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Mot : - Tags -/plugins

Exemple de boutons d’action pour une collection collaborative

27 février 2013, par kent1

Mis à jour : Mars 2013

Langue : français

Type : Image

Tags : plugins, collection

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Exemple de boutons d’action pour une collection personnelle

27 février 2013, par kent1

Mis à jour : Février 2013

Langue : English

Type : Image

Tags : plugins, collection

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Autres articles (51)

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The Only 7 Lead Generation Tools You Need in 2024

7 mars 2024, par Erin
If you can’t get leads, you can’t get customers. To ensure you always have a steady stream of new customers (and revenue), you need to equip yourself with lead generation tools.

Lead gen software does the heavy lifting for you so you can focus on providing great products and great services. With it, you’ll be able to turn more strangers into customers and grow your business.

And you don’t need a ton of tools to get the job done, either. Consolidating your tech stack to a few select tools will help you get more done in less time (and with less confusion).

In this article, we’ll analyse the top seven lead generation tools to help you grow your business in 2024.

Let’s dive in.

What is a lead generation tool ?

A lead generation tool is software you can use to turn strangers into customers. It helps you draw customers into your sales funnel by learning their contact details, like their email address or phone number.

Lead generation tools are great levers you can pull to drive high-quality leads. They remove the grunt work by automating the lead generation process.

Whether it’s through creating lead magnets, offering conversion rate analytics, helping you create high-quality forms or automating the lead follow-up process, lead generation tools can bring in new customers to grow your business.

The top 7 lead generation tools in 2024

To land more leads, you need to ensure you’re leveraging the right software. With so many to choose from, here’s just a handful of the best ones available :

1. Matomo : Best conversion optimisation tool

Matomo is an open-source website analytics tool dedicated to protecting user privacy and data. Trusted on over 1 million websites, the platform offers in-depth insights into your web traffic, including conversion data.
Why Matomo ? Matomo is trusted by over 1 million websites, including the United Nations and the European Commission, making it the leading choice for privacy-focused web analytics.

It comes equipped with a suite of conversion optimisation features to help you generate more leads. You can easily analyse your target audience’s behaviour while also respecting users’ privacy.

Standout features : In-depth visitor tracking, From Analytics, Session Recordings, A/B Testing, Heatmaps Marketing Attribution, roll-up reporting (pulling data from multiple sites), Google Analytics importing. and more.

Integrations : Cloudflare, WooCommerce, Squarespace, Shopify, Drupal, Magento, Vue, SharePoint, WordPress, Wix, Webflow, GoDaddy, Jimdo, Joomla, Kajabi. and more.

Pricing : Starts free for Matomo On-Premise and increases to $23/month for Matomo Cloud (which includes a free 21-day trial with no credit card required).

Pros

100% accurate data with no data sampling
Leading web analytics tool for respecting visitor privacy
Compliant with the strictest privacy laws, like the GDPR
No need for cookie consent banner (except in the UK and Germany)
Wide range of advanced features to optimise your website and increase conversions
Cloud hosting and on-premise options for flexibility

Cons

Matomo On-Premise requires technical expertise (but for the less technical, the Cloud option works instantly)
On-Premise plugins are an additional cost

Try Matomo for Free

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

Start for free

No credit card required
2. HubSpot : Best all-in-one CRM for organising leads

HubSpot is a customer relationship management (CRM) and marketing software with over 194,000 customers worldwide. This user-friendly platform is dedicated to helping businesses of all sizes manage leads and customers.
Why HubSpot ? HubSpot Marketing integrates seamlessly with the HubSpot CRM to help with everything from lead capture to conversion. The platform also features a free version — a great starting place for lead generation and management.

Standout features : A robust set of no-code lead gen tools, like ads, forms, customisable landing pages, lead capture templates for potential customers, email campaigns, analytics dashboards and a free CRM to track leads.

Integrations : Google Ads, WordPress, Jotform, Facebook Ads, Magento, Shopify, Weebly, WordPress, Zapier and Drupal.

Pricing : Starts free for anyone and increases to $800/month for a professional plan.

Pros

User-friendly interface
All-in-one lead management solution
Easy integration with HubSpot CRM
Simple analytics for beginners
Includes landing page tools
Offers email marketing tools to nurture leads

Cons

Free version has limited functionality
Expensive jump to paid plans
3. Leadfeeder : Best for finding warm B2B leads

Leadfeeder is a business-to-business (B2B) marketing tool that shows B2B brands which companies are visiting their websites and gives them contact information to reach out to the right decision-makers.
Why Leadfeeder ? Leadfeeder simplifies outreach for B2B organisations because it shows you what businesses are interacting with your website. Rather than trying to reach out to completely cold leads, the tool highlights brands that are already checking out your content and offerings.

Standout features : Many account-based marketing (ABM) tools enable you to discover B2B accounts with insights into when you should contact them after they visit your site, as well as their job titles. The platform also includes a range of features that notify you and your sales team when qualified B2B leads come to your site so that you can move to capture them quickly.

Integrations : Zoho, Google Chat, Pipedrive, Salesforce, Google Looker Studio, ActiveCampaign, HubSpot, Mailchimp, Microsoft Dynamics and Slack.

Pricing : Starts at $139/month (includes a 14-day free trial).

Pros

Easily find prospective customers
Track website visitors and potential customers freely
Simple filtering capabilities

Cons

Few integrations available
Can be difficult to contact customer support
4. OptinMonster : Best all-in-one lead generation form tool

Founded in 2013, OptinMonster has over 1.2 million users worldwide. It offers a wide range of lead gen tools led by robust form tools that turn your target audience into leads.
Why OptinMonster ? The platform is one of the most reputable lead generation platforms available. With nearly 100 lead capture templates, it’s highly customisable to almost any business looking to begin capturing leads with different forms.

Standout features : 95 customisable form templates, drag-and-drop builders, onsite retargeting, segmentation, A/B testing and exit-intent popups that present forms when a user is about to leave the site.

Integrations : Constant Contact, ConvertKit, ActiveCampaign, Salesforce Pardot, Campaign Monitor, HubSpot, Jilt, Keap and Mailchimp.

Pricing : Starts at $16/month (no free trial offered).

Pros

Easy drag-and-drop form-builder
Wide range of form templates
Customisable forms for any business
Simple A/B testing to help optimise form performance

Cons

No free trial available
Growth features, like onsite retargeting, are only available on higher-tiered plans
5. Intercom : Best live chat tool for capturing leads

Intercom is one of the top live chat tools for helping businesses maintain solid communication with their customers. Founded in 2011, this live chat platform serves over 25,000 users around the world with a simple, sophisticated experience and seamless lead generation features.
Why Intercom ? Intercom is a live chat tool first. But many people don’t know it’s also a simple lead capture tool. When people think of lead generation, they think of static or popup forms. But Intercom allows you to capture forms directly within a live chat conversation.

Standout features : Lead generation via live chat that allows you to naturally capture potential customers’ information to turn them into a lead. The tool also comes equipped with chatbots that can automate the communication and lead gen process on autopilot.

