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• How to Measure Marketing Effectiveness : A Step-by-Step Guide

  22 février 2024, par Erin

  Are you struggling to prove that your marketing efforts are having a measurable impact on your company’s performance ? We get it. 

  You would think that digital marketing would make it easier to track the effectiveness of your marketing efforts. But in many ways, it’s harder than ever. With so many channels and strategies competing against each other, it can feel impossible to pin down the campaign that caused a conversion. 

  That leaves you in a tricky spot as a marketing manager. It can be hard to know which campaigns to persevere with and harder still to prove your worth to stakeholders. 

  Thankfully, there are several strategies you can use to measure the success of your campaigns and put a value on your efforts. So, if you want to learn how you can measure the effectiveness of your marketing, improve the ROI of your efforts and prove your value as an employee, read on. 

  What is marketing effectiveness ?

  Marketing effectiveness measures how successful a marketing strategy or campaign is and the extent to which it achieves goals and business objectives.

  

  It’s a growing concern for brands, with research showing that 61.2% say measuring marketing effectiveness has become a more prominent factor in decision-making over the last three years. In other words, it’s becoming critical for marketers to know how to measure their effectiveness. 

  But it’s getting harder to do so. A combination of factors, including channel fragmentation, increasingly convoluted customer journeys, and the deprecation of third-party cookies, makes it hard for marketing teams to measure marketing performance. 

  Why you need to measure marketing effectiveness

  Imagine ploughing thousands of dollars into a campaign and not being confident that your efforts bore fruit. It’s unthinkable, right ? If you care about optimising campaigns and improving your worth as a marketer, measuring marketing effectiveness is necessary. 

  

  Optimise marketing campaigns

  Do you know how effectively each campaign generates conversions and drives revenue ? No ? Then, you need to measure marketing effectiveness.

  Doing so could also shine a light on ways to improve your campaigns. One paid ad campaign may suffer from a poor return on ad spend caused by high CPCs. Targeting less competitive keywords could dramatically reduce your costs. 

  Improve ROI

  Today, marketing budgets make up almost 10% of a company’s total revenue, up from 6.4% in 2021. With so much revenue at stake, you’ve got to deliver a return on that investment. 

  Measuring marketing effectiveness can help you identify the campaigns or strategies delivering the highest ROI so you can invest more heavily into them. On the other side of the same coin, you can use the data to strike off any campaigns that aren’t pulling their weight — increasing your ROI even further. 

  Demonstrate value

  Let’s get selfish for a second. Whether you’re an in-house marketing manager or work for an agency, the security of your paycheck depends on your ability to deliver high-ROI campaigns. 

  Measuring your marketing effectiveness lets you showcase your value to your company and clients. It helps you build stronger relationships that can lead to bigger and better opportunities in the future. 

  We should take this opportunity to point out that a good tool for measuring marketing effectiveness is equally important. You probably think Google Analytics will do the job, right ? But when you start implementing the strategies we discuss below, there’s a good chance you’ll have data quality issues. 

  That was the case for full-service marketing agency MHP/Team SI, which found Google Analytics’ data sampling severely limited the quantity and quality of insights they could collect. It was only by switching to Matomo, a platform that doesn’t use data sampling, that the agency could deliver the insights its clients needed to grow. 

  Further reading :

  • How to check website traffic as accurately as possible
  • 8 best tools to analyse website traffic

  Try Matomo for Free

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

  Start for free

  No credit card required

  How to measure marketing effectiveness

  Measuring marketing effectiveness is not always easy, especially if you have long buying cycles and a lack of good-quality data. Make things as easy as possible by following the steps below :

  Know what success looks like

  You can’t tell whether your campaigns are effective if you don’t know what you are trying to achieve. That’s why the first step in measuring marketing effectiveness is to set a clear goal. 

  So, ask yourself what success looks like for each campaign you launch. 

  Remember, a campaign doesn’t have to drive leads to be considered effective. If all you wanted to do was raise brand awareness or increase organic traffic, you could achieve both goals without recording a single conversion. 

