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• What is Audience Segmentation ? The 5 Main Types & Examples

  16 novembre 2023, par Erin — Analytics Tips

  The days of mass marketing with the same message for millions are long gone. Today, savvy marketers instead focus on delivering the most relevant message to the right person at the right time.

  They do this at scale by segmenting their audiences based on various data points. This isn’t an easy process because there are many types of audience segmentation. If you take the wrong approach, you risk delivering irrelevant messages to your audience — or breaking their trust with poor data management.

  In this article, we’ll break down the most common types of audience segmentation, share examples highlighting their usefulness and cover how you can segment campaigns without breaking data regulations.

  What is audience segmentation ?

  Audience segmentation is when you divide your audience into multiple smaller specific audiences based on various factors. The goal is to deliver a more targeted marketing message or to glean unique insights from analytics.

  It can be as broad as dividing a marketing campaign by location or as specific as separating audiences by their interests, hobbies and behaviour.

  

  Audience segmentation inherently makes a lot of sense. Consider this : an urban office worker and a rural farmer have vastly different needs. By targeting your marketing efforts towards agriculture workers in rural areas, you’re honing in on a group more likely to be interested in farm equipment. 

  Audience segmentation has existed since the beginning of marketing. Advertisers used to select magazines and placements based on who typically read them. They would run a golf club ad in a golf magazine, not in the national newspaper.

  How narrow you can make your audience segments by leveraging multiple data points has changed.

  Why audience segmentation matters

  In a survey by McKinsey, 71% of consumers said they expected personalisation, and 76% get frustrated when a vendor doesn’t deliver.

  

  These numbers reflect expectations from consumers who have actively engaged with a brand — created an account, signed up for an email list or purchased a product.

  They expect you to take that data and give them relevant product recommendations — like a shoe polishing kit if you bought nice leather loafers.

  If you don’t do any sort of audience segmentation, you’re likely to frustrate your customers with post-sale campaigns. If, for example, you just send the same follow-up email to all customers, you’d damage many relationships. Some might ask : “What ? Why would you think I need that ?” Then they’d promptly opt out of your email marketing campaigns.

  To avoid that, you need to segment your audience so you can deliver relevant content at all stages of the customer journey.

  5 key types of audience segmentation

  To help you deliver the right content to the right person or identify crucial insights in analytics, you can use five types of audience segmentation : demographic, behavioural, psychographic, technographic and transactional.

  

  Demographic segmentation 

  Demographic segmentation is when you segment a larger audience based on demographic data points like location, age or other factors.

  The most basic demographic segmentation factor is location, which is easy to leverage in marketing efforts. For example, geographic segmentation can use IP addresses and separate marketing efforts by country. 

  But more advanced demographic data points are becoming increasingly sensitive to handle. Especially in Europe, GDPR makes advanced demographics a more tentative subject. Using age, education level and employment to target marketing campaigns is possible. But you need to navigate this terrain thoughtfully and responsibly, ensuring meticulous adherence to privacy regulations.

  Potential data points :

  • Location
  • Age
  • Marital status
  • Income
  • Employment 
  • Education

  Example of effective demographic segmentation :

  A clothing brand targeting diverse locations needs to account for the varying weather conditions. In colder regions, showcasing winter collections or insulated clothing might resonate more with the audience. Conversely, in warmer climates, promoting lightweight or summer attire could be more effective. 

  Here are two ads run by North Face on Facebook and Instagram to different audiences to highlight different collections :

  

  Each collection is featured differently and uses a different approach with its copy and even the media. With social media ads, targeting people based on advanced demographics is simple enough — you can just single out the factors when making your campaign. But if you don’t want to rely on these data-mining companies, that doesn’t mean you have no options for segmentation.

  Consider allowing people to self-select their interests or preferences by incorporating a short survey within your email sign-up form. This simple addition can enhance engagement, decrease bounce rates, and ultimately improve conversion rates, offering valuable insights into audience preferences.

  This is a great way to segment ethically and without the need of data-mining companies.