Integrations : Pipedrive, Typeform, Google Analytics, Zapier, Calendly, Salesforce, Stripe, Campaign Monitor, Clearbit Reveal and HubSpot.

Pricing : Starts at $39/month (with a 21-day free trial).

Pros

Live chat lead gen capture
Chatbot lead generation automation
Wide range of integrations and apps
User-friendly interface

Cons

Fairly expensive for small businesses
Customer support isn’t the fastest
6. Callingly : Best for making inbound calls with leads

Callingly is a sophisticated call software that lets you get the most out of every inbound call you get from leads. Founded in 2019, this software company gives valuable insights into your inbound call leads, pulling information from various integrations and forms.
Why Callingly ? Callingly is a robust call software that gathers lead information through forms, lead magnets, landing pages and forms. The software also has intelligent routing, which sends a call to the most relevant salesperson.

Standout features : Advanced lead routing ensures inbound leads are directed to the most appropriate sales rep based on their unique needs and geographic location. The tool is also equipped with call tracking, analytics, lead source tracking and more to help personalise the experience for quick capture and conversion of leads.

Integrations : ClickFunnels, Pipedrive, Salesforce, Drip, Aircall, HubSpot, Jotform, OptinMonster, Unbounce and Zapier.

Pricing : Starts at $49/month (with a 14-day free trial).

Pros

Instantly see robust caller information based on previous interactions
Intelligent routing places leads with the right sales reps
Call recordings to capture data and transfer it into your CRM
Voicemail and caller ID capabilities
Reporting and analytics for performance tracking

Cons

Doesn’t include lead segmentation
Limited customisations
No email integration
7. Notion : Best for creating informational lead magnets

Notion is one of the most popular collaboration tools on the Internet. Founded in 2013, the platform has over 35 million users worldwide. While it’s known primarily for its advanced note-taking capabilities, Notion is also a simple tool you can use to create informational lead magnets.
Why Notion ? Notion is a simple yet powerful tool you can use to create almost anything. If you want to generate more leads, then creating a free info product with Notion is a simple and effective way to do that. It enables you to create ebooks, digital courses and video courses without having to rely on expensive software.

Standout features : Documentation tools, note-taking, collaborative documents and duplication capabilities. It’s simple to create a high-value informational product, like an ebook or course with multiple chapters.

Integrations : Audienceful, Miro, Momentum, Slack, ChatGPT, Clockify, Desktop.com, SureTriggers, Trello and Google Drive.

Pricing : Starts at $8/month (no free trial available).

Pros

Easy to create a digital product or lead magnet
Leads have access with a simple link
Lead magnet can be updated in real time
AI writing assistant
Drag-and-drop functionality
User-friendly interface
Low-cost pricing plans

Cons

No free trial available (though there is a free version)
Search function could use some improvement
Performance isn’t the fastest
Use Matomo to generate more leads

If you want more leads, then you need to start tracking your website’s forms.

With Matomo, you get access to features like Form Analytics, A/B Testing, Heatmaps, and Session Recordings to help with conversion rate optimisation.

Recently, Concrete CMS leveraged Matomo’s funnel analysis feature to improve its lead capture. The CMS was then able to identify bottlenecks in user onboarding. Matomo’s insights showed that users were getting stuck at the address input stage of the form.

By tweaking their form, Concrete CMS tripled their leads in just a few days.

If you want to improve your lead generation, then get started with Matomo’s 21-day free trial today. No credit card required.

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avcodec/x86/vvc : add avg and avg_w AVX2 optimizations

23 janvier 2024, par Wu Jianhua

avcodec/x86/vvc : add avg and avg_w AVX2 optimizations

The avg/avg_w is based on dav1d.
See https://code.videolan.org/videolan/dav1d/-/blob/master/src/x86/mc_avx2.asm