  We’d wager that’s probably not true for most marketing managers. It’s much more likely you want to achieve something like the following :

  • Generating 100 new customers
  • Increasing revenue by 20%
  • Selling $5,000 of your new product line
  • Reducing customer churn by 50%
  • Achieving a return on ad spend of 150%

  Conventional goal-setting wisdom applies here. So, ensure your goals are measurable, timely, relevant and achievable. 

  Track conversions

  Setting up conversion tracking in your web analytics platform is vital to measuring marketing effectiveness accurately. 

  What you count as a conversion event will depend on the goals you’ve set above. It doesn’t have to be a sale, mind you. Downloading an ebook or signing up for a webinar are worthy conversion goals, especially if you know they increase the chances of a customer converting. 

  

  Whichever platform you choose, ensure it can meet your current and future needs. This is one of the reasons open-source content management system Concrete CMS opted for Matomo when choosing a new website analytics platform. The flexibility of the Matomo platform gave Concrete CMS the adaptability it needed for future growth. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  Decide on an attribution model

  Marketing attribution is a way of measuring the impact of different channels and touchpoints across the customer journey. If you can assign a value to each conversion, you can use a marketing attribution model to quantify the value of your channels and campaigns.

  While most web analytics platforms simply credit the last touchpoint, marketing attribution offers a more comprehensive view by considering all interactions along the customer journey. This distinction is important because relying solely on the last touchpoint can lead to skewed insights and misallocation of resources and budget. 

  By adopting a marketing attribution approach, you can make more informed decisions, optimizing your campaigns and maximizing your return on investment.

  

  There are several different attribution models you can use to give credit to your various campaigns. These include :

  • First interaction : Gives all the credit to the first channel in the customer journey.
  • Last interaction : Gives all the credit to the last channel in the customer journey.
  • Last non-direct attribution : Gives all credit to the final touchpoint in the customer journey, except for direct interactions. In those cases, credit is given to the touchpoint just before the direct one.
  • Linear attribution : Distributes credit equally across all touchpoints.
  • Position-based attribution : Attributes 40% credit to the first and last touchpoints and distributes the remaining 20% evenly across all other touchpoints. 

  Consider carefully which attribution model to use, as this can significantly impact your marketing effectiveness calculation by giving certain campaigns too much credit.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Analyse KPIs

  Tracking KPIs is essential if you want to quantify the impact of your marketing campaigns. But which metrics should you track ?

  To improve brand awareness or traffic, so-called vanity metrics like sessions, returning visitors, and organic traffic may suffice as KPIs. 

  However, that’s not going to be the case for most marketers, whose performance is tied to revenue and ROI. If that’s you, put vanity metrics to one side and focus on the following conversion metrics instead :

  • Conversion rate : the percentage of users who complete a desired action. 
  • Return on ad spend : the revenue earned for every dollar spent on a campaign.
  • Return on investment : a broader calculation than ROAS, typically calculated across all your marketing efforts. 
  • Customer lifetime value : the total amount a customer will spend throughout their relationship with your company.
  • Customer acquisition cost : the cost to acquire each customer on average.

  

  Your analytics platform and advertising tools should track most of these KPIs by default. Matomo, for instance, automatically calculates your conversion rate in the Goals report. 

  How to present your marketing effectiveness

  Calculating your marketing effectiveness is one thing, but it’s important to share this information with stakeholders — whether those are executives in your company or your agency’s clients. 

  Follow the steps below to create an insightful and compelling marketing report :

  • Set the scene. There’s no guarantee that the people reading your report will know your goals. So, add context at the start of the reporting by spelling out what you are trying to achieve and why. 
  • Select the right data. You don’t want to overwhelm the reader with facts and figures, but you do need to provide hard evidence of your success. Include the KPIs you used to measure your success and show how these have changed over time. You can also support your report with audience insights such as heatmaps or customer surveys.
  • Tell a story with your presentation. Give your presentation a narrative arc with a beginning, middle, and end. Start with what you want to achieve, describe how you plan to achieve it and end with the results. Support your story with graphs and other visual aids that hold your reader’s attention. 
  • Provide a concise summary. Not everyone will read your presentation cover to cover. With that in mind, provide a summary of your report at the start or end that shows what you achieved and quantifies your marketing effectiveness. 

