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• Custom Segmentation Guide : How it Works & Segments to Test

  13 novembre 2023, par Erin — Analytics Tips, Uncategorized

  Struggling to get the insights you’re looking for with premade reports and audience segments in your analytics ?

  Custom segmentation can help you better understand your customers, app users or website visitors, but only if you know what you’re doing.

  You can derive false insights with the wrong segments, leading your marketing campaigns or product development in the wrong direction.

  In this article, we’ll break down what custom segmentation is, useful custom segments to consider, how new privacy laws affect segmentation options and how to create these segments in an analytics platform.

  What is custom segmentation ?

  Custom segmentation is when you divide your audience (customers, users, website visitors) into bespoke segments of your own design, not premade segments designed by the analytics or marketing platform provider.

  To do this, you single out “custom segment input” — data points you will use to pinpoint certain users. For example, it could be everyone who has visited a certain page on your site.

  

  Segmentation isn’t just useful for targeting marketing campaigns and also for analysing your customer data. Creating segments is a great way to dive deeper into your data beyond surface-level insights.

  You can explore how various factors impact engagement, conversion rates, and customer lifetime value. These insights can help guide your higher-level strategy, not just campaigns.

  How custom segments can help your business

  As the global business world clamours to become more “data-driven,” even smaller companies collect all sorts of data on visitors, users, and customers.

  However, inexperienced organisations often become “data hoarders” without meaningful insights. They have in-house servers full of data or gigabytes stored by Google Analytics and other third-party providers.

  

  One way to leverage this data is with standard customer segmentation models. This can help you get insights into your most valuable customer groups and other standard segments.

  Custom segments, in turn, can help you dive deeper. They help you unlock insights into the “why” of certain behaviours. They can help you segment customers and your audience to figure out :

  • Why and how someone became a loyal customer
  • How high-order-value customers interact with your site before purchases
  • Which behaviours indicate audience members are likely to convert
  • Which traffic sources drive the most valuable customers

  This specific insight’s power led Gartner to predict that 70% of companies will shift focus from “big data” to “small and wide” by 2025. The lateral detail is what helps inform your marketing strategy. 

  You don’t need the same volume of data if you’re analysing and segmenting it effectively.

  Custom segment inputs : 6 data points you can use to create valuable custom segments 

  To help you get started, here are six useful data points you can use as a basis to create segments — AKA customer segment inputs :

  

  Visits to certain pages

  A basic data point that’s great for custom segments is visits to certain pages. Create segments for popular middle-of-funnel pages and compare their engagement and conversion rates. 

  For example, if a user visits a case study page, you can compare their likelihood to convert vs. other visitors.

  This is a type of behavioural segmentation, but it is the easiest custom segment to set up in terms of analysis and marketing efforts.

  Visitors who perform certain actions

  The other important type of behavioural segment is visitors or users who take certain actions. Think of things like downloading a file, clicking a link, playing a video or scrolling a certain amount.

  For instance, you can create a segment of all visitors who have downloaded a white paper. This can help you explore, for example, what drives someone to download a white paper. You can look at the typical user journey and make it easier for them to access the white paper — especially if your sales reps indicate many inbound leads mention it as a key driver of their interest.

  User devices

  Device-based segmentation lets you compare engagement and conversion rates on mobile, desktop and tablets. You can also get insights into their usage patterns and potential issues with certain mobile elements.

  

  This is one aspect of technographic segmentation, where you segment based on users’ hardware or software. You can also create segments based on browser software or even specific versions.

  Loyal or high-value customers

  The best way to get more loyal or high-value customers is to explore their journey in more detail. These types of segments can help you better understand your ideal customers and how they act on your site.

  You can then use this insight to alter your campaigns or how you communicate with your target audience.

  For example, you might notice that high-value customers tend to come from a certain source. You can then focus your marketing efforts on this source to reach more of your ideal customers.

  Visitor or customer source

  You need to track the results if you’re investing in marketing (like an influencer campaign or a sponsored post) outside platforms with their own analytics.

  

  Before you can create a reliable segment, you need to make sure that you use campaign tracking parameters to reliably track the source. You can use our free campaign tracking URL builder for that.