vvc_avg_8_2x2_c : 71.6
vvc_avg_8_2x2_avx2 : 26.8
vvc_avg_8_2x4_c : 140.8
vvc_avg_8_2x4_avx2 : 34.6
vvc_avg_8_2x8_c : 410.3
vvc_avg_8_2x8_avx2 : 41.3
vvc_avg_8_2x16_c : 769.3
vvc_avg_8_2x16_avx2 : 60.3
vvc_avg_8_2x32_c : 1669.6
vvc_avg_8_2x32_avx2 : 105.1
vvc_avg_8_2x64_c : 1978.3
vvc_avg_8_2x64_avx2 : 425.8
vvc_avg_8_2x128_c : 6536.8
vvc_avg_8_2x128_avx2 : 1315.1
vvc_avg_8_4x2_c : 155.6
vvc_avg_8_4x2_avx2 : 26.1
vvc_avg_8_4x4_c : 250.3
vvc_avg_8_4x4_avx2 : 31.3
vvc_avg_8_4x8_c : 831.8
vvc_avg_8_4x8_avx2 : 41.3
vvc_avg_8_4x16_c : 1461.1
vvc_avg_8_4x16_avx2 : 57.1
vvc_avg_8_4x32_c : 2821.6
vvc_avg_8_4x32_avx2 : 105.1
vvc_avg_8_4x64_c : 3615.8
vvc_avg_8_4x64_avx2 : 412.6
vvc_avg_8_4x128_c : 11962.6
vvc_avg_8_4x128_avx2 : 1274.3
vvc_avg_8_8x2_c : 215.8
vvc_avg_8_8x2_avx2 : 29.1
vvc_avg_8_8x4_c : 430.6
vvc_avg_8_8x4_avx2 : 37.6
vvc_avg_8_8x8_c : 1463.3
vvc_avg_8_8x8_avx2 : 51.8
vvc_avg_8_8x16_c : 2630.1
vvc_avg_8_8x16_avx2 : 97.6
vvc_avg_8_8x32_c : 5813.8
vvc_avg_8_8x32_avx2 : 196.6
vvc_avg_8_8x64_c : 6687.3
vvc_avg_8_8x64_avx2 : 487.8
vvc_avg_8_8x128_c : 13178.6
vvc_avg_8_8x128_avx2 : 1290.6
vvc_avg_8_16x2_c : 443.8
vvc_avg_8_16x2_avx2 : 28.3
vvc_avg_8_16x4_c : 1253.3
vvc_avg_8_16x4_avx2 : 32.1
vvc_avg_8_16x8_c : 2236.3
vvc_avg_8_16x8_avx2 : 44.3
vvc_avg_8_16x16_c : 5127.8
vvc_avg_8_16x16_avx2 : 63.3
vvc_avg_8_16x32_c : 6573.3
vvc_avg_8_16x32_avx2 : 223.6
vvc_avg_8_16x64_c : 30311.8
vvc_avg_8_16x64_avx2 : 437.8
vvc_avg_8_16x128_c : 25693.3
vvc_avg_8_16x128_avx2 : 1266.8
vvc_avg_8_32x2_c : 954.6
vvc_avg_8_32x2_avx2 : 32.1
vvc_avg_8_32x4_c : 2359.6
vvc_avg_8_32x4_avx2 : 39.6
vvc_avg_8_32x8_c : 5703.6
vvc_avg_8_32x8_avx2 : 57.1
vvc_avg_8_32x16_c : 9967.6
vvc_avg_8_32x16_avx2 : 107.1
vvc_avg_8_32x32_c : 21327.6
vvc_avg_8_32x32_avx2 : 272.6
vvc_avg_8_32x64_c : 39240.8
vvc_avg_8_32x64_avx2 : 529.6
vvc_avg_8_32x128_c : 52580.8
vvc_avg_8_32x128_avx2 : 1338.8
vvc_avg_8_64x2_c : 1647.3
vvc_avg_8_64x2_avx2 : 38.8
vvc_avg_8_64x4_c : 5130.1
vvc_avg_8_64x4_avx2 : 58.8
vvc_avg_8_64x8_c : 6529.3
vvc_avg_8_64x8_avx2 : 88.3
vvc_avg_8_64x16_c : 19913.6
vvc_avg_8_64x16_avx2 : 162.3
vvc_avg_8_64x32_c : 39360.8
vvc_avg_8_64x32_avx2 : 295.8
vvc_avg_8_64x64_c : 49658.3
vvc_avg_8_64x64_avx2 : 784.1
vvc_avg_8_64x128_c : 108513.1
vvc_avg_8_64x128_avx2 : 1977.1
vvc_avg_8_128x2_c : 3226.1
vvc_avg_8_128x2_avx2 : 61.1
vvc_avg_8_128x4_c : 10280.3
vvc_avg_8_128x4_avx2 : 94.6
vvc_avg_8_128x8_c : 18079.3
vvc_avg_8_128x8_avx2 : 155.3
vvc_avg_8_128x16_c : 45121.8
vvc_avg_8_128x16_avx2 : 285.3
vvc_avg_8_128x32_c : 48651.8
vvc_avg_8_128x32_avx2 : 581.6
vvc_avg_8_128x64_c : 165078.6
vvc_avg_8_128x64_avx2 : 1942.8
vvc_avg_8_128x128_c : 339103.1
vvc_avg_8_128x128_avx2 : 4332.6
vvc_avg_10_2x2_c : 144.3
vvc_avg_10_2x2_avx2 : 26.8
vvc_avg_10_2x4_c : 142.6
vvc_avg_10_2x4_avx2 : 45.3
vvc_avg_10_2x8_c : 478.1
vvc_avg_10_2x8_avx2 : 38.1
vvc_avg_10_2x16_c : 518.3
vvc_avg_10_2x16_avx2 : 58.1
vvc_avg_10_2x32_c : 2059.8
vvc_avg_10_2x32_avx2 : 93.1
vvc_avg_10_2x64_c : 2383.8
vvc_avg_10_2x64_avx2 : 714.8
vvc_avg_10_2x128_c : 4498.3
vvc_avg_10_2x128_avx2 : 1466.3
vvc_avg_10_4x2_c : 228.6
vvc_avg_10_4x2_avx2 : 26.8
vvc_avg_10_4x4_c : 378.3
vvc_avg_10_4x4_avx2 : 30.6
vvc_avg_10_4x8_c : 866.8
vvc_avg_10_4x8_avx2 : 44.6
vvc_avg_10_4x16_c : 1018.1
vvc_avg_10_4x16_avx2 : 58.1
vvc_avg_10_4x32_c : 3590.8
vvc_avg_10_4x32_avx2 : 128.8
vvc_avg_10_4x64_c : 4200.8
vvc_avg_10_4x64_avx2 : 663.6
vvc_avg_10_4x128_c : 8450.8
vvc_avg_10_4x128_avx2 : 1531.8
vvc_avg_10_8x2_c : 369.3
vvc_avg_10_8x2_avx2 : 28.3
vvc_avg_10_8x4_c : 513.8
vvc_avg_10_8x4_avx2 : 32.1
vvc_avg_10_8x8_c : 1720.3
vvc_avg_10_8x8_avx2 : 49.1
vvc_avg_10_8x16_c : 1894.8
vvc_avg_10_8x16_avx2 : 71.6
vvc_avg_10_8x32_c : 3931.3
vvc_avg_10_8x32_avx2 : 148.1
vvc_avg_10_8x64_c : 7964.3
vvc_avg_10_8x64_avx2 : 613.1
vvc_avg_10_8x128_c : 15540.1
vvc_avg_10_8x128_avx2 : 1585.1
vvc_avg_10_16x2_c : 877.3
vvc_avg_10_16x2_avx2 : 27.6
vvc_avg_10_16x4_c : 955.8
vvc_avg_10_16x4_avx2 : 29.8
vvc_avg_10_16x8_c : 3419.6
vvc_avg_10_16x8_avx2 : 62.6
vvc_avg_10_16x16_c : 3826.8
vvc_avg_10_16x16_avx2 : 54.3
vvc_avg_10_16x32_c : 7655.3
vvc_avg_10_16x32_avx2 : 86.3
vvc_avg_10_16x64_c : 30011.1
vvc_avg_10_16x64_avx2 : 692.6
vvc_avg_10_16x128_c : 47894.8
vvc_avg_10_16x128_avx2 : 1580.3
vvc_avg_10_32x2_c : 944.3
vvc_avg_10_32x2_avx2 : 29.8