  How to improve marketing effectiveness

  Don’t settle for simply measuring your marketing effectiveness. Use the following strategies to make future campaigns as effective as possible. 

  Understand customer behaviour

  More effective marketing campaigns start by deeply understanding your customers, who they are, and how they behave. This allows you to take an audience-first approach to your marketing efforts and design campaigns around the unique needs of your customers. 

  Gather as much first-party data as you can. Surveys, focus groups, and other market research techniques can help you learn more about who your customers are, but don’t disregard the quantitative data you can gather from your web analytics platform. 

  Using Heatmaps, Session Recordings and behavioural analytics tools, you can learn exactly how customers behave when they land on your site, where they focus their attention and which pages they look at first. 

  

  These insights can help you turn an average campaign into an exceptional one. For example, a heatmap may highlight the need to move CTA buttons above the fold to increase conversions. A session recording could pinpoint the problems users have when filling out your website’s forms. 

  Further reading :

  • What Is Behavioural Analytics & How Can It Improve Website Performance
  • 9 Form Optimisation Tips to Convert More Visitors
  • How to Increase Conversions with Form Analysis

  Optimise landing pages

  Developing a culture of testing and experimentation is a great way to improve your marketing effectiveness. Let’s dive into A/B testing.

  By tweaking various elements of your landing pages, you can squeeze every last conversion from your campaigns.

  

  We have a guide on conversion funnel optimisation, which we recommend you check out, but I’ll briefly list some of the optimisations you could test :

  • Making your CTAs actionable and compelling
  • Integrating images and videos
  • Adding testimonials and other forms of social proof
  • Reducing form fields

  Use a different attribution model

  It might be that some campaigns, strategies or traffic sources aren’t getting the love they deserve. By changing your attribution model, you can significantly change the perceived effectiveness of certain campaigns. 

  Let’s say you use a last-touch attribution model, for instance. Only the last channel customers will get credit for each conversion, meaning top-of-the-funnel campaigns like SEO may be deemed less effective than they are. 

  It’s why you must continually test, tweak and validate your chosen model — and why changing it can be so powerful. 

  Measure your marketing effectiveness with Matomo

  Measuring your marketing effectiveness is hard work. But it’s vital to optimise campaigns, improve your ROI and demonstrate your value. 

  The good news is that Matomo makes things a lot easier thanks to its comprehensive conversion tracking, attribution modelling capabilities and behavioural insight features like Heatmaps, A/B Testing and Session Recordings. 

  Take steps today to start measuring (and improving) the effectiveness of your marketing with our 21-day free trial. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• Attribution Tracking (What It Is and How It Works)

  23 février 2024, par Erin

  Facebook, TikTok, Google, email, display ads — which one is best to grow your business ? There’s one proven way to figure it out : attribution tracking.

  Marketing attribution allows you to see which channels are producing the best results for your marketing campaigns.

  In this guide, we’ll show you what attribution tracking is, why it’s important and how you can leverage it to accelerate your marketing success.

  What is attribution tracking ?

  By 2026, the global digital marketing industry is projected to reach $786.2 billion.

  With nearly three-quarters of a trillion U.S. dollars being poured into digital marketing every year, there’s no doubt it dominates traditional marketing.

  The question is, though, how do you know which digital channels to use ?

  By measuring your marketing efforts with attribution tracking.

  

  So, what is attribution tracking ?

  Attribution tracking is where you use software to keep track of different channels and campaign efforts to determine which channel you should attribute conversion to.

  In other words, you can (and should) use attribution tracking to analyse which channels are pushing the needle and which ones aren’t.

  By tracking your marketing efforts, you’ll be able to accurately measure the scale of impact each of your channels, campaigns and touchpoints have on a customer’s purchasing decision.

  If you don’t track your attribution, you’ll end up blindly pouring time, money, and effort into activities that may or may not be helpful.

