31% or higher. (Source)

  Let’s break things down by industry now. The Unbounce Conversion Benchmark Report offers a detailed analysis of how landing pages convert across various industries.

  First, we have the Finance and Insurance industry, which boasts a conversion rate of 15.6%. 

  On the other end, agencies appears to be one of the worst-performing. Agencies’ landing pages convert at a rate of 8.8%. (Source)

  

  What about the size of the conversion rate optimisation industry ? Given the growth in popularity of the term in Google, surely the industry is experiencing growth, right ?

  You’d be correct in that assumption. The conversion rate optimisation software market was valued at $771.2 million in 2018 and is projected to reach $1.932 billion by 2026 — a compound annual growth rate (CAGR) of 9.6%.

  Statistics on the importance of conversion rate optimisation

  If you’re reading this article, you probably think conversion rate optimisation is pretty important. But do you know its importance and where it ranks in your competitors’ priorities ? Read on to find out. 

  Bounce rate — the number of people who leave your website without visiting another page or taking action — is the scourge of conversion rate optimisation efforts. Every time someone bounces from your site, you lose the chance to convert them.

  The questions, then, are : how often do people bounce on average and how does your bounce rate compare ? 

  Siege Media analysed over 1.3 billion sessions from a range of traffic sources, including 700 million bounces, to calculate an average bounce rate of 50.9%. (Source)

  

  Bounce rates vary massively from website to website and industry to industry, however. Siege Media’s study unveils an array of average bounce rates across industries :

  • Travel – 82.58%
  • B2B – 65.17%
  • Lifestyle – 64.26%
  • Business and Finance – 63.51%
  • Healthcare – 59.50%
  • eCommerce – 54.54%
  • Insurance – 45.96%
  • Real Estate – 40.78%

  It won’t come as much of a surprise to learn that marketers are determined to reduce bounce rates and improve lead conversion. Today’s marketers are highly performance-based. When asked about their priorities for the coming year, 79% of marketers said their priority was generating quality qualified leads — the most popular answer in the survey. (Source)

  Just because it is a priority for marketers doesn’t mean that everyone has their stuff together. If you have a conversion rate optimisation process in place, you’re in the minority. According to research by HubSpot, less than one in five marketers (17%) use landing page A/B tests to improve their conversion rates. (Source)

  When it comes to personalisation strategies – a common and effective tool to increase conversion rates — the picture isn’t any rosier. Research by Salesforce found just over one-quarter of markets are confident their organisation has a successful strategy for personalisation. (Source)

  Conversion rate optimisation tactics statistics

  There are hundreds of ways to improve your website’s conversion rates. From changing the color of buttons to the structure of your landing page to your entire conversion funnel, in this section, we’ll look at the most important statistics you need to know when choosing tactics and building your own CRO experiments. 

  If you are looking for the best method to convert visitors, then email lead generation forms are the way to go, according to HubSpot. This inoffensive and low-barrier data collection method boasts a 15% conversion rate, according to the marketing automation company’s research. (Source)

  Where possible, make your call-to-actions personalised. Marketing personalisation, whether through behavioral segmentation or another strategy, is an incredibly powerful way of showing users that you care about their specific needs. It’s no great surprise, then, that HubSpot found personalised calls-to-actions perform a whopping 202% better than basic CTAs. (Source)

  If you want to boost conversion rates, then it’s just as important to focus on quantity as well as quality. Yes, a great-looking, well-written landing page will go a long way to improving your conversion rate, but having a dozen of these pages will do even more. 

  Research by HubSpot found companies see a 55% increase in leads when they increase the number of landing pages from 10 to 15. What’s more, companies with over 40 landing pages increase conversion by more than 500%. (Source)

  

  User-generated content (UGC) should also be high on your priority list to boost conversion rates. Several statistics show how powerful, impactful and persuasive social proof like user reviews can be. 