  Behavioural segmentation

  Behavioural segmentation segments audiences based on their interaction with your website or app.

  You use various data points to segment your target audience based on their actions.

  Potential data points :

  • Page visits
  • Referral source
  • Clicks
  • Downloads
  • Video plays
  • Goal completion (e.g., signing up for a newsletter or purchasing a product)

  Example of using behavioural segmentation to improve campaign efficiency :

  One effective method involves using a web analytics tool such as Matomo to uncover patterns. By segmenting actions like specific clicks and downloads, pinpoint valuable trends—identifying actions that significantly enhance visitor conversions. 

  

  For instance, if a case study video substantially boosts conversion rates, elevate its prominence to capitalise on this success.

  Then, you can set up a conditional CTA within the video player. Make it pop up after the user has watched the entire video. Use a specific form and sign them up to a specific segment for each case study. This way, you know the prospect’s ideal use case without surveying them.

  This is an example of behavioural segmentation that doesn’t rely on third-party cookies.

  Psychographic segmentation

  Psychographic segmentation is when you segment audiences based on your interpretation of their personality or preferences.

  Potential data points :

  • Social media patterns
  • Follows
  • Hobbies
  • Interests

  Example of effective psychographic segmentation :

  Here, Adidas segments its audience based on whether they like cycling or rugby. It makes no sense to show a rugby ad to someone who’s into cycling and vice versa. But to rugby athletes, the ad is very relevant.

  

  If you want to avoid social platforms, you can use surveys about hobbies and interests to segment your target audience in an ethical way.

  Technographic segmentation

  Technographic segmentation is when you single out specific parts of your audience based on which hardware or software they use.

  Potential data points :

  • Type of device used
  • Device model or brand
  • Browser used

  Example of segmenting by device type to improve user experience :

  Upon noticing a considerable influx of tablet users accessing their platform, a leading news outlet decided to optimise their tablet browsing experience. They overhauled the website interface, focusing on smoother navigation and better readability for tablet users. These changes offered tablet users a seamless and enjoyable reading experience tailored precisely to their device.

  Transactional segmentation

  Transactional segmentation is when you use your customers’ purchase history to better target your marketing message to their needs.

  When consumers prefer personalisation, they typically mean based on their actual transactions, not their social media profiles.

  Potential data points :

  • Average order value
  • Product categories purchased within X months
  • X days since the last purchase of a consumable product

  Example of effective transactional segmentation :

  A pet supply store identifies a segment of customers consistently purchasing cat food but not other pet products. They create targeted email campaigns offering discounts or loyalty rewards specifically for cat-related items to encourage repeat purchases within this segment.

  If you want to improve customer loyalty and increase revenue, the last thing you should do is send generic marketing emails. Relevant product recommendations or coupons are the best way to use transactional segmentation.

  B2B-specific : Firmographic segmentation

  Beyond the five main segmentation types, B2B marketers often use “firmographic” factors when segmenting their campaigns. It’s a way to segment campaigns that go beyond the considerations of the individual.

  Potential data points :

  • Company size
  • Number of employees
  • Company industry
  • Geographic location (office)

  Example of effective firmographic segmentation :

  Companies of different sizes won’t need the same solution — so segmenting leads by company size is one of the most common and effective examples of B2B audience segmentation.

  The difference here is that B2B campaigns are often segmented through manual research. With an account-based marketing approach, you start by researching your potential customers. You then separate the target audience into smaller segments (or even a one-to-one campaign).

  Start segmenting and analysing your audience more deeply with Matomo

  Segmentation is a great place to start if you want to level up your marketing efforts. Modern consumers expect to get relevant content, and you must give it to them.

  But doing so in a privacy-sensitive way is not always easy. You need the right approach to segment your customer base without alienating them or breaking regulations.

  That’s where Matomo comes in. Matomo champions privacy compliance while offering comprehensive insights and segmentation capabilities. With robust privacy controls and cookieless configuration, it ensures GDPR and other regulations are met, empowering data-driven decisions without compromising user privacy.