  Attribution tracking simply gives you insight into what you’re doing right as a marketer — and what you’re doing wrong.

  By understanding which efforts and channels are driving conversions and revenue, you’ll be able to properly allocate resources toward winning channels to double down on growth.

  Matomo lets you track attribution across various channels. Whether you’re looking to track your conversions through organic, referral websites, campaigns, direct traffic, or social media, you can see all your conversions in one place.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Why attribution tracking is important

  Attribution tracking is crucial to succeed with your marketing since it shows you your most valuable channels.

  It takes the guesswork out of your efforts.

  You don’t need to scratch your head wondering what made your campaigns a success (or a failure).

  While most tools show you last click attribution by default, using attribution tracking, or marketing attribution, you can track revenue and conversions for each touchpoint.

  For example, a Facebook ad might have no led to a conversion immediately. But, maybe the visitor returned to your website two weeks later through your email campaign. Attribution tracking will give credit over longer periods of time to see the bigger picture of how your marketing channels are impacting your overall performance.

  Here are five reasons you need to be using attribution tracking in your business today :

  

  1. Measure channel performance

  The most obvious way attribution tracking helps is to show you how well each channel performs.

  When you’re using a variety of marketing channels to reach your audience, you have to know what’s actually doing well (and what’s not).

  This means having clarity on the performance of your :

  • Emails
  • Google Ads
  • Facebook Ads
  • Social media marketing
  • Search engine optimisation (SEO)
  • And more

  Attribution tracking allows you to measure each channel’s ROI and identify how much each channel impacted your campaigns.

  It gives you a more accurate picture of the performance of each channel and each campaign.

  With it, you can easily break down your channels by how much they drove sales, conversions, signups, or other actions.

  With this information, you can then understand where to further allocate your resources to fuel growth.

  2. See campaign performance over longer periods of time

  When you start tracking your channel performance with attribution tracking, you’ll gain new insights into how well your channels and campaigns are performing.

  The best part — you don’t just get to see recent performance.

  You get to track your campaign results over weeks or months.

  For example, if someone found you through Google by searching a question that your blog had an answer to, but they didn’t convert, your traditional tracking strategy would discount SEO.

  But, if that same person clicked a TikTok ad you placed three weeks later, came back, and converted — SEO would receive some attribution on the conversion.

  Using an attribution tracking tool like Matomo can help paint a holistic view of how your marketing is really doing from channel to channel over the long run.

  Try Matomo for Free

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

  Start for free

  No credit card required

  3. Increase revenue

  Attribution tracking has one incredible benefit for marketers : optimised marketing spend.

  When you begin looking at how well your campaigns and your channels are performing, you’ll start to see what’s working.

  Attribution tracking gives you clarity into the performance of campaigns since it’s not just looking at the first time someone clicks through to your site. It’s looking at every touchpoint a customer made along the way to a conversion.

  By understanding what channels are most effective, you can pour more resources like time, money and labour into those effective channels.

  By doubling down on the winning channels, you’ll be able to grow like never before.

  Rather than trying to “diversify” your marketing efforts, lean into what’s working.

  This is one of the key strategies of an effective marketer to maximise your campaign returns and experience long-term success in terms of revenue.

  4. Improve profit margins

  The final benefit to attribution tracking is simple : you’ll earn more profit.

  Think about it this way : let’s say you’re putting 50% of your marketing spend into Facebook ads and 50% of your spend into email marketing.

  You do this for one year, allocating $500,000 to Facebook and $500,000 to email.

  Then, you start tracking attribution.

  You find that your Facebook ads are generating $900,000 in revenue. 

  That’s a 1,800% return on your investment.

  Not bad, right ?

  Well, after tracking your attribution, you see what your email revenue is.

  In the past year, you generated $1.7 million in email revenue.

  That’s a 3,400% return on your investment (close to the average return of email marketing across all industries).

  In this scenario, you can see that you’re getting nearly twice as much of a return on your marketing spend with email.

  So, the following year, you decide to go for a 75/25 split.