vvc_avg_10_32x4_c : 2022.6
vvc_avg_10_32x4_avx2 : 35.1
vvc_avg_10_32x8_c : 6148.8
vvc_avg_10_32x8_avx2 : 51.3
vvc_avg_10_32x16_c : 12601.6
vvc_avg_10_32x16_avx2 : 70.8
vvc_avg_10_32x32_c : 15958.6
vvc_avg_10_32x32_avx2 : 124.3
vvc_avg_10_32x64_c : 31784.6
vvc_avg_10_32x64_avx2 : 757.3
vvc_avg_10_32x128_c : 63892.8
vvc_avg_10_32x128_avx2 : 1711.3
vvc_avg_10_64x2_c : 1890.8
vvc_avg_10_64x2_avx2 : 34.3
vvc_avg_10_64x4_c : 6267.3
vvc_avg_10_64x4_avx2 : 42.6
vvc_avg_10_64x8_c : 12778.1
vvc_avg_10_64x8_avx2 : 67.8
vvc_avg_10_64x16_c : 22304.3
vvc_avg_10_64x16_avx2 : 116.8
vvc_avg_10_64x32_c : 30777.1
vvc_avg_10_64x32_avx2 : 201.1
vvc_avg_10_64x64_c : 60169.1
vvc_avg_10_64x64_avx2 : 1454.3
vvc_avg_10_64x128_c : 124392.8
vvc_avg_10_64x128_avx2 : 3648.6
vvc_avg_10_128x2_c : 3650.1
vvc_avg_10_128x2_avx2 : 41.1
vvc_avg_10_128x4_c : 22887.8
vvc_avg_10_128x4_avx2 : 64.1
vvc_avg_10_128x8_c : 14622.6
vvc_avg_10_128x8_avx2 : 111.6
vvc_avg_10_128x16_c : 62207.6
vvc_avg_10_128x16_avx2 : 186.3
vvc_avg_10_128x32_c : 59761.3
vvc_avg_10_128x32_avx2 : 374.6
vvc_avg_10_128x64_c : 117504.3
vvc_avg_10_128x64_avx2 : 2684.6
vvc_avg_10_128x128_c : 236767.6
vvc_avg_10_128x128_avx2 : 15278.1
vvc_avg_12_2x2_c : 78.6
vvc_avg_12_2x2_avx2 : 26.1
vvc_avg_12_2x4_c : 254.1
vvc_avg_12_2x4_avx2 : 30.6
vvc_avg_12_2x8_c : 261.8
vvc_avg_12_2x8_avx2 : 39.1
vvc_avg_12_2x16_c : 527.6
vvc_avg_12_2x16_avx2 : 57.3
vvc_avg_12_2x32_c : 1089.1
vvc_avg_12_2x32_avx2 : 93.8
vvc_avg_12_2x64_c : 2337.6
vvc_avg_12_2x64_avx2 : 707.1
vvc_avg_12_2x128_c : 4582.1
vvc_avg_12_2x128_avx2 : 1414.6
vvc_avg_12_4x2_c : 129.6
vvc_avg_12_4x2_avx2 : 26.8
vvc_avg_12_4x4_c : 427.3
vvc_avg_12_4x4_avx2 : 30.6
vvc_avg_12_4x8_c : 529.6
vvc_avg_12_4x8_avx2 : 36.6
vvc_avg_12_4x16_c : 1022.1
vvc_avg_12_4x16_avx2 : 57.3
vvc_avg_12_4x32_c : 1987.6
vvc_avg_12_4x32_avx2 : 84.3
vvc_avg_12_4x64_c : 4147.6
vvc_avg_12_4x64_avx2 : 706.3
vvc_avg_12_4x128_c : 8469.3
vvc_avg_12_4x128_avx2 : 1448.3
vvc_avg_12_8x2_c : 253.6
vvc_avg_12_8x2_avx2 : 27.6
vvc_avg_12_8x4_c : 836.3
vvc_avg_12_8x4_avx2 : 32.1
vvc_avg_12_8x8_c : 1074.6
vvc_avg_12_8x8_avx2 : 45.1
vvc_avg_12_8x16_c : 3616.8
vvc_avg_12_8x16_avx2 : 71.6
vvc_avg_12_8x32_c : 3823.6
vvc_avg_12_8x32_avx2 : 140.1
vvc_avg_12_8x64_c : 7764.8
vvc_avg_12_8x64_avx2 : 656.1
vvc_avg_12_8x128_c : 15896.1
vvc_avg_12_8x128_avx2 : 1232.8
vvc_avg_12_16x2_c : 462.1
vvc_avg_12_16x2_avx2 : 26.8
vvc_avg_12_16x4_c : 1732.1
vvc_avg_12_16x4_avx2 : 29.1
vvc_avg_12_16x8_c : 2097.6
vvc_avg_12_16x8_avx2 : 62.6
vvc_avg_12_16x16_c : 6753.1
vvc_avg_12_16x16_avx2 : 47.8
vvc_avg_12_16x32_c : 7373.1
vvc_avg_12_16x32_avx2 : 80.8
vvc_avg_12_16x64_c : 15046.3
vvc_avg_12_16x64_avx2 : 621.1
vvc_avg_12_16x128_c : 52574.6
vvc_avg_12_16x128_avx2 : 1417.1
vvc_avg_12_32x2_c : 1712.1
vvc_avg_12_32x2_avx2 : 29.8
vvc_avg_12_32x4_c : 2036.8
vvc_avg_12_32x4_avx2 : 37.6
vvc_avg_12_32x8_c : 4017.6
vvc_avg_12_32x8_avx2 : 44.1
vvc_avg_12_32x16_c : 8018.6
vvc_avg_12_32x16_avx2 : 70.8
vvc_avg_12_32x32_c : 15637.6
vvc_avg_12_32x32_avx2 : 124.3
vvc_avg_12_32x64_c : 31143.3
vvc_avg_12_32x64_avx2 : 830.3
vvc_avg_12_32x128_c : 75706.8
vvc_avg_12_32x128_avx2 : 1604.8
vvc_avg_12_64x2_c : 3230.3
vvc_avg_12_64x2_avx2 : 33.6
vvc_avg_12_64x4_c : 4139.6
vvc_avg_12_64x4_avx2 : 45.1
vvc_avg_12_64x8_c : 8201.6
vvc_avg_12_64x8_avx2 : 67.1
vvc_avg_12_64x16_c : 25632.3
vvc_avg_12_64x16_avx2 : 110.3
vvc_avg_12_64x32_c : 30744.3
vvc_avg_12_64x32_avx2 : 200.3
vvc_avg_12_64x64_c : 105554.8
vvc_avg_12_64x64_avx2 : 1325.6
vvc_avg_12_64x128_c : 235254.3
vvc_avg_12_64x128_avx2 : 3132.6
vvc_avg_12_128x2_c : 6194.3
vvc_avg_12_128x2_avx2 : 55.1
vvc_avg_12_128x4_c : 7583.8
vvc_avg_12_128x4_avx2 : 79.3
vvc_avg_12_128x8_c : 14635.6
vvc_avg_12_128x8_avx2 : 104.3
vvc_avg_12_128x16_c : 29270.8
vvc_avg_12_128x16_avx2 : 194.3
vvc_avg_12_128x32_c : 60113.6
vvc_avg_12_128x32_avx2 : 346.3
vvc_avg_12_128x64_c : 197030.3
vvc_avg_12_128x64_avx2 : 2779.6
vvc_avg_12_128x128_c : 432809.6
vvc_avg_12_128x128_avx2 : 5513.3
vvc_w_avg_8_2x2_c : 84.3
vvc_w_avg_8_2x2_avx2 : 42.6
vvc_w_avg_8_2x4_c : 156.3
vvc_w_avg_8_2x4_avx2 : 58.8
vvc_w_avg_8_2x8_c : 310.6
vvc_w_avg_8_2x8_avx2 : 73.1
vvc_w_avg_8_2x16_c : 942.1
vvc_w_avg_8_2x16_avx2 : 113.3
vvc_w_avg_8_2x32_c : 1098.8
vvc_w_avg_8_2x32_avx2 : 202.6
vvc_w_avg_8_2x64_c : 2414.3
vvc_w_avg_8_2x64_avx2 : 467.6