  Take advantage of our 21-day free trial to get insights that can help you improve your marketing strategy and better reach your target audience. No credit card required.

• FFMPEG- Streaming Stops after few seconds

  25 mars 2019, par Manjot Singh Kalsi

  Hi there dear community

  This is the thing that I am dealing with, since last few days. After thorough search in the ffmpeg community, I was unable to find the solution. I am unable to Stream local flv, to facebook rtmp server.

  I am running the following command to stream my local flv video to the rtmp server of Facebook for Live-Streaming of my local File.

  ```ffmpeg -re -i SampleM.flv -acodec libmp3lame  -ar 44100 -b:a 128k -pix_fmt yuv420p -profile:v baseline -s 426x240 -bufsize 6000k -vb 400k -maxrate 1500k -deinterlace -vcodec libx264 -preset veryfast -g 30 -r 30 -f flv "rtmp://live-api.facebook.com:80/rtmp/my_key"```

  It has been a misfortune-situation that even after reading ffmpeg documentation, I have been unable to find the issue that is leading me to this situation as follows.

  I am still missing something that i need to know.

  Following is the log to the execution of the above command.

  ```ffmpeg version N-91024-g293a6e8332 Copyright (c) 2000-2018 the FFmpeg developers
  
    built with gcc 7.3.0 (GCC)
  
    configuration: --enable-gpl --enable-version3 --enable-sdl2 --enable-bzlib --enable-fontconfig --enable-gnutls --enable-iconv --enable-libass --enable-libbluray --enable-libfreetype --enable-libmp3lame --enable-libopencore-amrnb --enable-libopencore-amrwb --enable-libopenjpeg --enable-libopus --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libtheora --enable-libtwolame --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx264 --enable-libx265 --enable-libxml2 --enable-libzimg --enable-lzma --enable-zlib --enable-gmp --enable-libvidstab --enable-libvorbis --enable-libvo-amrwbenc --enable-libmysofa --enable-libspeex --enable-libxvid --enable-libaom --enable-libmfx --enable-amf --enable-ffnvcodec --enable-cuvid --enable-d3d11va --enable-nvenc --enable-nvdec --enable-dxva2 --enable-avisynth
  
    libavutil      56. 18.100 / 56. 18.100
  
    libavcodec     58. 19.101 / 58. 19.101
  
    libavformat    58. 13.102 / 58. 13.102
  
    libavdevice    58.  4.100 / 58.  4.100
  
    libavfilter     7. 21.100 /  7. 21.100
  
    libswscale      5.  2.100 /  5.  2.100
  
    libswresample   3.  2.100 /  3.  2.100
  
    libpostproc    55.  2.100 / 55.  2.100
  
  Input #0, flv, from '.\video.flv':
  
    Metadata:
  
      audiodelay      : 0
  
      canSeekToEnd    : 1
  
      creationdate    : Fri Feb 03 11:52:46 2006
  
                      :
  
    Duration: 00:00:16.92, start: 0.000000, bitrate: 316 kb/s
  
      Stream #0:0: Audio: mp3, 22050 Hz, stereo, fltp, 40 kb/s
  
      Stream #0:1: Video: vp6f, 1 reference frame, yuv420p, 360x288 (368x288), 266 kb/s, 25 fps, 25 tbr, 1k tbn
  
  Stream mapping:
  
    Stream #0:1 -> #0:0 (vp6f (native) -> h264 (libx264))
  
    Stream #0:0 -> #0:1 (mp3 (mp3float) -> mp3 (libmp3lame))
  
  Press [q] to stop, [?] for help
  
  [graph_1_in_0_0 @ 0000020c0bcc4200] tb:1/22050 samplefmt:fltp samplerate:22050 chlayout:0x3
  
  [format_out_0_1 @ 0000020c0bca2cc0] auto-inserting filter 'auto_resampler_0' between the filter 'Parsed_anull_0' and the filter 'format_out_0_1'
  
  [auto_resampler_0 @ 0000020c0bca5140] ch:2 chl:stereo fmt:fltp r:22050Hz -> ch:2 chl:stereo fmt:fltp r:44100Hz
  
