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• 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


  


• 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.

• What is a Cohort Report ? A Beginner’s Guide to Cohort Analysis

  3 janvier 2024, par Erin

  Handling your user data as a single mass of numbers is rarely conducive to figuring out meaningful patterns you can use to improve your marketing campaigns.

  A cohort report (or cohort analysis) can help you quickly break down that larger audience into sequential segments and contrast and compare based on various metrics. As such, it is a great tool for unlocking more granular trends and insights — for example, identifying patterns in engagement and conversions based on the date users first interacted with your site.

  In this guide, we explain the basics of the cohort report and the best way to set one up to get the most out of it.

  What is a cohort report ?

  In a cohort report, you divide a data set into groups based on certain criteria — typically a time-based cohort metric like first purchase date — and then analyse the data across those segments, looking for patterns.

  Date-based cohort analysis is the most common approach, often creating cohorts based on the day a user completed a particular action — signed up, purchased something or visited your website. Depending on the metric you choose to measure (like return visits), the cohort report might look something like this :

  

  Note that this is not a universal benchmark or anything of the sort. The above is a theoretical cohort analysis based on app users who downloaded the app, tracking and comparing the retention rates as the days go by. 

  The benchmarks will be drastically different depending on the metric you’re measuring and the basis for your cohorts. For example, if you’re measuring returning visitor rates among first-time visitors to your website, expect single-digit percentages even on the second day.

  Your industry will also greatly affect what you consider positive in a cohort report. For example, if you’re a subscription SaaS, you’d expect high continued usage rates over the first week. If you sell office supplies to companies, much less so.

  What is an example of a cohort ?

  As we just mentioned, a typical cohort analysis separates users or customers by the date they first interacted with your business — in this case, they downloaded your app. Within that larger analysis, the users who downloaded it on May 3 represent a single cohort.

  

  In this case, we’ve chosen behaviour and time — the app download day — to separate the user base into cohorts. That means every specific day denotes a specific cohort within the analysis.

  Diving deeper into an individual cohort may be a good idea for important holidays or promotional events like Black Friday.

  Of course, cohorts don’t have to be based on specific behaviour within certain periods. You can also create cohorts based on other dimensions :

  • Transactional data — revenue per user
  • Churn data — date of churn
  • Behavioural cohort — based on actions taken on your website, app or e-commerce store, like the number of sessions per user or specific product pages visited
  • Acquisition cohort — which channel referred the user or customer

  For more information on different cohort types, read our in-depth guide on cohort analysis.

  How to create a cohort report (and make sense of it)

  Matomo makes it easy to view and analyse different cohorts (without the privacy and legal implications of using Google Analytics).

  Here are a few different ways to set up a cohort report in Matomo, starting with our built-in cohorts report.

  Cohort reports

  With Matomo, cohort reports are automatically compiled based on the first visit date. The default metric is the percentage of returning visitors.

  

  Changing the settings allows you to create multiple variations of cohort analysis reports.

  Break down cohorts by different metrics

  The percentage of returning visits can be valuable if you’re trying to improve early engagement in a SaaS app onboarding process. But it’s far from your only option.

  You can also compare performance by conversion, revenue, bounce rate, actions per visit, average session duration or other metrics.

  

  Change the time and scope of your cohort analysis

  Splitting up cohorts by single days may be useless if you don’t have a high volume of users or visitors. If the average cohort size is only a few users, you won’t be able to identify reliable patterns. 

  Matomo lets you set any time period to create your cohort analysis report. Instead of the most recent days, you can create cohorts by week, month, year or custom date ranges. 

  

  Cohort sizes will depend on your customer base. Make sure each cohort is large enough to encapsulate all the customers in that cohort and not so small that you have insignificant cohorts of only a few customers. Choose a date range that gives you that without scaling it too far so you can’t identify any seasonal trends.

  Cohort analysis can be a great tool if you’ve recently changed your marketing, product offering or onboarding. Set the data range to weekly and look for any impact in conversions and revenue after the changes.

  Using the “compare to” feature, you can also do month-over-month, quarter-over-quarter or any custom date range comparisons. This approach can help you get a rough overview of your campaign’s long-term progress without doing any in-depth analysis.

  You can also use the same approach to compare different holiday seasons against each other.

  If you want to combine time cohorts with segmentation, you can run cohort reports for different subsets of visitors instead of all visitors. This can lead to actionable insights like adjusting weekend or specific seasonal promotions to improve conversion rates.

  Try Matomo for Free

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

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  Easily create custom cohort reports beyond the time dimension

  If you want to split your audience into cohorts by focusing on something other than time, you will need to create a custom report and choose another dimension. In Matomo, you can choose from a wide range of cohort metrics, including referrers, e-commerce signals like viewed product or product category, form submissions and more.

  

  Then, you can create a simple table-based report with all the insights you need by choosing the metrics you want to see. For example, you could choose average visit duration, bounce rate and other usage metrics.

  

  If you want more revenue-focused insights, add metrics like conversions, add-to-cart and other e-commerce events.

  Custom reports make it easy to create cohort reports for almost any dimension. You can use any metric within demographic and behavioural analytics to create a cohort. (You can explore the complete list of our possible segmentation metrics.)

  We cover different types of custom reports (and ideas for specific marketing campaigns) in our guide on custom segmentation.

  Create your first cohort report and gain better insights into your visitors

  Cohort reports can help you identify trends and the impact of short-term marketing efforts like events and promotions.

  With Matomo cohort reports you have the power to create complex custom reports for various cohorts and segments. 

  If you’re looking for a powerful, easy-to-use web analytics solution that gives you 100% accurate data without compromising your users’ privacy, Matomo is a great fit. Get started with a 21-day free trial today. No credit card required. 

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