  Instead of putting $500,000 into both email and Facebook ads and email, you put $750,000 into email and $250,000 into Facebook ads.

  You’re still diversifying, but you’re doubling down on what’s working best.

  The result is that you’ll be able to get more revenue by investing the same amount of money, leaving you with higher profit margins.

  Different types of marketing attribution tracking

  There are several types of attribution tracking models in marketing.

  Depending on your goals, your business and your preferred method, there are a variety of types of attribution tracking you can use.

  Here are the six main types of attribution tracking :

  

  1. Last interaction

  Last interaction attribution model is also called “last touch.”

  It’s one of the most common types of attribution. The way it works is to give 100% of the credit to the final channel a customer interacted with before they converted into a customer.

  This could be through a paid ad, direct traffic, or organic search.

  One potential drawback of last interaction is that it doesn’t factor in other channels that may have assisted in the conversion. However, this model can work really well depending on the business.

  2. First interaction

  This is the opposite of the previous model.

  First interaction, or “first touch,” is all about the first interaction a customer has with your brand.

  It gives 100% of the credit to the channel (i.e. a link clicked from a social media post). And it doesn’t report or attribute anything else to another channel that someone may have interacted with in your marketing mix.

  For example, it won’t attribute the conversion or revenue if the visitor then clicked on an Instagram ad and converted. All credit would be given to the first touch which in this case would be the social media post. 

  The first interaction is a good model to use at the top of your funnel to help establish which channels are bringing leads in from outside your audience.

  3. Last non-direct

  Another model is called the last non-direct attribution model. 

  This model seeks to exclude direct traffic and assigns 100% credit for a conversion to the final channel a customer interacted with before becoming a customer, excluding clicks from direct traffic.

  For instance, if someone first comes to your website from an emai campaignl, and then, a week later, directly visits and buys a product, the email campaign gets all the credit for the sale.

  This attribution model tells a bit more about the whole sales process, shedding some more light on what other channels may have influenced the purchase decision.

  4. Linear

  Another common attribution model is linear.

  This model distributes completely equal credit across every single touchpoint (that’s tracked). 

  Imagine someone comes to your website in different ways : first, they find it through a Google search, then they click a link in an email from your campaign the next day, followed by visiting from a Facebook post a few days later, and finally, a week later, they come from a TikTok ad. 

  Here’s how the attribution is divided among these sources :

  • 25% Organic
  • 25% Email
  • 25% Facebook
  • 25% TikTok ad

  This attirubtion model provides a balanced perspective on the contribution of various sources to a user’s journey on your website.

  5. Position-based

  Position-based attribution is when you give 40% credit to both the first and last touchpoints and 20% credit is spread between the touchpoints in between.

  This model is preferred if you want to identify the initial touchpoint that kickstarted a conversion journey and the final touchpoint that sealed the deal.

  The downside is that you don’t gain much insight into the middle of the customer journey, which can make it hard to make effective decisions.

  For example, someone may have been interacting with your email newsletter for seven weeks, which allowed them to be nurtured and build a relationship with you.

  But that relationship and trust-building effort will be overlooked by the blog post that brought them in and the social media ad that eventually converted them.

  6. Time decay

  The final attribution model is called time decay attribution.

  This is all about giving credit based on the timing of the interactions someone had with your brand.

  For example, the touchpoints that just preceded the sale get the highest score, while the first touchpoints get the lowest score.

  For example, let’s use that scenario from above with the linear model :

  • 25% SEO
  • 25% Email
  • 25% Facebook ad
  • 25% Organic TikTok

  But, instead of splitting credit by 25% to each channel, you weigh the ones closer to the sale with more credit.

  Instead, time decay may look at these same channels like this :

  • 5% SEO (6 weeks ago)
  • 20% Email (3 weeks ago)
  • 30% Facebook ad (1 week ago)
  • 45% Organic TikTok (2 days ago)

  One downside is that it underestimates brand awareness campaigns. And, if you have longer sales cycles, it also isn’t the most accurate, as mid-stage nurturing and relationship building are underlooked. 