  [graph 0 input from stream 0:1 @ 0000020c0c4f4600] w:360 h:288 pixfmt:yuv420p tb:1/1000 fr:25/1 sar:0/1 sws_param:flags=2
  
  [scaler_out_0_0 @ 0000020c0c4f73c0] w:426 h:240 flags:'bicubic' interl:0
  
  [scaler_out_0_0 @ 0000020c0c4f73c0] w:360 h:288 fmt:yuv420p sar:0/1 -> w:426 h:240 fmt:yuv420p sar:0/1 flags:0x4
  
  [libx264 @ 0000020c0bc80600] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX FMA3 BMI2 AVX2
  
  [libx264 @ 0000020c0bc80600] profile Constrained Baseline, level 3.0
  
  [libx264 @ 0000020c0bc80600] 264 - core 155 r2901 7d0ff22 - H.264/MPEG-4 AVC codec - Copyleft 2003-2018 - http://www.videolan.org/x264.html - options: cabac=0 ref=1 deblock=1:0:0 analyse=0x1:0x111 me=hex subme=2 psy=1 psy_rd=1.00:0.00 mixed_ref=0 me_range=16 chroma_me=1 trellis=0 8x8dct=0 cqm=0 deadzone=21,11 fast_pskip=1 chroma_qp_offset=0 threads=7 lookahead_threads=1 sliced_threads=0 nr=0 decimate=1 interlaced=0 bluray_compat=0 constrained_intra=0 bframes=0 weightp=0 keyint=30 keyint_min=3 scenecut=40 intra_refresh=0 rc_lookahead=10 rc=abr mbtree=1 bitrate=400 ratetol=1.0 qcomp=0.60 qpmin=0 qpmax=69 qpstep=4 vbv_maxrate=1500 vbv_bufsize=6000 nal_hrd=none filler=0 ip_ratio=1.40 aq=1:1.00
  
  Output #0, flv, to 'rtmp://live-api.facebook.com:80/rtmp/my key:
  
    Metadata:
  
      audiodelay      : 0
  
      canSeekToEnd    : 1
  
      creationdate    : Fri Feb 03 11:52:46 2006
  
                      :
  
      encoder         : Lavf58.13.102
  
      Stream #0:0: Video: h264 (libx264), 1 reference frame ([7][0][0][0] / 0x0007), yuv420p, 426x240, q=-1--1, 400 kb/s, 30 fps, 1k tbn, 30 tbc
  
      Metadata:
  
        encoder         : Lavc58.19.101 libx264
  
      Side data:
  
        cpb: bitrate max/min/avg: 1500000/0/400000 buffer size: 6000000 vbv_delay: -1
  
      Stream #0:1: Audio: mp3 (libmp3lame) ([2][0][0][0] / 0x0002), 44100 Hz, stereo, fltp, delay 1105, 128 kb/s
  
      Metadata:
  
        encoder         : Lavc58.19.101 libmp3lame
  
  No more output streams to write to, finishing.e=00:00:16.51 bitrate= 533.3kbits/s speed=0.992x
  
  [flv @ 0000020c0bc97fc0] Failed to update header with correct duration.
  
  [flv @ 0000020c0bc97fc0] Failed to update header with correct filesize.
  
  frame=  424 fps= 25 q=-1.0 Lsize=    1153kB time=00:00:16.95 bitrate= 557.1kbits/s speed=0.997x
  
  video:869kB audio:265kB subtitle:0kB other streams:0kB global headers:0kB muxing overhead: 1.666647%
  
  Input file #0 (.\video.flv):
  
    Input stream #0:0 (audio): 649 packets read (84767 bytes); 649 frames decoded (373824 samples);
  
    Input stream #0:1 (video): 424 packets read (566376 bytes); 424 frames decoded;
  
    Total: 1073 packets (651143 bytes) demuxed
  
  Output file #0 (rtmp://live-api.facebook.com:80/rtmp/my key):
  
    Output stream #0:0 (video): 424 frames encoded; 424 packets muxed (889641 bytes);
  