vvc_w_avg_8_2x128_c : 4763.8
vvc_w_avg_8_2x128_avx2 : 1333.1
vvc_w_avg_8_4x2_c : 140.1
vvc_w_avg_8_4x2_avx2 : 49.8
vvc_w_avg_8_4x4_c : 276.3
vvc_w_avg_8_4x4_avx2 : 58.1
vvc_w_avg_8_4x8_c : 524.3
vvc_w_avg_8_4x8_avx2 : 72.3
vvc_w_avg_8_4x16_c : 1108.1
vvc_w_avg_8_4x16_avx2 : 111.8
vvc_w_avg_8_4x32_c : 2149.8
vvc_w_avg_8_4x32_avx2 : 199.6
vvc_w_avg_8_4x64_c : 12288.1
vvc_w_avg_8_4x64_avx2 : 509.3
vvc_w_avg_8_4x128_c : 8398.6
vvc_w_avg_8_4x128_avx2 : 1319.6
vvc_w_avg_8_8x2_c : 271.1
vvc_w_avg_8_8x2_avx2 : 44.1
vvc_w_avg_8_8x4_c : 503.3
vvc_w_avg_8_8x4_avx2 : 61.8
vvc_w_avg_8_8x8_c : 1031.1
vvc_w_avg_8_8x8_avx2 : 93.8
vvc_w_avg_8_8x16_c : 2009.8
vvc_w_avg_8_8x16_avx2 : 163.1
vvc_w_avg_8_8x32_c : 4161.3
vvc_w_avg_8_8x32_avx2 : 292.1
vvc_w_avg_8_8x64_c : 7940.6
vvc_w_avg_8_8x64_avx2 : 592.1
vvc_w_avg_8_8x128_c : 16802.3
vvc_w_avg_8_8x128_avx2 : 1287.6
vvc_w_avg_8_16x2_c : 762.6
vvc_w_avg_8_16x2_avx2 : 53.6
vvc_w_avg_8_16x4_c : 1486.3
vvc_w_avg_8_16x4_avx2 : 67.1
vvc_w_avg_8_16x8_c : 1907.8
vvc_w_avg_8_16x8_avx2 : 96.8
vvc_w_avg_8_16x16_c : 3883.6
vvc_w_avg_8_16x16_avx2 : 151.3
vvc_w_avg_8_16x32_c : 7974.8
vvc_w_avg_8_16x32_avx2 : 285.8
vvc_w_avg_8_16x64_c : 25160.6
vvc_w_avg_8_16x64_avx2 : 589.8
vvc_w_avg_8_16x128_c : 58328.1
vvc_w_avg_8_16x128_avx2 : 1169.8
vvc_w_avg_8_32x2_c : 1009.1
vvc_w_avg_8_32x2_avx2 : 65.6
vvc_w_avg_8_32x4_c : 2091.1
vvc_w_avg_8_32x4_avx2 : 96.8
vvc_w_avg_8_32x8_c : 3997.8
vvc_w_avg_8_32x8_avx2 : 156.3
vvc_w_avg_8_32x16_c : 8216.8
vvc_w_avg_8_32x16_avx2 : 269.6
vvc_w_avg_8_32x32_c : 21746.1
vvc_w_avg_8_32x32_avx2 : 635.3
vvc_w_avg_8_32x64_c : 31564.8
vvc_w_avg_8_32x64_avx2 : 1010.6
vvc_w_avg_8_32x128_c : 114373.3
vvc_w_avg_8_32x128_avx2 : 2013.6
vvc_w_avg_8_64x2_c : 2067.3
vvc_w_avg_8_64x2_avx2 : 97.6
vvc_w_avg_8_64x4_c : 3901.1
vvc_w_avg_8_64x4_avx2 : 154.8
vvc_w_avg_8_64x8_c : 7911.6
vvc_w_avg_8_64x8_avx2 : 268.8
vvc_w_avg_8_64x16_c : 16508.8
vvc_w_avg_8_64x16_avx2 : 501.8
vvc_w_avg_8_64x32_c : 38770.3
vvc_w_avg_8_64x32_avx2 : 1287.6
vvc_w_avg_8_64x64_c : 110350.6
vvc_w_avg_8_64x64_avx2 : 1890.8
vvc_w_avg_8_64x128_c : 141354.6
vvc_w_avg_8_64x128_avx2 : 3839.6
vvc_w_avg_8_128x2_c : 7012.1
vvc_w_avg_8_128x2_avx2 : 159.3
vvc_w_avg_8_128x4_c : 8146.8
vvc_w_avg_8_128x4_avx2 : 272.6
vvc_w_avg_8_128x8_c : 24596.8
vvc_w_avg_8_128x8_avx2 : 501.1
vvc_w_avg_8_128x16_c : 35918.1
vvc_w_avg_8_128x16_avx2 : 948.8
vvc_w_avg_8_128x32_c : 68799.6
vvc_w_avg_8_128x32_avx2 : 1963.1
vvc_w_avg_8_128x64_c : 133862.1
vvc_w_avg_8_128x64_avx2 : 3833.6
vvc_w_avg_8_128x128_c : 348427.8
vvc_w_avg_8_128x128_avx2 : 7682.8
vvc_w_avg_10_2x2_c : 118.6
vvc_w_avg_10_2x2_avx2 : 73.1
vvc_w_avg_10_2x4_c : 189.1
vvc_w_avg_10_2x4_avx2 : 89.3
vvc_w_avg_10_2x8_c : 382.8
vvc_w_avg_10_2x8_avx2 : 179.8
vvc_w_avg_10_2x16_c : 658.3
vvc_w_avg_10_2x16_avx2 : 185.1
vvc_w_avg_10_2x32_c : 1409.3
vvc_w_avg_10_2x32_avx2 : 290.8
vvc_w_avg_10_2x64_c : 2906.8
vvc_w_avg_10_2x64_avx2 : 793.1
vvc_w_avg_10_2x128_c : 6292.6
vvc_w_avg_10_2x128_avx2 : 1696.8
vvc_w_avg_10_4x2_c : 178.8
vvc_w_avg_10_4x2_avx2 : 80.1
vvc_w_avg_10_4x4_c : 581.6
vvc_w_avg_10_4x4_avx2 : 97.6
vvc_w_avg_10_4x8_c : 693.3
vvc_w_avg_10_4x8_avx2 : 128.1
vvc_w_avg_10_4x16_c : 1436.6
vvc_w_avg_10_4x16_avx2 : 179.8
vvc_w_avg_10_4x32_c : 2409.1
vvc_w_avg_10_4x32_avx2 : 292.3
vvc_w_avg_10_4x64_c : 4925.3
vvc_w_avg_10_4x64_avx2 : 746.1
vvc_w_avg_10_4x128_c : 10664.6
vvc_w_avg_10_4x128_avx2 : 1647.6
vvc_w_avg_10_8x2_c : 359.3
vvc_w_avg_10_8x2_avx2 : 80.1
vvc_w_avg_10_8x4_c : 925.6
vvc_w_avg_10_8x4_avx2 : 97.6
vvc_w_avg_10_8x8_c : 1360.6
vvc_w_avg_10_8x8_avx2 : 121.8
vvc_w_avg_10_8x16_c : 3490.3
vvc_w_avg_10_8x16_avx2 : 203.3
vvc_w_avg_10_8x32_c : 5266.1
vvc_w_avg_10_8x32_avx2 : 325.8
vvc_w_avg_10_8x64_c : 11127.1
vvc_w_avg_10_8x64_avx2 : 747.8
vvc_w_avg_10_8x128_c : 31058.3
vvc_w_avg_10_8x128_avx2 : 1424.6
vvc_w_avg_10_16x2_c : 624.8
vvc_w_avg_10_16x2_avx2 : 84.6
vvc_w_avg_10_16x4_c : 1389.6
vvc_w_avg_10_16x4_avx2 : 109.1
vvc_w_avg_10_16x8_c : 2688.3
vvc_w_avg_10_16x8_avx2 : 137.1
vvc_w_avg_10_16x16_c : 5387.1
vvc_w_avg_10_16x16_avx2 : 224.6
vvc_w_avg_10_16x32_c : 10776.3
vvc_w_avg_10_16x32_avx2 : 312.1
vvc_w_avg_10_16x64_c : 18069.1
vvc_w_avg_10_16x64_avx2 : 858.6
vvc_w_avg_10_16x128_c : 43460.3
vvc_w_avg_10_16x128_avx2 : 1411.6
vvc_w_avg_10_32x2_c : 1232.8
vvc_w_avg_10_32x2_avx2 : 99.1
