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• GA360 vs GA4 : Key Differences and Challenges

  20 mai 2024, par Erin

  While the standard Universal Analytics (UA) was sunset for free users in July 2023, Google Analytics 360 (GA360) users could postpone the switch to GA4 for another 12 months. But time is running out. As July is rapidly approaching, GA360 customers need to prepare for the switch to Google Analytics 4 (GA4) or another solution. 

  This comparison post will help you understand the differences between GA360 vs. GA4. We’ll dive beneath the surface, examining each solution’s privacy implications and their usability, features, new metrics and measurement methods.

  What is Google Analytics 4 (Standard) ?

  GA4 is the latest version of Google Analytics, succeeding Universal Analytics. It was designed to address privacy issues with Universal Analytics, which made compliance with privacy regulations like GDPR difficult.

  It completely replaced Universal Analytics for free users in July 2023. GA4 Standard features many differences from the original UA, including :

  • Tracking and analysis are now events-based.
  • Insights are primarily powered by machine learning. (There are fewer reports and manual analysis tools).
  • Many users find the user interface to be too complex compared to Universal Analytics.

  The new tracking, reports and metrics already make GA4 feel like a completely different web analytics platform. The user interface itself also includes notable changes in navigation and implementation. These changes make the transition hard for experienced analysts and digital marketers alike. 

  For a more in-depth look at the differences, read our comparison of Google Analytics 4 and Universal Analytics.

  What is Google Analytics 360

  Google Analytics 360 is a paid version of Google Analytics, mostly aimed at enterprises that need to analyse a large amount of data.

  It significantly increases standard limits on data collection, sampling and processing. It also improves data granularity with more custom events and dimensions.

  Transitioning from Universal Analytics 360 to GA4 360

  You may still use the Universal Analytics tag and interface if you’ve been a Google Analytics 360 customer for multiple years. However, access to Universal Analytics 360 will be discontinued on July 1, 2024. Unlike the initial UA sunset (free version), you won’t be able to access the interface or your data after that, so it will be deleted.

  That means you will have to adapt to the new GA4 user interface, reports and metrics before the sunset or find an alternative solution.

  What is the difference between GA4 360 and free GA4 ?

  The key differences between GA4 360 and free GA4 are higher data limits, enterprise support, uptime guarantees and more robust administrative controls.

  

  GA4 offers most of the same features across the paid and free versions, but there are certain limits on data sampling, data processing and integrations. With the free version, you also can’t define as detailed events using event parameters as you can with GA4 360.

  Higher data collection, accuracy, storage and processing limits

  The biggest difference that GA4 360 brings to the table is more oomph in data collection, accuracy and analysis.

  You can collect more specific data (with 100 event parameters instead of 25 for custom metrics). GA4 360 lets you divide users using more custom dimensions based on events or user characteristics. Instead of 50 per property, you get up to 125 per property.

  And with up to 400 custom audiences, 360 is better for companies that heavily segment their users. More audiences, events and metrics per property mean more detailed insights.

  Sampling limits are also of a completely different scale. The max sample size in GA4 360 is 100x the free version of GA4, with up to 1 billion events per query. This makes analysis a lot more accurate for high-volume users. A slice of 10 million events is hardly representative if you have 200 million monthly events.

  Finally, GA4 360 lets you store all of that data for longer (up to 50 months vs up to 14 months). While new privacy regulations demand that you store user data only for the shortest time possible, website analytics data is often used for year-over-year analysis.

  Enterprise-grade support and uptime guarantees

  Because GA360 users are generally enterprises, Google offers service-level agreements for uptime and technical support response times.

  • Tracking : 99.9% uptime guarantee
  • Reporting : 99% uptime guarantee
  • Data processing : within 4 hours at a 98% uptime guarantee

  The free version of GA4 includes no such guarantees and limited access to professional support in the first place.

  Integrations

  GA4 360 increases limits for BigQuery and Google Ads Manager exports.

  

  The standard limits in the free version are 1 million events per day to BigQuery. In GA4 360, this is increased to billions of events per day. You also get up to 400 audiences for Search Ads 360 instead of the 100 limit in standard GA4.

  Roll-up analytics for agencies and enterprises

  If you manage a wide range of digital properties, checking each one separately isn’t very effective. You can export the data into a tool like Looker Studio (formerly Google Data Studio), but this requires extra work.

  With GA360, you can create “roll-up properties” to analyse data from multiple properties in the same space. It’s the best way to analyse larger trends and patterns across sites and apps.

  Administration and user access controls

  Beyond roll-up reporting, the other unique “advanced features” found in GA360 are related to administration and user access controls.

  

  First, GA360 lets you create custom user roles, giving different access levels to different properties. Sub-properties and roll-up properties are also useful tools for data governance purposes. They make it easier to limit access for specific analysts to the area they’re directly working on.

  You can also design custom reports for specific roles and employees based on their access levels.

  Pricing 

  While GA4 is free, Google Analytics 360 is priced based on your traffic volume. 

  With the introduction of GA4, Google implemented a revised pricing model. For GA4 360, pricing typically begins at USD $50,000/year which covers up to 25 million events per month. Beyond this limit, costs increase based on data usage, scaling accordingly.