  Demographic segments — location (country, state) and more

  Web analytics tools, such as Matomo, use visitors’ IP addresses to pinpoint their location more accurately by cross-referencing with a database of known and estimated IP locations. In addition, these tools can detect a visitor’s location through the language settings in their browser. 

  This can help create segments based on location or language. By exploring these trends, you can identify patterns in behaviour, tailor your content to specific audiences, and adapt your overall strategy to better meet the preferences and needs of your diverse visitor base.

  How new privacy laws affect segmentation options

  Over the past few years, new legislation regarding privacy and customer data has been passed globally. The most notable privacy laws are the GDPR in the EU, the CCPA in California and the VCDPA in Virginia.

  

  For most companies, it can save a lot of work and future headaches to choose a GDPR-compliant web analytics solution not only streamlines operations, saving considerable effort and preventing future headaches, but also ensures peace of mind by guaranteeing the collection of compliant and accurate data. This approach allows companies to maintain compliance with privacy regulations while remaining firmly committed to a data-driven strategy.

  Create your very own custom segments in Matomo (while ensuring compliance and data accuracy)

  Crafting precise marketing messages and optimising ROI is crucial, but it becomes challenging without the right tools, especially when it comes to maintaining accurate data.

  That’s where Matomo comes in. Our privacy-friendly web analytics platform is GDPR-compliant and ensures accurate data, empowering you to effortlessly create and analyse precise custom segments.

  If you want to improve your marketing campaigns while remaining GDPR-compliant, start your 21-day free trial of Matomo. No credit card required.

• FFMPEG equalizer clipping audio despite low volume

  23 juillet 2023, par Tom

  I'm using ffmpeg to equalise audio transferred from historic gramophone records, using standard eqs of the era.

  


  The frequency and gain values are taken from the graphic eq settings listed on the Audacity website - https://plugins.audacityteam.org/additional-resources/eq-curves/playback-equalization-for-78-rpm-shellacs-and-early-33-lps

  


  An example of the Blumlien300 curve here - https://2850314611-files.gitbook.io/ /files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FklCVENFte0GRy5IqVz0W%2Fuploads%2FJHS6Mv121GX1h898xy4K%2FBlumlein300_3.2.2.txt?alt=media&token=8d04df05-366d-47f8-8c82-149fa5eda59a

  


  The audio file I'm testing with has a digital peak of -35db, the highest gain value applied on this eq is 17db. When I run the ffmpeg command though, it reports the audio is clipping and the result is a horribly distorted recording.

  


  Can anyone advise why this is happening ? I run the same file through the same eq settings in Audacity and the result is as expected.

  