    Output stream #0:1 (audio): 649 frames encoded (747648 samples); 650 packets muxed (271673 bytes);
  
    Total: 1074 packets (1161314 bytes) muxed
  
  [libx264 @ 0000020c0bc80600] frame I:18    Avg QP:27.75  size:  7001
  
  [libx264 @ 0000020c0bc80600] frame P:406   Avg QP:32.67  size:  1879
  
  [libx264 @ 0000020c0bc80600] mb I  I16..4: 39.3%  0.0% 60.7%
  
  [libx264 @ 0000020c0bc80600] mb P  I16..4:  8.3%  0.0%  2.3%  P16..4: 42.2% 16.2%  4.4%  0.0%  0.0%    skip:26.6%
  
  [libx264 @ 0000020c0bc80600] final ratefactor: 28.61
  
  [libx264 @ 0000020c0bc80600] coded y,uvDC,uvAC intra: 40.2% 33.7% 9.2% inter: 23.8% 7.5% 0.2%
  
  [libx264 @ 0000020c0bc80600] i16 v,h,dc,p: 24% 50% 20%  6%
  
  [libx264 @ 0000020c0bc80600] i4 v,h,dc,ddl,ddr,vr,hd,vl,hu: 13% 34% 18%  5%  5%  4%  8%  4%  8%
  
  [libx264 @ 0000020c0bc80600] i8c dc,h,v,p: 67% 24%  7%  2%
  
  [libx264 @ 0000020c0bc80600] kb/s:418.33```

  This Image shows that The stream was alive few Few Seconds on Facebook

  ```[flv @ 0000020c0bc97fc0] Failed to update header with correct duration.
  
  [flv @ 0000020c0bc97fc0] Failed to update header with correct filesize.```

  Please correct me, the above error listed in the log, seems to be the main cause that the video stops streaming after few seconds. I’ve checked for the latency issues, But they won’t help anyway.

  Please Help me to tackle this issue. I’ll be very much thankful. :’)

  Streaming ends even earlier, when I use Google compute engine, instead my own PC as streaming service.

• Developers and vendors : Want a Matomo Hoodie ? Add a tag to the Matomo Open Source Tag Manager and this could be yours !

  7 juin 2018, par Matomo Core Team — Community, Development

  The Free Open Source Tag Manager is now available as a public beta on the Matomo Marketplace. Don’t know what a Tag Manager is ? Learn more here. In Short : It lets you easily manage all your third party JavaScript and HTML snippets (analytics, ads, social media, remarketing, affiliates, etc) through a single interface.

  Over the last few months we have worked on building the core for the Matomo Tag Manager which comes with a great set of features and a large set of pre-configured triggers and variables. However, we currently lack tags.

  This is where we need your help ! Together we can build a complete and industry leading open source tag manager.

  Tag examples include Google AdWords Conversion Tracking, Facebook Buttons, Facebook Pixels, Twitter Universal Website Tags, LinkedIn Insights.

  Are you a developer who is familiar with JavaScript and keen on adding a tag ? Or are you a vendor ? Don’t be shy, we appreciate any tags, even analytics related :) We have documented how to develop a new tag here, which is quite easy and straightforward. You may also need to understand a tiny bit of PHP but you’ll likely be fine even if you don’t (here is an example PHP file and the related JS file).

  As we want to ship the Matomo Tag Manager with as many tags as possible out of the box, we appreciate any new tag additions as a pull request on https://github.com/matomo-org/tag-manager.

  We will send out “Matomo Contributor” stickers that cannot be purchased anywhere for every contributor who contributes a tag within the next 3 months. As for the top 3 contributors… you’ll receive a Matomo hoodie ! Simply send us an email at hello@matomo.org after your tag has been merged. If needed, a draw will decide who gets the hoodies.

  FYI : The Matomo Tag Manager is already prepared to be handled in different contexts and we may possibly generate containers for Android and iOS. If you are keen on building the official Matomo SDKs for any of these mobile platforms, please get in touch.