  What’s not different : the interface, metrics, reports and basic features

  GA4 360 is the same analytics tool as the free version of GA4, with higher usage limits and a few enterprise features. You get more advanced tracking capabilities and more accurate analysis in the same GA4 packaging.

  If you already use and love GA4 but need to process more data, that’s great news. But if you’re using UA 360 and are hesitant to switch to the new interface, not so much. 

  Making the transition from UA to GA4 isn’t easy. Transferring the data means you need to figure out how to work with the API or use Google BigQuery.

  Plus, you have to deal with new metrics, reports and a new interface. For example, you don’t get to keep your custom funnel reports. You need to use “funnel explorations.”

  Going from UA to GA4 can feel like starting from scratch in a completely new web analytics tool.

  Which version of Google Analytics 4 is right for you ?

  Standard GA4 is a cost-effective web analytics option, but it’s not without its problems :

  • If you’re used to the UA interface, it feels clunky and difficult to analyse.
  • Data sampling is prevalent in the free version, leading to inaccuracies that can negatively affect decision-making and performance.

  And that’s just scratching the surface of common GA4 issues.

  Google Analytics 4 360 is a more reliable web analytics solution for enterprises. However, it suffers from many issues that made the GA4 transition painful for many free UA users last year.

  • You need to rebuild reports and adjust to the new complex interface.
  • To transfer historical data, you must use spreadsheets, the API, or BigQuery.

  You will still lose some of the data due to changes to the metrics and reporting.

  What if neither option is right for you ? Key considerations for choosing a Google Analytics alternative

  Despite what Google would like you to think, GA4 isn’t the only option for website analytics in 2024 — far from it. For companies that are used to UA 360, the right alternative can offer unique benefits to your company.

  Privacy regulations and future-proofing your analytics and marketing

  Although less flagrant than UA, GA4 is still in murky waters regarding compliance with GDPR and other privacy regulations. 

  And the issue isn’t just that you can get fined (which is bad enough). As part of a ruling, you may be ordered to change your analytics platform and protocol, which can completely disrupt your marketing workflow.

  When most marketing teams rely on web analytics to judge the ROI of their campaigns, this can be catastrophic. You may even have to pause campaigns as your team makes the adjustments.

  Avoid this risk completely by going with a privacy-friendly alternative.

  Features beyond basic web analytics

  To understand your users, you need to look at more than just events and conversions.

  That’s why some web analytics solutions have built-in behavioural analytics tools. Features like heatmaps (a visual pattern of popular clicks, scrolling and cursor movement) can help you understand how users interact with specific pages.

  

  Matomo allows you to consolidate behavioural analytics and regular web analytics into a single platform. You don’t need separate tools and subscriptions for heatmaps, session recordings, from analytics, media analytics and A/B testing. You can do all of this with Matomo.

  With insights about visits, sales, conversions, and usability in the same place, it’s a lot easier to improve your website.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Usability and familiar metrics

  The move to event tracking means new metrics, reports and tools. So, if you’re used to Universal Analytics, it can be tricky to transition to GA4. 

  But there’s no need to start from zero, learning to work with a brand-new interface. Many competing web analytics platforms offer familiar reports and metrics — ones your team has gotten used to. This will help you speed up the time to value with a shorter learning curve.

  Why Matomo is a better option than GA4 360 for UA 360 users

  Matomo offers privacy-friendly tracking, built from the ground up to comply with regulations — including IP anonymisation and DoNotTrack settings. You also get 100% ownership of the data, which means we will never use your data for our own profit (unlike Google and other data giants).

  This is a big deal, as breaking GDPR rules can lead to fines of up to 4% of your annual revenue. At the same time, you’ll also future-proof your marketing workflow by choosing a web analytics provider built with privacy regulations in mind.

  Plus, for legacy UA 360 users, the Matomo interface will also feel a lot more intuitive and familiar. Matomo also provides marketing attribution models you know, like first click, which GA4 has removed.

  Finally, you can access various behavioural analytics tools in a single platform — heatmaps, session recordings, form analytics, A/B testing and more. That means you don’t need to pay for separate solutions for conversion rate optimisation efforts.

  And the transition is smooth. Matomo lets you import Universal Analytics data and offers ready-made Google Ads integration and Looker Studio Connector.

  Join over 1 million websites that choose Matomo as their web analytics solution. Try it free for a 21-days. No credit card required.

  Try Matomo for Free

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• FFMpeg fails to compile

  28 juin 2024, par Nicolas Appriou

  I'm trying to compile a project that needs a specific version of ffmpeg to work.

  


  I isolated ffmpeg build and tried to compile it on its own as done in the parent project.
It seems to be version 6.1.1, the build system downloads ffmpeg from this url https://github.com/FFmpeg/FFmpeg/archive/e38092ef9395d7049f871ef4d5411eb410e283e0.zip before building it.
I'm using an up-to-date debian testing distribution.