  set eq="equalizer=f=22050:g=-0.4,equalizer=f=21203.720228928225:g=-0.4,equalizer=f=20389.920705063967:g=-0.4,equalizer=f=19607.354835383569:g=-0.4,equalizer=f=18854.823871147240:g=-0.4,equalizer=f=18131.175071633737:g=-0.4,equalizer=f=17435.299938351014:g=-0.4,equalizer=f=16766.132517017904:g=-0.4,equalizer=f=16122.647764715837:g=-0.4,equalizer=f=15503.859979709296:g=-0.4,equalizer=f=14908.821291529812:g=-0.4,equalizer=f=14336.620209010769:g=-0.4,equalizer=f=13786.380224048187:g=-0.4,equalizer=f=13257.258468950000:g=-0.4,equalizer=f=12748.444425315412:g=-0.4,equalizer=f=12259.158682468413:g=-0.4,equalizer=f=11788.651743541806:g=-0.4,equalizer=f=11336.202877384472:g=-0.4,equalizer=f=10901.119014532051:g=-0.4,equalizer=f=10482.733685550458:g=-0.4,equalizer=f=10080.406000125797:g=-0.4,equalizer=f=9693.519665336817:g=-0.4,equalizer=f=9321.482041606178:g=-0.4,equalizer=f=8963.723234884175:g=-0.4,equalizer=f=8619.695223674737:g=-0.4,equalizer=f=8288.871019565895:g=-0.4,equalizer=f=7970.743859979441:g=-0.4,equalizer=f=7664.826431902562:g=-0.4,equalizer=f=7370.650125412990:g=-0.4,equalizer=f=7087.764315853595:g=-0.4,equalizer=f=6815.735673557399:g=-0.4,equalizer=f=6554.147500065165:g=-0.4,equalizer=f=6302.599089819104:g=-0.4,equalizer=f=6060.705116354743:g=-0.4,equalizer=f=5828.095042050793:g=-0.4,equalizer=f=5604.412550532827:g=-0.4,equalizer=f=5389.315000861326:g=-0.4,equalizer=f=5182.472902668021:g=-0.394052055589,equalizer=f=4983.569411436476:g=-0.386751590389,equalizer=f=4792.299843153906:g=-0.376185664074,equalizer=f=4608.371207590573:g=-0.362543760251,equalizer=f=4431.501759492006:g=-0.345993198097,equalizer=f=4261.420566996452:g=-0.330710126890,equalizer=f=4097.867096616487:g=-0.318503033191,equalizer=f=3940.590814149046:g=-0.309564283335,equalizer=f=3789.350800902538:g=-0.303741189604,equalizer=f=3643.915384653179:g=-0.300601888512,equalizer=f=3504.061784765236:g=-0.3,equalizer=f=3369.575770931567:g=-0.3,equalizer=f=3240.251335011708:g=-0.3,equalizer=f=3115.890375464830:g=-0.3,equalizer=f=2996.302393894170:g=-0.3,equalizer=f=2881.304203238093:g=-0.3,equalizer=f=2770.719647160795:g=-0.3,equalizer=f=2664.379330212802:g=-0.3,equalizer=f=2562.120358347913:g=-0.3,equalizer=f=2463.786089399117:g=-0.3,equalizer=f=2369.225893131248:g=-0.3,equalizer=f=2278.294920502843:g=-0.3,equalizer=f=2190.853881783698:g=-0.3,equalizer=f=2106.768833188346:g=-0.296437432785,equalizer=f=2025.910971698469:g=-0.290217913930,equalizer=f=1948.156437760116:g=-0.280922418484,equalizer=f=1873.386125553329:g=-0.268550946447,equalizer=f=1801.485500543704:g=-0.253103497820,equalizer=f=1732.344424036255:g=-0.235614749092,equalizer=f=1665.856984462975:g=-0.218076286078,equalizer=f=1601.921335145533:g=-0.200537822606,equalizer=f=1540.439538284674:g=-0.184632657170,equalizer=f=1481.317414937308:g=-0.168779161348,equalizer=f=1424.464400751469:g=-0.152925665153,equalizer=f=1369.793407238189:g=-0.137072168707,equalizer=f=1317.220688367753:g=-0.121218672255,equalizer=f=1266.665712285991:g=-0.105365175802,equalizer=f=1218.051037954117:g=-0.088396941462,equalizer=f=1171.302196523118:g=-0.070858476440,equalizer=f=1126.347577261013:g=-0.053320011417,equalizer=f=1083.118317858216:g=-0.034770724190,equalizer=f=1041.548198942992:g=-0.013200571808,equalizer=f=1001.573542645411:g=0.011445558081,equalizer=f=963.133115054414:g=0.039167665478,equalizer=f=926.168032418592:g=0.069965750383,equalizer=f=890.621670946974:g=0.103839812794,equalizer=f=856.439580071665:g=0.140789852714,equalizer=f=823.569399039473:g=0.180815870141,equalizer=f=791.960776704742:g=0.223158863450,equalizer=f=761.565294400547:g=0.266149082252,equalizer=f=732.336391770094:g=0.311823093692,equalizer=f=704.229295444710:g=0.360237839089,equalizer=f=677.200950459179:g=0.413174176689,equalizer=f=651.209954299352:g=0.471478099167,equalizer=f=626.216493481026:g=0.535493496953,equalizer=f=602.182282562909:g=0.606978871276,equalizer=f=579.070505500287:g=0.684199304160,equalizer=f=556.