  Research shows that visitors who scroll to the point where they encounter user-generated content increase the likelihood they convert by a staggering 102.4%. (Source)

  Other trust signs can be just as impactful. Research by Trustpilot found that the following four trust signals make consumers more likely to make a purchase when shown on a product page :

  • Positive star rating and reviews (85% more likely to make a purchase)
  • Positive star rating (78%)
  • Positive customer testimonials (82%)
  • Approved or authorised seller badge (76%)

  (Source)

  Showing ratings and reviews has also increased conversion rates by 38% on home appliances and electronics stores. (Source)

  And no wonder, given that consumers are more likely to buy from brands they trust than brands they love, according to the 2021 Edelman Trust Barometer Special Report. (Source) 

  A lack of trust is also one of the top four reasons consumers abandon their shopping cart at checkout. (Source) 

  Traffic source conversion rate statistics

  What type of traffic works the best when it comes to conversions, or how often you should be signing up users to your mailing list ? Let’s look at the stats to find out. 

  Email opt-ins are one of the most popular methods for collecting customer information — and an area where digital marketers spend a lot of time and effort when it comes to conversion rate optimisation. So, what is the average conversion rate of an email opt-in box ?

  According to research by Sumo — based on 3.2 billion users who have seen their opt-in boxes — the average email opt-in rate is 1.95%. (Source)

  Search advertising is an effective way of driving website traffic, but how often do those users click on these ads ?

  WordStream’s research puts the average conversion of search advertising for all industries at 6.11%. (Source)

  The arts and entertainment industry enjoys the highest clickthrough rates (11.78%), followed by sports and recreation (10.53%) and travel (10.03%). Legal services and the home improvement industry have the lowest clickthrough rates at 4.76% and 4.8%, respectively.

  

  If you’re spending money on Google ads, then you’d better hope a significant amount of users convert after clicking them. 

  Unfortunately, conversion rates from Google ads decreased year-on-year for most industries in 2023, according to research by WordStream — in some cases, those decreases were significant. The only two industries that didn’t see a decrease in conversion rates were beauty and personal care and education and instruction. (Source)

  The average conversion rate for search ads across all industries is 7.04%. The animal and pet niche has the highest conversion rate (13.41%), while apparel, fashion and jewelry have the lowest conversion rate (1.57%). (Source)

  What about other forms of traffic ? Well, there’s good reason to try running interstitial ads on smartphone apps if you aren’t already. Ads on the iOS app see a 14.3 percent conversion rate on average. (Source)

  E-commerce conversion rate optimisation statistics (400 words)

  Conversion rate optimisation can be the difference between a store that sets new annual sales records and one struggling to get by. 

  The good news is that the conversion rate among US shoppers was the highest it’s ever been in 2021, with users converting at 2.6%. (Source)

  If you have a Shopify store, then you may find conversion rates a little lower. A survey by Littledata found the average conversion rate for Shopify was 1.4% in September 2022. (Source)

  What about specific e-commerce categories ? According to data provided by Dynamic Yield, the consumer goods category converted at the highest rate in September 2023 (4.22%), a spike of 0.34% from August. 

  Generally, the food and beverage niche boasts the highest conversion rate (4.87%), and the home and furniture niche has the lowest conversion rate (1.44%). (Source)

  If you’re serious about driving sales, don’t focus on mobile devices at the expense of consumers who shop on desktop devices. The conversion rate among US shoppers tends to be higher for desktop users than for mobile users. 

  

  In the second quarter of 2022, for instance, desktop shoppers converted at a rate of 3% on average compared to smartphone users who converted at an average rate of 2%. (Source)

  Increase your conversions with Matomo

  Conversion rate optimisation can help you grow your subscriber list, build your customer base and increase your revenue. Now, it’s time to put what you’ve learned into practice.

  Use the advice above to guide your experiments and track everything with Matomo. Achieve unparalleled data accuracy while harnessing an all-in-one solution packed with essential conversion optimisation features, including Heatmaps, Session Recordings and A/B Testing. Matomo makes it easier than ever to analyse conversion-focused experiments.