  


  When trying to build it on my own, I got this error message :

  


  $ ./configure --enable-shared --disable-static --disable-programs --disable-doc
$ make
CC  libavcodec/vulkan_av1.o
In file included from libavcodec/vulkan_av1.c:21:
libavcodec/vulkan_decode.h:31:5: error: unknown type name ‘VkVideoDecodeAV1ProfileInfoMESA’
   31 |     VkVideoDecodeAV1ProfileInfoMESA av1_profile;
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:38:5: error: unknown type name ‘StdVideoAV1MESATile’
   38 |     StdVideoAV1MESATile            tiles[MAX_TILES];
      |     ^~~~~~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:39:5: error: unknown type name ‘StdVideoAV1MESATileList’
   39 |     StdVideoAV1MESATileList        tile_list;
      |     ^~~~~~~~~~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:43:5: error: unknown type name ‘VkVideoDecodeAV1DpbSlotInfoMESA’
   43 |     VkVideoDecodeAV1DpbSlotInfoMESA    vkav1_ref;
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:44:5: error: unknown type name ‘StdVideoAV1MESAFrameHeader’
   44 |     StdVideoAV1MESAFrameHeader         av1_frame_header;
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:45:5: error: unknown type name ‘VkVideoDecodeAV1PictureInfoMESA’
   45 |     VkVideoDecodeAV1PictureInfoMESA    av1_pic_info;
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:49:5: error: unknown type name ‘VkVideoDecodeAV1DpbSlotInfoMESA’
   49 |     VkVideoDecodeAV1DpbSlotInfoMESA     vkav1_refs[AV1_NUM_REF_FRAMES];
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:58:29: error: unknown type name ‘VkVideoDecodeAV1DpbSlotInfoMESA’; did you mean ‘VkVideoDecodeAV1DpbSlotInfoKHR’?
   58 |                             VkVideoDecodeAV1DpbSlotInfoMESA *vkav1_ref, /* Goes in ^ */
      |                             ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      |                             VkVideoDecodeAV1DpbSlotInfoKHR
libavcodec/vulkan_av1.c: In function ‘vk_av1_create_params’:
libavcodec/vulkan_av1.c:113:5: error: unknown type name ‘StdVideoAV1MESASequenceHeader’; did you mean ‘StdVideoAV1SequenceHeader’?
  113 |     StdVideoAV1MESASequenceHeader av1_sequence_header;
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      |     StdVideoAV1SequenceHeader
libavcodec/vulkan_av1.c:114:5: error: unknown type name ‘VkVideoDecodeAV1SessionParametersAddInfoMESA’; did you mean ‘VkVideoDecodeH265SessionParametersAddInfoKHR’?
  114 |     VkVideoDecodeAV1SessionParametersAddInfoMESA av1_params_info;
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      |     VkVideoDecodeH265SessionParametersAddInfoKHR
libavcodec/vulkan_av1.c:115:5: error: unknown type name ‘VkVideoDecodeAV1SessionParametersCreateInfoMESA’; did you mean ‘VkVideoDecodeAV1SessionParametersCreateInfoKHR’?
  115 |     VkVideoDecodeAV1SessionParametersCreateInfoMESA av1_params;
      |     ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      |     VkVideoDecodeAV1SessionParametersCreateInfoKHR
libavcodec/vulkan_av1.c:120:28: error: ‘StdVideoAV1MESASequenceHeader’ undeclared (first use in this function); did you mean ‘StdVideoAV1SequenceHeader’?
  120 |     av1_sequence_header = (StdVideoAV1MESASequenceHeader) {
      |                            ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      |                            StdVideoAV1SequenceHeader
libavcodec/vulkan_av1.c:120:28: note: each undeclared identifier is reported only once for each function it appears in
libavcodec/vulkan_av1.c:120:58: error: expected ‘;’ before ‘{’ token
  120 |     av1_sequence_header = (StdVideoAV1MESASequenceHeader) {
      |                                                          ^~
      |                                                          ;
libavcodec/vulkan_av1.c:171:24: error: ‘VkVideoDecodeAV1SessionParametersAddInfoMESA’ undeclared (first use in this function); did you mean ‘VkVideoDecodeH265SessionParametersAddInfoKHR’?
  171 |     av1_params_info = (VkVideoDecodeAV1SessionParametersAddInfoMESA) {
      |                        ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      |                        VkVideoDecodeH265SessionParametersAddInfoKHR
libavcodec/vulkan_av1.c:171:69: error: expected ‘;’ before ‘{’ token
  171 |     av1_params_info = (VkVideoDecodeAV1SessionParametersAddInfoMESA) {
      |                                                                     ^~
      |                                                                     ;
libavcodec/vulkan_av1.c:175:19: error: ‘VkVideoDecodeAV1SessionParametersCreateInfoMESA’ undeclared (first use in this function); did you mean ‘VkVideoDecodeAV1SessionParametersCreateInfoKHR’?
  175 |     av1_params = (VkVideoDecodeAV1SessionParametersCreateInfoMESA) {
      |                   ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      |                   VkVideoDecodeAV1SessionParametersCreateInfoKHR
libavcodec/vulkan_av1.c:175:67: error: expected ‘;’ before ‘{’ token
  175 |     av1_params = (VkVideoDecodeAV1SessionParametersCreateInfoMESA) {
      |                                                                   ^~
      |                                                                   ;
libavcodec/vulkan_av1.c:114:50: warning: variable ‘av1_params_info’ set but not used [-Wunused-but-set-variable]
  114 |     VkVideoDecodeAV1SessionParametersAddInfoMESA av1_params_info;
      |                                                  ^~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:113:35: warning: variable ‘av1_sequence_header’ set but not used [-Wunused-but-set-variable]
  113 |     StdVideoAV1MESASequenceHeader av1_sequence_header;
      |                                   ^~~~~~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:111:33: warning: unused variable ‘seq’ [-Wunused-variable]
  111 |     const AV1RawSequenceHeader *seq = s->raw_seq;
      |                                 ^~~
libavcodec/vulkan_av1.c: In function ‘vk_av1_start_frame’:
libavcodec/vulkan_av1.c:237:15: error: implicit declaration of function ‘vk_av1_fill_pict’ [-Werror=implicit-function-declaration]