845759249530:g=0.767096732395,equalizer=f=535.473999537060:g=0.853776460170,equalizer=f=514.922488709709:g=0.943323717867,equalizer=f=495.159745586582:g=1.036571598687,equalizer=f=476.155497235608:g=1.135335711982,equalizer=f=457.880632600910:g=1.237175803242,equalizer=f=440.307157909949:g=1.342335109599,equalizer=f=423.408153792158:g=1.453088412615,equalizer=f=407.157734043353:g=1.569993670188,equalizer=f=391.531005972773:g=1.688508164136,equalizer=f=376.504032271996:g=1.808802987893,equalizer=f=362.053794347337:g=1.934465396527,equalizer=f=348.158157059540:g=2.065823830001,equalizer=f=334.795834816768:g=2.204891058267,equalizer=f=321.946358968944:g=2.352009664049,equalizer=f=309.590046453497:g=2.509552803849,equalizer=f=297.707969644483:g=2.678532979186,equalizer=f=286.281927358906:g=2.856115742576,equalizer=f=275.294416975809:g=3.041612670003,equalizer=f=264.728607625441:g=3.230723044219,equalizer=f=254.568314407418:g=3.422700948357,equalizer=f=244.797973598401:g=3.621312762050,equalizer=f=235.402618811295:g=3.826195809769,equalizer=f=226.367858069467:g=4.034154835453,equalizer=f=217.679851760848:g=4.246639157749,equalizer=f=209.325291438168:g=4.468048945659,equalizer=f=201.291379432825:g=4.698686666092,equalizer=f=193.565809251186:g=4.938552319047,equalizer=f=186.136746723276:g=5.187645904525,equalizer=f=178.992811874976:g=5.445967422525,equalizer=f=172.123061495972:g=5.712025685327,equalizer=f=165.516972376744:g=5.984236264250,equalizer=f=159.164425188922:g=6.258981796419,equalizer=f=153.055688984312:g=6.515823590632,equalizer=f=147.181406288853:g=6.777692051390,equalizer=f=141.532578768664:g=7.044587178695,equalizer=f=136.100553446236:g=7.314095599483,equalizer=f=130.877009445637:g=7.583605034445,equalizer=f=125.853945246444:g=7.853114469407,equalizer=f=121.023666426868:g=8.146285201135,equalizer=f=116.378773877299:g=8.444439101287,equalizer=f=111.912152466211:g=8.742593001439,equalizer=f=107.616960141075:g=9.042209423688,equalizer=f=103.486617447577:g=9.344900874707,equalizer=f=99.514797451091:g=9.650668303691,equalizer=f=95.695416044961:g=9.959511710641,equalizer=f=92.022622630759:g=10.271431095557,equalizer=f=88.490791156230:g=10.586541422511,equalizer=f=85.094511497198:g=10.906991735356,equalizer=f=81.828581170245:g=11.233594002758,equalizer=f=78.687997363448:g=11.556996378650,equalizer=f=75.667949272979:g=11.873211536187,equalizer=f=72.763810733831:g=12.194794278600,equalizer=f=69.971133133372:g=12.521192148224,equalizer=f=67.285638596875:g=12.846501740168,equalizer=f=64.703213434600:g=13.169127539473,equalizer=f=62.219901840358:g=13.492484068742,equalizer=f=59.831899831942:g=13.820346094285,equalizer=f=57.535549424116:g=14.145340590334,equalizer=f=55.327333025244:g=14.467659297988,equalizer=f=53.203868048980:g=14.789401139821,equalizer=f=51.161901732761:g=15.111142981226,equalizer=f=49.198306155165:g=15.437629968456,equalizer=f=47.310073444503:g=15.770860796927,equalizer=f=45.494311171305:g=16.104091624940,equalizer=f=43.748237917649:g=16.412536097232,equalizer=f=42.069179016527:g=16.579143834849,equalizer=f=40.454562454745:g=16.588876722789,equalizer=f=38.901914933067:g=16.461103901687,equalizer=f=37.408858077565:g=16.215674576171,equalizer=f=35.973104796389:g=15.850016386783,equalizer=f=34.592455776352:g=15.350234288456,equalizer=f=33.264796113983:g=14.615823142814,equalizer=f=31.988092075884:g=13.626809695512,equalizer=f=30.760387983412:g=12.332756508563,equalizer=f=29.579803216941:g=10.518513413063,equalizer=f=28.444529335092:g=8.346792732977,equalizer=f=27.352827304528:g=5.833681758551,equalizer=f=26.303024836072:g=3.097942665008,equalizer=f=25.293513823067:g=0.163604913582,equalizer=f=24.322747878043:g=-2.887748621210,equalizer=f=23.389239963935:g=-6.091081601564,equalizer=f=22.491560116216:g=-9.478973229620,equalizer=f=21.628333252442:g=-12.539218030638,equalizer=f=20.798237065887:g=-14.384804507659,equalizer=f=20:g=-15"
ffmpeg -i "File.wav" -af %eq% -c:a pcm_s24le out.wav