  Get more from your conversion rate optimisations by trying Matomo free for 21 days. No credit card required.

• ffmpeg : videos before and after conversion aren't the same length

  16 juillet 2012, par Koyot

  I have a set of .mov videos which require conversion to .mp4 format. I'm using ffmpeg and running this command :

  ffmpeg -i Banking.mov -vsync -async -sameq -ac 1 -ab 64k -ar 44100 Banking.mp4

  There is a slight difference between input and output video in time length (00:03:35.407 and 00:03:35.582). And here's the catch - I'm storing time cue set at precise times in a file which is used by a program to point at specific scenes. The 0.1 second difference causes it to point at wrong scenes, therefore making the cue set useless. Is there any possibility to preserve exactly the same time in different format ?

     FFmpeg version CVS, Copyright (c) 2000-2004 Fabrice BellardMac OSX universal build for ffmpegX
  
    configuration:  --enable-memalign-hack --enable-mp3lame --enable-gpl --disable-vhook --disable-ffplay --disable-ffserver --enable-a52 --enable-xvid --enable-faac --enable-faad --enable-amr_nb --enable-amr_wb --enable-pthreads --enable-x264 
  
    libavutil version: 49.0.0
  
    libavcodec version: 51.9.0
  
    libavformat version: 50.4.0
  
    built on Apr 15 2006 04:58:19, gcc: 4.0.1 (Apple Computer, Inc. build 5250)
  
  [mov,mp4,m4a,3gp,3g2,mj2 @ 0x5597b8]negative ctts, ignoring
  
  Input #0, mov,mp4,m4a,3gp,3g2,mj2, from 'Banking.mov':
  
    Duration: 00:03:35.6, start: 0.000000, bitrate: 1400 kb/s
  
    Stream #0.0(eng): Audio: pcm_s16be, 24000 Hz, stereo, 768 kb/s
  
    Stream #0.1(eng), 29.97 fps(r): Video: h264, yuv420p, 720x480
  
  Output #0, mp4, to 'Banking.mp4':
  
    Stream #0.0, 29.97 fps(c): Video: mpeg4, yuv420p, 720x480, q=2-31, 200 kb/s
  
    Stream #0.1: Audio: aac, 44100 Hz, mono, 64 kb/s
  
  Stream mapping:
  
    Stream #0.1 -> #0.0
  
    Stream #0.0 -> #0.1
  
  Press [q] to stop encoding
  
  frame= 6461 q=0.0 Lsize=   53181kB time=215.3 bitrate=2023.3kbits/s    
  
  video:51437kB audio:1618kB global headers:0kB muxing overhead 0.237816%

• FFMPEG Pipeline Crash [closed]

  17 août 2023, par Badgio10177

  I instantiate an ffmpeg pipeline within C++. No frames get streamed to the RTSP server and the pipeline crashes unexpectedly.

  


  I have the following code :

  


  #include <iostream>&#xA;#include <typeinfo>&#xA;#include "opencvmex.hpp"&#xA;#include &#xA;#include &#xA;#include "mex.h"&#xA;#include &#xA;#include &#xA;#include  // Windows API for process enumeration&#xA;#include <opencv2></opencv2>core.hpp>&#xA;&#xA;// Global variables&#xA;FILE* openPipeLine = NULL;&#xA;&#xA;//////////////////////////////////////////////////////////////////////////////&#xA;// Exit function to execute when the mex function is cleared.&#xA;//////////////////////////////////////////////////////////////////////////////&#xA;void exitFcn()&#xA;{&#xA;    fflush(openPipeLine); // Clear out the pipeline.&#xA;    _pclose(openPipeLine);   //Close the pipeline.&#xA;}&#xA;&#xA;///////////////////////////////////////////////////////////////////////////&#xA;// Main entry point to a MEX function&#xA;///////////////////////////////////////////////////////////////////////////&#xA;void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[], int frameWidth, int frameHeight)&#xA;{&#xA;    // Use the appropriate namespace for OpenCV functions&#xA;    using namespace cv;&#xA;&#xA;    Ptr<mat> inputFrame = ocvMxArrayToImage_uint8(prhs[0], true);&#xA;    Mat processedFrame = *inputFrame;&#xA;&#xA;    // Check if FFMPEG process has been started&#xA;    if (!openPipeLine)&#xA;    {&#xA;        openPipeLine = _popen("ffmpeg -f rawvideo -r 10 -video_size 1280x720 -pixel_format bgr24 -i pipe: -vcodec libx264 -crf 25 -pix_fmt yuv420p -f rtsp rtsp://192.168.0.2:8554/mystream 2> log.txt", "wb");&#xA;    }&#xA;&#xA;    // Write the frame data to the pipeline&#xA;    fwrite(processedFrame.data, 1, frameWidth * frameHeight * 3, openPipeLine);&#xA;    mexAtExit(exitFcn);&#xA;}&#xA;&#xA;&#xA;&#xA;</mat></typeinfo></iostream>