  Leverage Matomo : A marketing attribution tool

  Attribution tracking is a crucial part of leading an effective marketing strategy.

  But it’s impossible to do this without the right tools.

  A marketing attribution tool can give you insights into your best-performing channels automatically. 

  

  One of the best marketing attribution tools available is Matomo, a web analytics tool that helps you understand what’s going on with your website and different channels in one easy-to-use dashboard.

  With Matomo, you get marketing attribution as a plug-in or within Matomo On-Premise or for free in Matomo Cloud.

  The best part is it’s all done with crystal-clear data. Matomo gives you 100% accurate data since it doesn’t use data sampling on any plans like Google Analytics.

  To start tracking attribution today, try Matomo’s 21-day free trial. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• When I use ffmpeg to go from a video to frames, and then back to video, the duration is different between the videos

  24 février 2024, par bluepanda

  I am trying to use ffmpeg to convert from a .mp4 (or .mov) video into individual frames, do some processing on those frames, and then convert back to .mp4. The problem is that the resulting video I create is a different duration than the input - I can see this visually when I play the two videos side by side. The difference is not large (i.e. 00:00:00.50 for the input video and 00:00:00.52 for the output video), but when the videos are looped next to each other they get out of sync.

  


  Here is information about the input video retrieved using fluent-ffmpeg's ffmpeg.ffprobe(videoPath) :

  


  metadata {
  streams: [
    {
      index: 0,
      codec_name: 'h264',
      codec_long_name: 'H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10',
      profile: 'High',
      codec_type: 'video',
      codec_tag_string: 'avc1',
      codec_tag: '0x31637661',
      width: 1080,
      height: 1920,
      coded_width: 1080,
      coded_height: 1920,
      closed_captions: 0,
      has_b_frames: 2,
      sample_aspect_ratio: 'N/A',
      display_aspect_ratio: 'N/A',
      pix_fmt: 'yuv420p',
      level: 40,
      color_range: 'tv',
      color_space: 'bt709',
      color_transfer: 'bt709',
      color_primaries: 'bt709',
      chroma_location: 'left',
      field_order: 'unknown',
      refs: 1,
      is_avc: 'true',
      nal_length_size: 4,
      id: 'N/A',
      r_frame_rate: '30000/1001',
      avg_frame_rate: '27000/1001',
      time_base: '1/30000',
      start_pts: 0,
      start_time: 0,
      duration_ts: 15100,
      duration: 0.503333,
      bit_rate: 5660223,
      max_bit_rate: 'N/A',
      bits_per_raw_sample: 8,
      nb_frames: 36,
      nb_read_frames: 'N/A',
      nb_read_packets: 'N/A',
      tags: [Object],
      disposition: [Object]
    },
    {
      index: 1,
      codec_name: 'aac',
      codec_long_name: 'AAC (Advanced Audio Coding)',
      profile: 'LC',
      codec_type: 'audio',
      codec_tag_string: 'mp4a',
      codec_tag: '0x6134706d',
      sample_fmt: 'fltp',
      sample_rate: 48000,
      channels: 2,
      channel_layout: 'stereo',
      bits_per_sample: 0,
      id: 'N/A',
      r_frame_rate: '0/0',
      avg_frame_rate: '0/0',
      time_base: '1/48000',
      start_pts: 0,
      start_time: 0,
      duration_ts: 24160,
      duration: 0.503333,
      bit_rate: 248416,
      max_bit_rate: 'N/A',
      bits_per_raw_sample: 'N/A',
      nb_frames: 27,
      nb_read_frames: 'N/A',
      nb_read_packets: 'N/A',
      tags: [Object],
      disposition: [Object]
    }
  ],
  format: {
    filename: '/Users/name/images/input.mp4',
    nb_streams: 2,
    nb_programs: 0,
    format_name: 'mov,mp4,m4a,3gp,3g2,mj2',
    format_long_name: 'QuickTime / MOV',
    start_time: 0,
    duration: 0.503333,
    size: 963879,
    bit_rate: 15319941,
    probe_score: 100,
    tags: {
      major_brand: 'mp42',
      minor_version: '1',
      compatible_brands: 'isommp41mp42',
      creation_time: '2024-02-14T01:21:12.000000Z'
    }
  },
  chapters: []
}