  237 |         err = vk_av1_fill_pict(avctx, &ap->ref_src[i], &vp->ref_slots[i],
      |               ^~~~~~~~~~~~~~~~
libavcodec/vulkan_av1.c:252:18: error: request for member ‘nb_tiles’ in something not a structure or union
  252 |     ap->tile_list.nb_tiles = 0;
      |                  ^
libavcodec/vulkan_av1.c:253:18: error: request for member ‘tile_list’ in something not a structure or union
  253 |     ap->tile_list.tile_list = ap->tiles;
      |                  ^
libavcodec/vulkan_av1.c:255:25: error: ‘VkVideoDecodeAV1PictureInfoMESA’ undeclared (first use in this function); did you mean ‘VkVideoDecodeAV1PictureInfoKHR’?
  255 |     ap->av1_pic_info = (VkVideoDecodeAV1PictureInfoMESA) {
      |                         ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
      |                         VkVideoDecodeAV1PictureInfoKHR
libavcodec/vulkan_av1.c:255:57: error: expected ‘;’ before ‘{’ token
  255 |     ap->av1_pic_info = (VkVideoDecodeAV1PictureInfoMESA) {
      |                                                         ^~
      |                                                         ;
libavcodec/vulkan_av1.c:278:29: error: ‘StdVideoAV1MESAFrameHeader’ undeclared (first use in this function); did you mean ‘StdVideoAV1SequenceHeader’?
  278 |     ap->av1_frame_header = (StdVideoAV1MESAFrameHeader) {
      |                             ^~~~~~~~~~~~~~~~~~~~~~~~~~
      |                             StdVideoAV1SequenceHeader
libavcodec/vulkan_av1.c:278:56: error: expected ‘;’ before ‘{’ token
  278 |     ap->av1_frame_header = (StdVideoAV1MESAFrameHeader) {
      |                                                        ^~
      |                                                        ;
libavcodec/vulkan_av1.c:402:29: error: request for member ‘tiling’ in something not a structure or union
  402 |         ap->av1_frame_header.tiling.width_in_sbs_minus_1[i] = frame_header->width_in_sbs_minus_1[i];
      |                             ^
libavcodec/vulkan_av1.c:403:29: error: request for member ‘tiling’ in something not a structure or union
  403 |         ap->av1_frame_header.tiling.height_in_sbs_minus_1[i] = frame_header->height_in_sbs_minus_1[i];
      |                             ^
libavcodec/vulkan_av1.c:404:29: error: request for member ‘tiling’ in something not a structure or union
  404 |         ap->av1_frame_header.tiling.tile_start_col_sb[i] = frame_header->tile_start_col_sb[i];
      |                             ^
libavcodec/vulkan_av1.c:405:29: error: request for member ‘tiling’ in something not a structure or union
  405 |         ap->av1_frame_header.tiling.tile_start_row_sb[i] = frame_header->tile_start_row_sb[i];
      |                             ^
libavcodec/vulkan_av1.c:409:29: error: request for member ‘segmentation’ in something not a structure or union
  409 |         ap->av1_frame_header.segmentation.feature_enabled_bits[i] = 0;
      |                             ^
libavcodec/vulkan_av1.c:411:33: error: request for member ‘segmentation’ in something not a structure or union
  411 |             ap->av1_frame_header.segmentation.feature_enabled_bits[i] |= (frame_header->feature_enabled[i][j] << j);
      |                                 ^
libavcodec/vulkan_av1.c:412:33: error: request for member ‘segmentation’ in something not a structure or union
  412 |             ap->av1_frame_header.segmentation.feature_data[i][j] = frame_header->feature_value[i][j];
      |                                 ^
libavcodec/vulkan_av1.c:415:29: error: request for member ‘loop_filter’ in something not a structure or union
  415 |         ap->av1_frame_header.loop_filter.ref_deltas[i] = frame_header->loop_filter_ref_deltas[i];
      |                             ^
libavcodec/vulkan_av1.c:417:29: error: request for member ‘cdef’ in something not a structure or union
  417 |         ap->av1_frame_header.cdef.y_pri_strength[i] = frame_header->cdef_y_pri_strength[i];
      |                             ^
libavcodec/vulkan_av1.c:418:29: error: request for member ‘cdef’ in something not a structure or union
  418 |         ap->av1_frame_header.cdef.y_sec_strength[i] = frame_header->cdef_y_sec_strength[i];
      |                             ^
libavcodec/vulkan_av1.c:419:29: error: request for member ‘cdef’ in something not a structure or union
  419 |         ap->av1_frame_header.cdef.uv_pri_strength[i] = frame_header->cdef_uv_pri_strength[i];
      |                             ^
libavcodec/vulkan_av1.c:420:29: error: request for member ‘cdef’ in something not a structure or union
  420 |         ap->av1_frame_header.cdef.uv_sec_strength[i] = frame_header->cdef_uv_sec_strength[i];
      |                             ^
libavcodec/vulkan_av1.c:422:29: error: request for member ‘ref_order_hint’ in something not a structure or union
  422 |         ap->av1_frame_header.ref_order_hint[i] = frame_header->ref_order_hint[i];
      |                             ^
libavcodec/vulkan_av1.c:423:29: error: request for member ‘global_motion’ in something not a structure or union
  423 |         ap->av1_frame_header.global_motion[i] = (StdVideoAV1MESAGlobalMotion) {
      |                             ^
libavcodec/vulkan_av1.c:423:50: error: ‘StdVideoAV1MESAGlobalMotion’ undeclared (first use in this function); did you mean ‘StdVideoAV1GlobalMotion’?
  423 |         ap->av1_frame_header.global_motion[i] = (StdVideoAV1MESAGlobalMotion) {
      |                                                  ^~~~~~~~~~~~~~~~~~~~~~~~~~~
      |                                                  StdVideoAV1GlobalMotion
libavcodec/vulkan_av1.c:423:78: error: expected ‘;’ before ‘{’ token
  423 |         ap->av1_frame_header.global_motion[i] = (StdVideoAV1MESAGlobalMotion) {
      |                                                                              ^~
      |                                                                              ;
libavcodec/vulkan_av1.c:437:29: error: request for member ‘ref_frame_idx’ in something not a structure or union