  


• FFmpeg error : ratecontrol_init : can't open stats file

  18 décembre 2015, par oldo.nicho

  I’ve setup an AWS EC2 instance running Ubuntu 14.04 and have installed FFmpeg so that I can compress and transcode video.

  I’m trying to do a two pass conversion with the following code :

  ffmpeg -i input-file.avi -codec:v libx264 -profile:v high -preset slow -b:v 500k -maxrate 500k -bufsize 1000k -vf scale=702:-1 -threads 0 -pass 1 -an -f mp4 ~/encoded/null

  and second pass :

  ffmpeg -i input-file.avi -codec:v libx264 -profile:v high -preset slow -b:v 500k -maxrate 500k -bufsize 1000k -vf scale=702:-1 -threads 0 -pass 2 -codec:a libfdk_aac -b:a 128k -f mp4 output-file.mp4

  However I get the following error :

  ffmpeg version N-77283-g91c2a33 Copyright (c) 2000-2015 the FFmpeg developers
  
    built with gcc 4.8 (Ubuntu 4.8.4-2ubuntu1~14.04)
  
    configuration: --prefix=/home/ubuntu/ffmpeg_build --pkg-config-flags=--static --extra-cflags=-I/home/ubuntu/ffmpeg_build/include --extra-ldflags=-L/home/ubuntu/ffmpeg_build/lib --bindir=/home/ubuntu/bin --enable-gpl --enable-libass --enable-libfdk-aac --enable-libfreetype --enable-libmp3lame --enable-libopus --enable-libtheora --enable-libvorbis --enable-libx264 --enable-nonfree
  
    libavutil      55. 11.100 / 55. 11.100
  
    libavcodec     57. 17.100 / 57. 17.100
  
    libavformat    57. 20.100 / 57. 20.100
  
    libavdevice    57.  0.100 / 57.  0.100
  
    libavfilter     6. 21.100 /  6. 21.100
  
    libswscale      4.  0.100 /  4.  0.100
  
    libswresample   2.  0.101 /  2.  0.101
  
    libpostproc    54.  0.100 / 54.  0.100
  
  Input #0, avi, from 'input-file.avi':
  
    Duration: 01:18:05.29, start: 0.000000, bitrate: 2025 kb/s
  
      Stream #0:0: Video: mpeg4 (Simple Profile) (XVID / 0x44495658), yuv420p, 720x480 [SAR 1:1 DAR 3:2], 1789 kb/s, 29.97 fps, 29.97 tbr, 29.97 tbn, 29.97 tbc
  
      Stream #0:1: Audio: ac3 ([0] [0][0] / 0x2000), 48000 Hz, stereo, fltp, 224 kb/s
  
  [libx264 @ 0x1e04240] using SAR=1/1
  
  [libx264 @ 0x1e04240] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX AVX2 FMA3 LZCNT BMI2
  
  [libx264 @ 0x1e04240] ratecontrol_init: can't open stats file
  
  Output #0, mp4, to '/home/ubuntu/encoded/null':
  
      Stream #0:0: Video: h264, none, q=2-31, 128 kb/s, SAR 1:1 DAR 0:0, 29.97 fps
  
      Metadata:
  
        encoder         : Lavc57.17.100 libx264
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (mpeg4 (native) -> h264 (libx264))
  
  Error while opening encoder for output stream #0:0 - maybe incorrect parameters such as bit_rate, rate, width or height

  The command as written above works fine on my local computer (running OSX). Would anyone have any suggestions as to how to fix this problem ?