  


  The function is a Matlab Mex function. What is interesting is that there are certain times when the stream works and some times it just crashes. The log file for the ffmpeg process is the following :

  


  ffmpeg version 2023-08-14-git-c704901324-full_build-www.gyan.dev Copyright (c) 2000-2023 the FFmpeg developers
  built with gcc 12.2.0 (Rev10, Built by MSYS2 project)
  configuration: --enable-gpl --enable-version3 --enable-static --disable-w32threads --disable-autodetect --enable-fontconfig --enable-iconv --enable-gnutls --enable-libxml2 --enable-gmp --enable-bzlib --enable-lzma --enable-libsnappy --enable-zlib --enable-librist --enable-libsrt --enable-libssh --enable-libzmq --enable-avisynth --enable-libbluray --enable-libcaca --enable-sdl2 --enable-libaribb24 --enable-libaribcaption --enable-libdav1d --enable-libdavs2 --enable-libuavs3d --enable-libzvbi --enable-librav1e --enable-libsvtav1 --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxavs2 --enable-libxvid --enable-libaom --enable-libjxl --enable-libopenjpeg --enable-libvpx --enable-mediafoundation --enable-libass --enable-frei0r --enable-libfreetype --enable-libfribidi --enable-libharfbuzz --enable-liblensfun --enable-libvidstab --enable-libvmaf --enable-libzimg --enable-amf --enable-cuda-llvm --enable-cuvid --enable-ffnvcodec --enable-nvdec --enable-nvenc --enable-d3d11va --enable-dxva2 --enable-libvpl --enable-libshaderc --enable-vulkan --enable-libplacebo --enable-opencl --enable-libcdio --enable-libgme --enable-libmodplug --enable-libopenmpt --enable-libopencore-amrwb --enable-libmp3lame --enable-libshine --enable-libtheora --enable-libtwolame --enable-libvo-amrwbenc --enable-libcodec2 --enable-libilbc --enable-libgsm --enable-libopencore-amrnb --enable-libopus --enable-libspeex --enable-libvorbis --enable-ladspa --enable-libbs2b --enable-libflite --enable-libmysofa --enable-librubberband --enable-libsoxr --enable-chromaprint
  libavutil      58. 16.101 / 58. 16.101
  libavcodec     60. 23.100 / 60. 23.100
  libavformat    60. 10.100 / 60. 10.100
  libavdevice    60.  2.101 / 60.  2.101
  libavfilter     9. 11.100 /  9. 11.100
  libswscale      7.  3.100 /  7.  3.100
  libswresample   4. 11.100 /  4. 11.100
  libpostproc    57.  2.100 / 57.  2.100
Input #0, rawvideo, from 'pipe:':
  Duration: N/A, start: 0.000000, bitrate: 221184 kb/s
  Stream #0:0: Video: rawvideo (BGR[24] / 0x18524742), bgr24, 1280x720, 221184 kb/s, 10 tbr, 10 tbn
Stream mapping:
  Stream #0:0 -> #0:0 (rawvideo (native) -> h264 (libx264))
[libx264 @ 0000027964ad6300] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2 AVX512
[libx264 @ 0000027964ad6300] profile High, level 3.1, 4:2:0, 8-bit