  437 |         ap->av1_frame_header.ref_frame_idx[i] = frame_header->ref_frame_idx[i];
      |                             ^
libavcodec/vulkan_av1.c:438:29: error: request for member ‘delta_frame_id_minus1’ in something not a structure or union
  438 |         ap->av1_frame_header.delta_frame_id_minus1[i] = frame_header->delta_frame_id_minus1[i];
      |                             ^
libavcodec/vulkan_av1.c:441:21: error: request for member ‘skip_mode_frame_idx’ in something not a structure or union
  441 |     ap->av1_pic_info.skip_mode_frame_idx[0] = s->cur_frame.skip_mode_frame_idx[0];
      |                     ^
libavcodec/vulkan_av1.c:442:21: error: request for member ‘skip_mode_frame_idx’ in something not a structure or union
  442 |     ap->av1_pic_info.skip_mode_frame_idx[1] = s->cur_frame.skip_mode_frame_idx[1];
      |                     ^
libavcodec/vulkan_av1.c:446:33: error: request for member ‘film_grain’ in something not a structure or union
  446 |             ap->av1_frame_header.film_grain.point_y_value[i] = film_grain->point_y_value[i];
      |                                 ^
libavcodec/vulkan_av1.c:447:33: error: request for member ‘film_grain’ in something not a structure or union
  447 |             ap->av1_frame_header.film_grain.point_y_scaling[i] = film_grain->point_y_scaling[i];
      |                                 ^
libavcodec/vulkan_av1.c:451:33: error: request for member ‘film_grain’ in something not a structure or union
  451 |             ap->av1_frame_header.film_grain.point_cb_value[i] = film_grain->point_cb_value[i];
      |                                 ^
libavcodec/vulkan_av1.c:452:33: error: request for member ‘film_grain’ in something not a structure or union
  452 |             ap->av1_frame_header.film_grain.point_cb_scaling[i] = film_grain->point_cb_scaling[i];
      |                                 ^
libavcodec/vulkan_av1.c:453:33: error: request for member ‘film_grain’ in something not a structure or union
  453 |             ap->av1_frame_header.film_grain.point_cr_value[i] = film_grain->point_cr_value[i];
      |                                 ^
libavcodec/vulkan_av1.c:454:33: error: request for member ‘film_grain’ in something not a structure or union
  454 |             ap->av1_frame_header.film_grain.point_cr_scaling[i] = film_grain->point_cr_scaling[i];
      |                                 ^
libavcodec/vulkan_av1.c:458:33: error: request for member ‘film_grain’ in something not a structure or union
  458 |             ap->av1_frame_header.film_grain.ar_coeffs_y_plus_128[i] = film_grain->ar_coeffs_y_plus_128[i];
      |                                 ^
libavcodec/vulkan_av1.c:459:33: error: request for member ‘film_grain’ in something not a structure or union
  459 |             ap->av1_frame_header.film_grain.ar_coeffs_cb_plus_128[i] = film_grain->ar_coeffs_cb_plus_128[i];
      |                                 ^
libavcodec/vulkan_av1.c:460:33: error: request for member ‘film_grain’ in something not a structure or union
  460 |             ap->av1_frame_header.film_grain.ar_coeffs_cr_plus_128[i] = film_grain->ar_coeffs_cr_plus_128[i];
      |                                 ^
libavcodec/vulkan_av1.c:463:29: error: request for member ‘film_grain’ in something not a structure or union
  463 |         ap->av1_frame_header.film_grain.ar_coeffs_cb_plus_128[24] = film_grain->ar_coeffs_cb_plus_128[24];
      |                             ^
libavcodec/vulkan_av1.c:464:29: error: request for member ‘film_grain’ in something not a structure or union
  464 |         ap->av1_frame_header.film_grain.ar_coeffs_cr_plus_128[24] = film_grain->ar_coeffs_cr_plus_128[24];
      |                             ^
libavcodec/vulkan_av1.c: In function ‘vk_av1_decode_slice’:
libavcodec/vulkan_av1.c:483:32: error: request for member ‘nb_tiles’ in something not a structure or union
  483 |         ap->tiles[ap->tile_list.nb_tiles] = (StdVideoAV1MESATile) {
      |                                ^
libavcodec/vulkan_av1.c:483:46: error: ‘StdVideoAV1MESATile’ undeclared (first use in this function); did you mean ‘StdVideoAV1Profile’?
  483 |         ap->tiles[ap->tile_list.nb_tiles] = (StdVideoAV1MESATile) {
      |                                              ^~~~~~~~~~~~~~~~~~~
      |                                              StdVideoAV1Profile
libavcodec/vulkan_av1.c:483:66: error: expected ‘;’ before ‘{’ token
  483 |         ap->tiles[ap->tile_list.nb_tiles] = (StdVideoAV1MESATile) {
      |                                                                  ^~
      |                                                                  ;
libavcodec/vulkan_av1.c:495:52: error: request for member ‘nb_tiles’ in something not a structure or union
  495 |                                      &ap->tile_list.nb_tiles,
      |                                                    ^
libavcodec/vulkan_av1.c:500:32: error: request for member ‘nb_tiles’ in something not a structure or union
  500 |         ap->tiles[ap->tile_list.nb_tiles - 1].offset = ap->tile_offsets[ap->tile_list.nb_tiles - 1];
      |                                ^
libavcodec/vulkan_av1.c:500:86: error: request for member ‘nb_tiles’ in something not a structure or union
  500 |         ap->tiles[ap->tile_list.nb_tiles - 1].offset = ap->tile_offsets[ap->tile_list.nb_tiles - 1];
      |                                                                                      ^
libavcodec/vulkan_av1.c: In function ‘vk_av1_end_frame’:
libavcodec/vulkan_av1.c:516:23: error: request for member ‘nb_tiles’ in something not a structure or union
  516 |     if (!ap->tile_list.nb_tiles)
      |                       ^
libavcodec/vulkan_av1.c:534:42: error: request for member ‘nb_tiles’ in something not a structure or union
  534 |            vp->slices_size, ap->tile_list.nb_tiles);
      |                                          ^
cc1: some warnings being treated as errors
make: *** [ffbuild/common.mak:81: libavcodec/vulkan_av1.o] Error 1