  


  and here is from running ffprobe directly :

  


  ffprobe '/Users/name/images/input.mp4'
ffprobe version 6.1.1 Copyright (c) 2007-2023 the FFmpeg developers
  built with Apple clang version 15.0.0 (clang-1500.1.0.2.5)
  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.1.1_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libharfbuzz --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libssh --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopenvino --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon
  libavutil      58. 29.100 / 58. 29.100
  libavcodec     60. 31.102 / 60. 31.102
  libavformat    60. 16.100 / 60. 16.100
  libavdevice    60.  3.100 / 60.  3.100
  libavfilter     9. 12.100 /  9. 12.100
  libswscale      7.  5.100 /  7.  5.100
  libswresample   4. 12.100 /  4. 12.100
  libpostproc    57.  3.100 / 57.  3.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/Users/name/images/input.mp4':
  Metadata:
    major_brand     : mp42
    minor_version   : 1
    compatible_brands: isommp41mp42
    creation_time   : 2024-02-14T01:21:12.000000Z
  Duration: 00:00:00.50, start: 0.000000, bitrate: 15319 kb/s
  Stream #0:0[0x1](und): Video: h264 (High) (avc1 / 0x31637661), yuv420p(tv, bt709, progressive), 1080x1920, 5660 kb/s, 26.97 fps, 29.97 tbr, 30k tbn (default)
    Metadata:
      creation_time   : 2024-02-14T01:21:12.000000Z
      handler_name    : Core Media Video
      vendor_id       : [0][0][0][0]
      encoder         : AVC Coding
  Stream #0:1[0x2](und): Audio: aac (LC) (mp4a / 0x6134706D), 48000 Hz, stereo, fltp, 248 kb/s (default)
    Metadata:
      creation_time   : 2024-02-14T01:21:12.000000Z
      handler_name    : Core Media Audio
      vendor_id       : [0][0][0][0]


  


  And this is my command to go from video to frames :

  


  ffmpeg -i /Users/name/images/input.mp4 -y -f image2 /Users/name/images/frames/%d.png


  


  After which I convert the frames back to video with this - note that I get by seeing avg_frame_rate is 27000/1001 = 26.97302697 :

  


  ffmpeg -r 26.973026973026972 -i /Users/name/images/frames/%d.png -y -r 26.973026973026972 -b:v 5660223k -f mp4 -pix_fmt yuv420p -t 0.503333 /Users/name/images/output.mp4


  


  And if I then run fluent-ffmpeg's ffmpeg.ffprobe(videoPath) I get :

  


  metadata {
  streams: [
    {
      index: 0,
      codec_name: 'h264',
      codec_long_name: 'H.264 / AVC / MPEG-4 AVC / MPEG-4 part 10',
      profile: 'High',
      codec_type: 'video',
      codec_tag_string: 'avc1',
      codec_tag: '0x31637661',
      width: 1080,
      height: 1920,
      coded_width: 1080,
      coded_height: 1920,
      closed_captions: 0,
      has_b_frames: 2,
      sample_aspect_ratio: '1:1',
      display_aspect_ratio: '9:16',
      pix_fmt: 'yuv420p',
      level: 62,
      color_range: 'unknown',
      color_space: 'unknown',
      color_transfer: 'unknown',
      color_primaries: 'unknown',
      chroma_location: 'left',
      field_order: 'unknown',
      refs: 1,
      is_avc: 'true',
      nal_length_size: 4,
      id: 'N/A',
      r_frame_rate: '27000/1001',
      avg_frame_rate: '27000/1001',
      time_base: '1/27000',
      start_pts: 0,
      start_time: 0,
      duration_ts: 14014,
      duration: 0.519037,
      bit_rate: 52138429,
      max_bit_rate: 'N/A',
      bits_per_raw_sample: 8,
      nb_frames: 14,
      nb_read_frames: 'N/A',
      nb_read_packets: 'N/A',
      tags: [Object],
      disposition: [Object]
    }
  ],
  format: {
    filename: '/Users/name/images/output.mp4',
    nb_streams: 1,
    nb_programs: 0,
    format_name: 'mov,mp4,m4a,3gp,3g2,mj2',
    format_long_name: 'QuickTime / MOV',
    start_time: 0,
    duration: 0.52,
    size: 3383708,
    bit_rate: 52057046,
    probe_score: 100,
    tags: {
      major_brand: 'isom',
      minor_version: '512',
      compatible_brands: 'isomiso2avc1mp41',
      encoder: 'Lavf60.3.100'
    }
  },
  chapters: []
}