[libx264 @ 0000027964ad6300] 264 - core 164 r3107 a8b68eb - H.264/MPEG-4 AVC codec - Copyleft 2003-2023 - 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=22 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=10 scenecut=40 intra_refresh=0 rc_lookahead=40 rc=crf mbtree=1 crf=25.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 ip_ratio=1.40 aq=1:1.00
Output #0, rtsp, to 'rtsp://192.168.0.2:8554/mystream':
  Metadata:
    encoder         : Lavf60.10.100
  Stream #0:0: Video: h264, yuv420p(tv, progressive), 1280x720, q=2-31, 10 fps, 90k tbn
    Metadata:
      encoder         : Lavc60.23.100 libx264
    Side data:
      cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
frame=    0 fps=0.0 q=0.0 size=       0kB time=N/A bitrate=N/A speed=N/A    
[vost#0:0/libx264 @ 0000027964ad5f00] Error submitting a packet to the muxer: Broken pipe
[out#0/rtsp @ 0000027964abdf00] Error muxing a packet
frame=    1 fps=0.1 q=27.0 size=N/A time=-00:00:00.10 bitrate=N/A speed=N/A    
[out#0/rtsp @ 0000027964abdf00] video:146kB audio:0kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: unknown
frame=    1 fps=0.0 q=-1.0 Lsize=N/A time=00:00:06.50 bitrate=N/A speed=0.32x    
[libx264 @ 0000027964ad6300] frame I:1     Avg QP:26.79  size:148574
[libx264 @ 0000027964ad6300] frame P:17    Avg QP:21.66  size: 23672
[libx264 @ 0000027964ad6300] frame B:50    Avg QP:28.20  size:  3276
[libx264 @ 0000027964ad6300] consecutive B-frames:  1.5%  0.0%  4.4% 94.1%
[libx264 @ 0000027964ad6300] mb I  I16..4:  1.1% 53.0% 45.9%
[libx264 @ 0000027964ad6300] mb P  I16..4:  1.8%  9.3%  1.2%  P16..4: 29.5% 10.2% 14.0%  0.0%  0.0%    skip:34.0%
[libx264 @ 0000027964ad6300] mb B  I16..4:  0.1%  0.5%  0.0%  B16..8: 21.1%  3.3%  1.3%  direct: 2.0%  skip:71.7%  L0:50.9% L1:46.2% BI: 2.9%
[libx264 @ 0000027964ad6300] 8x8 transform intra:68.9% inter:94.3%
[libx264 @ 0000027964ad6300] coded y,uvDC,uvAC intra: 78.9% 70.2% 26.1% inter: 10.9% 8.9% 1.7%
[libx264 @ 0000027964ad6300] i16 v,h,dc,p: 31% 36% 32%  1%
[libx264 @ 0000027964ad6300] i8 v,h,dc,ddl,ddr,vr,hd,vl,hu: 16% 22% 40%  4%  2%  2%  3%  2% 10%
[libx264 @ 0000027964ad6300] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 29% 32%  8%  4%  4%  4%  6%  4%  9%
[libx264 @ 0000027964ad6300] i8c dc,h,v,p: 35% 36% 24%  5%
[libx264 @ 0000027964ad6300] Weighted P-Frames: Y:0.0% UV:0.0%
[libx264 @ 0000027964ad6300] ref P L0: 60.0% 17.6%  9.3% 13.1%
[libx264 @ 0000027964ad6300] ref B L0: 73.1% 20.1%  6.8%
[libx264 @ 0000027964ad6300] ref B L1: 88.0% 12.0%
[libx264 @ 0000027964ad6300] kb/s:840.93
Conversion failed!



  


  Are there any parameters in my pipeline that are causing the process to crash ?