  


  The command launch above are the one taken from the parent app build system.
I'm not familiar with ffmpeg or graphics system in general.

  


  I don't understand why the first message says that VkVideoDecodeAV1ProfileInfoMESA could not be found.
I thought I might be missing some package dependencies but it appears that a VkVideoDecodeAV1ProfileInfoMESA typedef can be found in ffmpeg sources (libavcodec/vulkan_video_codec_av1std.h:373 in this version).
So I assume something may be wrong with my compile configuration ?

  


  I'm a little bit lost on this issue and don't know what to look for to solve it.

  


• Strategies for Reducing Bank Customer Acquisition Cost [2024]

  24 septembre 2024, par Daniel Crough — Banking and Financial Services

  Acquiring new customers is no small feat — regardless of the size of your team. The expenses of various marketing efforts tend to pile up fast, even more so when your business operates in a highly competitive industry like banking. At the same time, marketing budgets continue to decrease — dropping from an average of 9.1% of total company revenue in 2023 down to 7.7% in 2024 — prompting businesses in the financial services industry to figure out how they can do more with less.

  That brings us to bank customer acquisition cost (CAC) — a key business metric that can reveal quite a bit about your bank’s long-term profitability and potential for achieving sustainable growth. 

  This article will cover the ins and outs of bank customer acquisition costs and share actionable tips and strategies you can implement to reduce CAC.

  What is customer acquisition cost in banking ? 

  

  The global market volume of neobanks — fintech companies and digital banking platforms, often referred to as “challenger banks” — was estimated at $4.96 trillion in 2023. It’s expected to continue growing at a compound annual growth rate (CAGR) of 13.15% in the coming years, potentially reaching $10.44 trillion by 2028.

  That’s enough of an indicator that the financial services industry is now a highly competitive landscape where companies are often competing for the attention of a relatively limited audience. 

  Plus, several app-only banks based in Europe have made significant progress in attracting new customers to their financial products : 

  

  Unsurprisingly, this flurry of competition is putting upward pressure on customer acquisition and retention costs across the banking sector.