vvc_w_avg_10_32x4_c : 4017.6
vvc_w_avg_10_32x4_avx2 : 134.1
vvc_w_avg_10_32x8_c : 9306.3
vvc_w_avg_10_32x8_avx2 : 208.1
vvc_w_avg_10_32x16_c : 8424.6
vvc_w_avg_10_32x16_avx2 : 349.3
vvc_w_avg_10_32x32_c : 20787.8
vvc_w_avg_10_32x32_avx2 : 655.3
vvc_w_avg_10_32x64_c : 40972.1
vvc_w_avg_10_32x64_avx2 : 904.8
vvc_w_avg_10_32x128_c : 85670.3
vvc_w_avg_10_32x128_avx2 : 1751.6
vvc_w_avg_10_64x2_c : 2454.1
vvc_w_avg_10_64x2_avx2 : 132.6
vvc_w_avg_10_64x4_c : 5012.6
vvc_w_avg_10_64x4_avx2 : 215.6
vvc_w_avg_10_64x8_c : 10811.3
vvc_w_avg_10_64x8_avx2 : 361.1
vvc_w_avg_10_64x16_c : 33349.1
vvc_w_avg_10_64x16_avx2 : 904.1
vvc_w_avg_10_64x32_c : 41892.3
vvc_w_avg_10_64x32_avx2 : 1220.6
vvc_w_avg_10_64x64_c : 66983.3
vvc_w_avg_10_64x64_avx2 : 2622.1
vvc_w_avg_10_64x128_c : 246508.8
vvc_w_avg_10_64x128_avx2 : 3316.8
vvc_w_avg_10_128x2_c : 7791.6
vvc_w_avg_10_128x2_avx2 : 198.8
vvc_w_avg_10_128x4_c : 10534.3
vvc_w_avg_10_128x4_avx2 : 337.3
vvc_w_avg_10_128x8_c : 21142.3
vvc_w_avg_10_128x8_avx2 : 614.8
vvc_w_avg_10_128x16_c : 40968.6
vvc_w_avg_10_128x16_avx2 : 1160.6
vvc_w_avg_10_128x32_c : 113043.3
vvc_w_avg_10_128x32_avx2 : 1644.6
vvc_w_avg_10_128x64_c : 230658.3
vvc_w_avg_10_128x64_avx2 : 5065.3
vvc_w_avg_10_128x128_c : 335236.3
vvc_w_avg_10_128x128_avx2 : 6450.3
vvc_w_avg_12_2x2_c : 185.3
vvc_w_avg_12_2x2_avx2 : 43.6
vvc_w_avg_12_2x4_c : 340.3
vvc_w_avg_12_2x4_avx2 : 55.8
vvc_w_avg_12_2x8_c : 632.3
vvc_w_avg_12_2x8_avx2 : 70.1
vvc_w_avg_12_2x16_c : 728.3
vvc_w_avg_12_2x16_avx2 : 108.1
vvc_w_avg_12_2x32_c : 1392.6
vvc_w_avg_12_2x32_avx2 : 176.8
vvc_w_avg_12_2x64_c : 2618.3
vvc_w_avg_12_2x64_avx2 : 757.3
vvc_w_avg_12_2x128_c : 6408.8
vvc_w_avg_12_2x128_avx2 : 1435.1
vvc_w_avg_12_4x2_c : 349.3
vvc_w_avg_12_4x2_avx2 : 44.3
vvc_w_avg_12_4x4_c : 607.1
vvc_w_avg_12_4x4_avx2 : 52.6
vvc_w_avg_12_4x8_c : 1134.8
vvc_w_avg_12_4x8_avx2 : 70.1
vvc_w_avg_12_4x16_c : 1378.1
vvc_w_avg_12_4x16_avx2 : 115.3
vvc_w_avg_12_4x32_c : 2599.3
vvc_w_avg_12_4x32_avx2 : 174.3
vvc_w_avg_12_4x64_c : 4474.8
vvc_w_avg_12_4x64_avx2 : 656.1
vvc_w_avg_12_4x128_c : 11319.6
vvc_w_avg_12_4x128_avx2 : 1373.1
vvc_w_avg_12_8x2_c : 595.8
vvc_w_avg_12_8x2_avx2 : 44.3
vvc_w_avg_12_8x4_c : 1164.3
vvc_w_avg_12_8x4_avx2 : 56.6
vvc_w_avg_12_8x8_c : 2019.6
vvc_w_avg_12_8x8_avx2 : 80.1
vvc_w_avg_12_8x16_c : 4071.6
vvc_w_avg_12_8x16_avx2 : 139.3
vvc_w_avg_12_8x32_c : 4485.1
vvc_w_avg_12_8x32_avx2 : 250.6
vvc_w_avg_12_8x64_c : 8404.8
vvc_w_avg_12_8x64_avx2 : 735.8
vvc_w_avg_12_8x128_c : 35679.8
vvc_w_avg_12_8x128_avx2 : 1252.6
vvc_w_avg_12_16x2_c : 1114.8
vvc_w_avg_12_16x2_avx2 : 46.6
vvc_w_avg_12_16x4_c : 2240.1
vvc_w_avg_12_16x4_avx2 : 62.6
vvc_w_avg_12_16x8_c : 13174.6
vvc_w_avg_12_16x8_avx2 : 88.6
vvc_w_avg_12_16x16_c : 5334.6
vvc_w_avg_12_16x16_avx2 : 144.3
vvc_w_avg_12_16x32_c : 8378.1
vvc_w_avg_12_16x32_avx2 : 234.6
vvc_w_avg_12_16x64_c : 21300.8
vvc_w_avg_12_16x64_avx2 : 761.8
vvc_w_avg_12_16x128_c : 32786.8
vvc_w_avg_12_16x128_avx2 : 1432.8
vvc_w_avg_12_32x2_c : 2154.3
vvc_w_avg_12_32x2_avx2 : 61.1
vvc_w_avg_12_32x4_c : 4299.8
vvc_w_avg_12_32x4_avx2 : 83.1
vvc_w_avg_12_32x8_c : 7964.8
vvc_w_avg_12_32x8_avx2 : 132.6
vvc_w_avg_12_32x16_c : 13321.6
vvc_w_avg_12_32x16_avx2 : 234.6
vvc_w_avg_12_32x32_c : 21149.3
vvc_w_avg_12_32x32_avx2 : 433.3
vvc_w_avg_12_32x64_c : 43666.6
vvc_w_avg_12_32x64_avx2 : 876.6
vvc_w_avg_12_32x128_c : 83189.8
vvc_w_avg_12_32x128_avx2 : 1756.6
vvc_w_avg_12_64x2_c : 3829.8
vvc_w_avg_12_64x2_avx2 : 83.1
vvc_w_avg_12_64x4_c : 8588.1
vvc_w_avg_12_64x4_avx2 : 127.1
vvc_w_avg_12_64x8_c : 17027.6
vvc_w_avg_12_64x8_avx2 : 310.6
vvc_w_avg_12_64x16_c : 29797.8
vvc_w_avg_12_64x16_avx2 : 415.6
vvc_w_avg_12_64x32_c : 43854.3
vvc_w_avg_12_64x32_avx2 : 773.3
vvc_w_avg_12_64x64_c : 137767.3
vvc_w_avg_12_64x64_avx2 : 1608.6
vvc_w_avg_12_64x128_c : 316428.3
vvc_w_avg_12_64x128_avx2 : 3249.8
vvc_w_avg_12_128x2_c : 8824.6
vvc_w_avg_12_128x2_avx2 : 130.3
vvc_w_avg_12_128x4_c : 17173.6
vvc_w_avg_12_128x4_avx2 : 219.3
vvc_w_avg_12_128x8_c : 21997.8
vvc_w_avg_12_128x8_avx2 : 397.3
vvc_w_avg_12_128x16_c : 43553.8
vvc_w_avg_12_128x16_avx2 : 790.1
vvc_w_avg_12_128x32_c : 89792.1
vvc_w_avg_12_128x32_avx2 : 1497.6
vvc_w_avg_12_128x64_c : 226573.3
vvc_w_avg_12_128x64_avx2 : 3153.1
vvc_w_avg_12_128x128_c : 332090.1
vvc_w_avg_12_128x128_avx2 : 6499.6