  


  and here is from running ffprobe directly :

  


  ffprobe '/Users/name/images/output.mp4'
ffprobe version 6.1.1 Copyright (c) 2007-2023 the FFmpeg developers
  built with Apple clang version 15.0.0 (clang-1500.1.0.2.5)
  configuration: --prefix=/opt/homebrew/Cellar/ffmpeg/6.1.1_2 --enable-shared --enable-pthreads --enable-version3 --cc=clang --host-cflags= --host-ldflags='-Wl,-ld_classic' --enable-ffplay --enable-gnutls --enable-gpl --enable-libaom --enable-libaribb24 --enable-libbluray --enable-libdav1d --enable-libharfbuzz --enable-libjxl --enable-libmp3lame --enable-libopus --enable-librav1e --enable-librist --enable-librubberband --enable-libsnappy --enable-libsrt --enable-libssh --enable-libsvtav1 --enable-libtesseract --enable-libtheora --enable-libvidstab --enable-libvmaf --enable-libvorbis --enable-libvpx --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libxvid --enable-lzma --enable-libfontconfig --enable-libfreetype --enable-frei0r --enable-libass --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopenvino --enable-libspeex --enable-libsoxr --enable-libzmq --enable-libzimg --disable-libjack --disable-indev=jack --enable-videotoolbox --enable-audiotoolbox --enable-neon
  libavutil      58. 29.100 / 58. 29.100
  libavcodec     60. 31.102 / 60. 31.102
  libavformat    60. 16.100 / 60. 16.100
  libavdevice    60.  3.100 / 60.  3.100
  libavfilter     9. 12.100 /  9. 12.100
  libswscale      7.  5.100 /  7.  5.100
  libswresample   4. 12.100 /  4. 12.100
  libpostproc    57.  3.100 / 57.  3.100
Input #0, mov,mp4,m4a,3gp,3g2,mj2, from '/Users/name/images/output.mp4':
  Metadata:
    major_brand     : isom
    minor_version   : 512
    compatible_brands: isomiso2avc1mp41
    encoder         : Lavf60.3.100
  Duration: 00:00:00.52, start: 0.000000, bitrate: 52153 kb/s
  Stream #0:0[0x1](und): Video: h264 (High) (avc1 / 0x31637661), yuv420p(progressive), 1080x1920 [SAR 1:1 DAR 9:16], 52138 kb/s, 26.97 fps, 26.97 tbr, 27k tbn (default)
    Metadata:
      handler_name    : VideoHandler
      vendor_id       : [0][0][0][0]
      encoder         : Lavc60.3.100 libx264


  


  This seems like it should be a fairly common scenario, but I have not been able to find examples of this, and the other questions about incorrect durations on Stack Overflow are about bigger differences (i.e. 3 seconds instead of 10 seconds : Wrong video duration when recording with ffmpeg).

  


  Some other details :

  


  

  • I am running this through a Node.js script with fluent-ffmpeg, but I have also tried running the commands directly in the terminal and the result is the same.

  


  • I am fine with the output frames being .png / .jpg / other formats.

  


  • I am fine with setting this to a different frame rate than the original as long as the two output videos end up with the same duration.

  


  • One suspicious thing is that I set -t 0.503333 when creating the video, but it doesn't seem to work as the result video shows duration: 0.519037 / 00:00:00.52.

  


  


  Thank you for any help !