  Customer acquisition cost (CAC) — the sum of all costs and resources related to acquiring an additional customer — is one of the key business metrics to keep an eye on when trying to maximise your return on investment (ROI) and profitability, especially if your company operates in the banking industry.

  Here’s the basic formula you can use to calculate the cost of acquisition in banking : 

  Customer Acquisition Cost (CAC) = Total Amount Spent (TS) / Total New Customers Acquired (TNC)

  In essence, it requires you to divide the total cost of acquiring consumers — including sales and marketing expenses — by the total number of new customers your company has gained within a specific timeframe.

  There’s one thing you need to keep in mind : 

  The customer acquisition process involves more than just your marketing and sales departments. 

  While marketing and sales channels play a crucial role in this process, the list of expenses that may contribute to customer acquisition costs in banking goes well beyond that. 

  Here’s a quick breakdown of the customer acquisition cost formula to show you which costs make up the total amount spent : 

  • All advertising and marketing costs, including traditional (direct mail, billboards, TV and print advertising) and digital channels (email, Google ads, social media and influencer marketing)
  • Cost of outsourced marketing services, including any independent contractors involved in the process 
  • Salaries and commissions for the marketing team and sales representatives
  • Software subscriptions, including marketing software and web analytics tools 
  • Other overhead and operational costs 

  And until you’ve taken all these expenses into account, you won’t be able to accurately estimate how much it actually costs you to attract potential customers.

  Another thing to keep in mind is that there’s no universal definition of “good CAC.” 

  The average customer acquisition cost varies across different industries and business models. That said, you can generally expect a higher-than-average CAC in highly competitive sectors — namely, the financial, manufacturing and real estate industries. 

  Importance of tracking customer acquisition cost in banking 

  

  Customer acquisition costs are an important indicator of a banking business’s potential growth and profitability. Monitoring this fundamental business metric can provide data-driven insights about your current bank customer acquisition strategy — and offers a few notable benefits : 

  • Measuring the performance and effectiveness of different channels and campaigns and making data-driven decisions regarding future marketing efforts
  • Improving return on investment (ROI) by determining the most effective strategies for acquiring new customers 
  • Improving profitability by assessing the value per customer and improving profit margins 
  • Benchmarking against industry competitors to see where your business’s CAC stands compared to the banking industry average

  At the risk of stating the obvious, acquiring new customers isn’t always easy. That’s true for many highly competitive industries — especially the banking sector, which is currently witnessing the rapid rise of digital disruptors. 

  Case in point, the fintech market alone is currently valued at $312.98 billion and is expected to reach $556.70 billion by 2030, following a CAGR of 14%.

  

  However, strong competition is only one of the challenges banks face throughout the process of attracting potential customers. 

  Here are a few other things to keep in mind : 

  • Ethical business practices and strict compliance requirements when it comes to the privacy and security of customer data, including meeting data protection standards and ensuring regulatory compliance
  • Lack of personalisation throughout the customer journey, which today’s customers view as a lack of understanding of — and even interest in — their needs and preferences 
  • Limited mobile banking capabilities, which further points to a failure to innovate and adapt — one of the leading risks that financial services may face 

  7 strategies for reducing bank customer acquisition costs 

  

  When working on optimising your banking customer acquisition strategy, the key thing to keep in mind is that there are two sides to improving CAC : 

  On the one hand, you have efforts to decrease the costs associated with acquiring a new customer — and on the other, you have the importance of attracting high-value customers. 

  1. Eliminate friction points in the customer onboarding process

  One of the first things financial institutions should do is examine their existing digital onboarding process and look for friction points that might cause potential customers to drop off. After all, a streamlined onboarding process will minimise barriers to conversion, increasing the number of new customers acquired and improving overall customer satisfaction. 

  Keep in mind that, at the 30-day mark, finance mobile apps have an average user retention rate of 3% : 

  

  That says a lot about the importance of providing a frictionless onboarding experience as a retail bank or any other financial institution. 

  Granted, a single point of friction is rarely enough to cause customers to churn. It’s typically a combination of several factors — a lengthy sign-up process with complicated password requirements and time-consuming customer identification or poor customer service, for example — that occur during the key moments of the customer journey.

  In order to keep tabs on customer experiences across different touchpoints and spot potential barriers in their journey, you’ll need a reliable source of data. Matomo’s Funnels report can show you exactly where your website visitors are dropping off. 

  2. Get more personalised with your marketing efforts 

  Generic experiences are rarely the way to go — especially when you’re contending for the attention of prospective customers in such a competitive sector. 

  Besides, 62% of people who made an online purchase within the last six months have said that brands would lose their loyalty following a non-personalised experience. 

  What’s more shocking is that only a year earlier, that number stood at 45%.

  

  When it comes to improving marketing efficiency and sales strategies, 94% of marketers agree that personalisation is key : 

  

  It’s evident that personalised marketing supported by behavioural segmentation can significantly improve conversion rates — and, most importantly, reduce acquisition costs. 

  Of course, it’s virtually impossible to deliver targeted, personalised marketing messaging without creating audience segments and detailed buyer personas. Matomo’s Segmentation feature can help by allowing you to split website visitors into smaller groups and get much-needed insights for behavioural segmentation. 