Signed-off-by : Wu Jianhua <toqsxw@outlook.com>

[D H] libavcodec/x86/vvc/Makefile
[D H] libavcodec/x86/vvc/vvc_mc.asm
[D H] libavcodec/x86/vvc/vvcdsp_init.c

Unveiling GA4 Issues : 8 Questions from a Marketer That GA4 Can’t Answer

8 janvier 2024, par Alex
It’s hard to believe, but Universal Analytics had a lifespan of 11 years, from its announcement in March 2012. Despite occasional criticism, this service established standards for the entire web analytics industry. Many metrics and reports became benchmarks for a whole generation of marketers. It truly was an era.

For instance, a lot of marketers got used to starting each workday by inspecting dashboards and standard traffic reports in the Universal Analytics web interface. There were so, so many of those days. They became so accustomed to Universal Analytics that they would enter reports, manipulate numbers, and play with metrics almost on autopilot, without much thought.

However, six months have passed since the sunset of Universal Analytics – precisely on July 1, 2023, when Google stopped processing requests for resources using the previous version of Google Analytics. The time when data about visitors and their interactions with the website were more clearly structured within the UA paradigm is now in the past. GA4 has brought a plethora of opportunities to marketers, but along with those opportunities came a series of complexities.

GA4 issues

Since its initial announcement in 2020, GA4 has been plagued with errors and inconsistencies. It still has poor and sometimes illogical documentation, numerous restrictions, and peculiar interface solutions. But more importantly, the barrier to entry into web analytics has significantly increased.

If you diligently follow GA4 updates, read the documentation, and possess skills in working with data (SQL and basic statistics), you probably won’t feel any problems – you know how to set up a convenient and efficient environment for your product and marketing data. But what if you’re not that proficient ? That’s when issues arise.

In this article, we try to address a series of straightforward questions that less experienced users – marketers, project managers, SEO specialists, and others – want answers to. They have no time to delve into the intricacies of GA4 but seek access to the fundamentals crucial for their functionality.

Previously, in Universal Analytics, they could quickly and conveniently address their issues. Now, the situation has become, to put it mildly, more complex. We’ve identified 8 such questions for which the current version of GA4 either fails to provide answers or implies that answers would require significant enhancements. So, let’s dive into them one by one.

Question 1 : What are the most popular traffic sources on my website ?

Seemingly a straightforward question. What does GA4 tell us ? It responds with a question : “Which traffic source parameter are you interested in ?”
Wait, what ?

People just want to know which resources bring them the most traffic. Is that really an issue ?

Unfortunately, yes. In GA4, there are not one, not two, but three traffic source parameters :

Session source.
First User Source – the source of the first session for each user.
Just the source – determined at the event or conversion level.

If you wanted to open a report and draw conclusions quickly, we have bad news for you. Before you start ranking your traffic sources by popularity, you need to do some mental work on which parameter and in what context you will look. And even when you decide, you’ll need to make a choice in the selection of standard reports : work with the User Acquisition Report or Traffic Acquisition.

Yes, there is a difference between them : the first uses the First User Source parameter, and the second uses the session source. And you need to figure that out too.
Question 2 : What is my conversion rate ?

This question concerns everyone, and it should be simple, implying a straightforward answer. But no.
In GA4, there are three conversion metrics (yes, three) :

Session conversion – the percentage of sessions with a conversion.
User conversion – the percentage of users who completed a conversion.
First-time Purchaser Conversion – the share of active users who made their first purchase.

If the last metric doesn’t interest us much, GA4 users can still choose something from the remaining two. But what’s next ? Which parameters to use for comparison ? Session source or user source ? What if you want to see the conversion rate for a specific event ? And how do you do this in analyses rather than in standard reports ?

In the end, instead of an answer to a simple question, marketers get a bunch of new questions.
Question 3. Can I trust user and session metrics ?

Unfortunately, no. This may boggle the mind of those not well-versed in the mechanics of calculating user and session metrics, but it’s the plain truth : the numbers in GA4 and those in reality may and will differ.

The reason is that GA4 uses the HyperLogLog++ statistical algorithm to count unique values. Without delving into details, it’s a mechanism for approximate estimation of a metric with a certain level of error.

This error level is quite well-documented. For instance, for the Total Users metric, the error level is 1.63% (for a 95% confidence interval). In simple terms, this means that 100,000 users in the GA4 interface equate to 100,000 1.63% in reality.

Furthermore – but this is no surprise to anyone – GA4 samples data. This means that with too large a sample size or when using a large number of parameters, the application will assess your metrics based on a partial sample – let’s say 5, 10, or 30% of the entire population.

It’s a reasonable assumption, but it can (and probably will) surprise marketers – the metrics will deviate from reality. All end-users can do (excluding delving into raw data methodologies) is to take this error level into account in their conclusions.