  3. Build an omnichannel marketing strategy 

  Customer expectations, behaviours and preferences are constantly evolving, making it crucial for financial services to adapt their customer acquisition strategies accordingly. Meeting prospective customers on their preferred channels is a big part of that. 

  The issue is that modern banking customers tend to move across different channels. That’s one of the reasons why it’s becoming increasingly more difficult to deliver a unified experience throughout the entire customer journey and close the gap between digital and in-person customer interactions. 

  Omnichannel marketing gives you a way to keep up with customers’ ever-evolving expectations :

  Adopting this marketing strategy will allow you to meet customers where they are and deliver a seamless experience across a wide range of digital channels and touchpoints, leading to more exposure — and, ultimately, increasing the number of acquired customers.

  Matomo can support your omnichannel efforts by providing accurate, unsampled data needed for cross-channel analytics and marketing attribution. 

  4. Work on your social media presence 

  Social networks are among the most popular — and successful — digital marketing channels, with millions (even billions, depending on the platform) of active users. 

  In fact, 89% of marketers report using Facebook as their main platform for social media marketing, while another 80% use Instagram to reach their target audience and promote their business. 

  

  And according to The State of Social Media in Banking 2023 report, nine out of ten banks (89%) consider social media is important, while another 88% are active on their social media accounts. 

  That is to say, even traditionally conservative industries — like banking and finance — realise the crucial role of social media in promoting their services and engaging with customers on their preferred channels : 

  It’s an excellent way for businesses in the financial sector to gain exposure, drive traffic to their website and acquire new customers. 

  If you’re ready to improve social media visibility as part of your multichannel efforts, Matomo can help you track social media activity across 70 different platforms. 

  5. Shift the focus on customer loyalty and retention 

  Up until this point, the focus has mainly been on building new business relationships. However, one thing to keep in mind is that retaining existing customers is generally cheaper than investing in customer acquisition activities to attract new ones. 

  Of course, customer retention won’t directly impact your CAC. But what it can do is increase customer lifetime value, contributing to your company’s revenue and profits — which, in turn, can “balance out” your acquisition costs in the long run.

  That’s not to say that you should stop trying to bring in new clients ; far from it. 

  However, focusing on increasing customer loyalty — namely, delivering excellent customer service and building lasting business relationships — could motivate satisfied customers to become brand advocates. 

  As this survey of customer satisfaction for leading banks in the UK has shown, when clients are satisfied with a bank’s products and services, they’re more likely to recommend it. 

  

  Positive word-of-mouth recommendations can be a powerful way to drive customer acquisition. You can leverage that by launching a customer referral program and incentivising loyal customers to refer new ones to your business. 

  6. A/B test different elements to find ones that work 

  We’ve already underlined the importance of understanding your audience ; it’s the foundation for optimising the customer journey and delivering targeted marketing efforts that will attract more customers. 

  Another proven method that can be used to refine your customer acquisition strategy is A/B or split testing. 

  It involves testing different versions of specific elements of your marketing content — such as language, CTAs and visuals — to determine the most effective combinations that resonate with your target audience. 

  Besides your marketing campaigns, you can also split test different variants of your website or mobile app to see which version gets them to convert. 

  Matomo’s A/B Testing feature can be of huge help here : 

  

  7. Track other relevant customer acquisition metrics 

  To better assess your company’s profitability, you’ll have to go beyond CAC and factor in other critical metrics — namely, customer lifetime value (CLTV), churn rate and return on investment (ROI). 

  Here are the most important KPIs you should monitor in addition to CAC : 

  • Customer lifetime value (CLTV), which represents the revenue generated by a single customer throughout the duration of their relationship with your company and is another crucial indicator of customer profitability 
  • Churn rate — the rate at which your company loses clients within a given timeframe — can indicate how well you’re retaining customers 
  • Return on investment (ROI) — the revenue generated by new clients compared to the initial costs of acquiring them — can help you identify the most effective customer acquisition channels 

  These metrics work hand in hand. There needs to be a balance between the revenue the customer generates over their lifetime and the costs related to attracting them.

  Ideally, you should be aiming for lower CAC and customer churn and higher CLTV ; that’s usually a solid indicator of financial health and sustainable growth. 

  Lower bank customer acquisition costs with Matomo 

  Acquiring new customers will require a lot of time and resources, regardless of the industry you’re working in — but can be even more challenging in the financial sector, where you have to adapt to the ever-changing customer expectations and demands. 

  The strategies outlined above — combined with a thorough understanding of your customer’s behaviours and preferences — can help you lower the cost of bank customer acquisition.

  On that note, you can learn a lot about your customers through web analytics — and use those insights to support your customer acquisition process and ensure you’re delivering a seamless online banking experience. 

  If you need an alternative to Google Analytics that doesn’t rely on data sampling and ensures compliance with the strictest privacy regulations, all while being easy to use, choose Matomo — the go-to web analytics platform for more than 1 million websites around the globe. 

  CTA : Start your 21-day free trial today to see how Matomo’s all-in-one solution can help you understand and attract new customers — all while respecting their privacy.