Question 4. How do I calculate First Click attribution ?

You can’t. Unfortunately, as of late, GA4 offers only three attribution models available in the Attribution tab : Last Click, Last Click For Google Ads, and Data Driven. First Click attribution is essential for understanding where and when demand is generated. In the previous version of Google Analytics (and until recently, in the current one), users could quickly apply First Click and other attribution models, compare them, and gain insights. Now, this capability is gone.

Certainly, you can look at the conversion distribution considering the First User Source parameter – this will be some proxy for First Click attribution. However, comparing it with others in the Model Comparison tab won’t be possible. In the context of the GA4 interface, it makes sense to forget about non-standard attribution models.

Question 5. How do I account for intra-session traffic ?

Intra-session traffic essentially refers to a change in traffic sources within a session. Imagine a scenario where a user comes to your site organically from Google and, within a minute, comes from an email campaign. In the previous version of Google Analytics, a new session with the traffic source “e-mail” would be created in such a case. But now, the situation has changed.

A session now only ends in the case of a timeout – say, 30 minutes without interaction. This means a session will always have a source from which it started. If a user changes the source within a session (clicks on an ad, from email campaigns, and so on), you won’t know anything about it until they convert. This is a significant blow to intra-session traffic since their contribution to traffic remains virtually unnoticed.

Question 6. How can I account for users who have not consented to the use of third-party cookies ?

You can’t. Google Consent Mode settings imply several options when a user rejects the use of 3rd party cookies. In GA4 and BigQuery, depersonalized cookieless pings will be sent. These pings do not contain specific client_id, session_id, or other custom dimensions. As a result, you won’t be able to consider them as users or link the actions of such users together.

Question 7. How can I compare data in explorations with the previous year ?

The maximum data retention period for a free GA4 account is 14 months. This means that if the date range is wider, you can only use standard reports. You won’t be able to compare or view cohorts or funnels for periods more than 14 months ago. This makes the product functionality less rich because various report formats in explorations are very convenient for comparing specific metrics in easily digestible reports.

Of course, you always have the option to connect BigQuery and store raw data without limitations, but this process usually requires the involvement of an advanced analyst. And precisely this option is unavailable to most marketers in small teams.

Question 8. Is the data for yesterday accurate ?

Unknown. Google declares that data processing in GA4 takes up to 48 hours. And although this process is faster, most users still have room for frustration. And they can be understood.

What does “data processing takes 24-48 hours” mean ? When will the data in reports be complete ? For yesterday ? Or the day before yesterday ? Or for all days that were more than two days ago ? Unclear. What should marketers tell their managers when they were asked if all the data is in this report ? Well, probably all of it… or maybe not… Let’s wait for 48 hours…

Undoubtedly, computational resources and time are needed for data preprocessing and aggregation. It’s okay that data for today will not be up-to-date. And probably not for yesterday either. But people just want to know when they can trust their data. Are they asking for too much : just a note that this report contains all the data sent and processed by Google Analytics ?

What should you do ?

Credit should be given to the Google team – they have done a lot to enable users to answer these questions in one form or another. For example, you can use data streaming in BigQuery and work with raw data. The entry threshold for this functionality has been significantly lowered. In fact, if you are dissatisfied with the GA4 interface, you can organize your export to BigQuery and create your own reports without (almost) any restrictions.

Another strong option is the widespread launch of GTM Server Side. This allows you to quite freely modify the event model and essentially enrich each hit with various parameters, doing this in a first-party context. This, of course, reduces the harmful impact of most of the limitations described in this text.

But this is not a solution.

The users in question – marketers, managers, developers – they do not want or do not have the time for a deep dive into the issue. And they want simple answers to simple (it seemed) questions. And for now, unfortunately, GA4 is more of a professional tool for analysts than a convenient instrument for generating insights for not very advanced users.

Why is this such a serious issue ?

The thing is – and this is crucial – over the past 10 years, Google has managed to create a sort of GA-bubble for marketers. Many of them have become so accustomed to Google Analytics that when faced with another issue, they don’t venture to explore alternative solutions but attempt to solve it on their own. And almost always, this turns out to be expensive and inconvenient.

However, with the latest updates to GA4, it is becoming increasingly evident that this application is struggling to address even the most basic questions from users. And these questions are not fantastically complex. Much of what was described in this article is not an unsolvable mystery and is successfully addressed by other analytics services.

Let’s try to answer some of the questions described from the perspective of Matomo.

Question 1 : What are the most popular traffic sources ? [Solved]

In the Acquisition panel, you will find at least three easily identifiable reports – for traffic channels (All Channels), sources (Websites), and campaigns (Campaigns).

With these, you can quickly and easily answer the question about the most popular traffic sources, and if needed, delve into more detailed information, such as landing pages.

Question 2 : What is my conversion rate ? [Solved]

Under Goals in Matomo, you’ll easily find the overall conversion rate for your site. Below that you’ll have access to the conversion rate of each goal you’ve set in your Matomo instance.

Question 3 : Can I trust user and session metrics ? [Solved]

Yes. With Matomo, you’re guaranteed 100% accurate data. Matomo does not apply sampling, does not employ specific statistical algorithms, or any analogs of threshold values. Yes, it is possible, and it’s perfectly normal. If you see a metric in the visits or users field, it accurately represents reality by 100%.

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Question 4 : How do I calculate First Click attribution ? [Solved]

You can do this in the same section where the other 5 attribution models, available in Matomo, are calculated – in the Multi Attribution section.

You can choose a specific conversion and, in a few clicks, calculate and compare up to 3 marketing attribution models. This means you don’t have to spend several days digging through documentation trying to understand how a particular model is calculated. Have a question – get an answer.

Question 5 : How do I account for intra-session traffic ? [Solved]

Matomo creates a new visit when a user changes a campaign. This means that you will accurately capture all relevant traffic if it is adequately tagged. No campaigns will be lost within a visit, as they will have a new utm_campaign parameter.

This is a crucial point because when the Referrer changes, a new visit is not created, but the key lies in something else – accounting for all available traffic becomes your responsibility and depends on how you tag it.

Try Matomo for Free

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

Start for free

No credit card required

Question 6 : How can I account for users who have not consented to the use of third-party cookies ? [Solved]

Google Analytics requires users to accept a cookie consent banner with “analytics_storage=granted” to track them. If users reject cookie consent banners, however, then Google Analytics can’t track these visitors at all. They simply won’t show up in your traffic reports.

Matomo doesn’t require cookie consent banners (apart from in the United Kingdom and Germany) and can therefore continue to track visitors even after they have rejected a cookie consent screen. This is achieved through a config_id variable (the user identifier equivalent which is updating once a day).

This means that virtually all of your website traffic will be tracked regardless of whether users accept a cookie consent banner or not.

Question 7 : How can I compare data in explorations with the previous year ? [Solved]

There is no limitation on data retention for your aggregated reports in Matomo. The essence of Matomo experience lies in the reporting data, and consequently, retaining reports indefinitely is a viable option. So you can compare data for any timeframe. 7