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• FFmpeg error : ratecontrol_init : can't open stats file

  6 octobre 2017, par oldo.nicho

  I’ve setup an AWS EC2 instance running Ubuntu 14.04 and have installed FFmpeg so that I can compress and transcode video.

  I’m trying to do a two pass conversion with the following code :

  ffmpeg -i input-file.avi -codec:v libx264 -profile:v high -preset slow -b:v 500k -maxrate 500k -bufsize 1000k -vf scale=702:-1 -threads 0 -pass 1 -an -f mp4 ~/encoded/null

  and second pass :

  ffmpeg -i input-file.avi -codec:v libx264 -profile:v high -preset slow -b:v 500k -maxrate 500k -bufsize 1000k -vf scale=702:-1 -threads 0 -pass 2 -codec:a libfdk_aac -b:a 128k -f mp4 output-file.mp4

  However I get the following error :

  ffmpeg version N-77283-g91c2a33 Copyright (c) 2000-2015 the FFmpeg developers
  
    built with gcc 4.8 (Ubuntu 4.8.4-2ubuntu1~14.04)
  
    configuration: --prefix=/home/ubuntu/ffmpeg_build --pkg-config-flags=--static --extra-cflags=-I/home/ubuntu/ffmpeg_build/include --extra-ldflags=-L/home/ubuntu/ffmpeg_build/lib --bindir=/home/ubuntu/bin --enable-gpl --enable-libass --enable-libfdk-aac --enable-libfreetype --enable-libmp3lame --enable-libopus --enable-libtheora --enable-libvorbis --enable-libx264 --enable-nonfree
  
    libavutil      55. 11.100 / 55. 11.100
  
    libavcodec     57. 17.100 / 57. 17.100
  
    libavformat    57. 20.100 / 57. 20.100
  
    libavdevice    57.  0.100 / 57.  0.100
  
    libavfilter     6. 21.100 /  6. 21.100
  
    libswscale      4.  0.100 /  4.  0.100
  
    libswresample   2.  0.101 /  2.  0.101
  
    libpostproc    54.  0.100 / 54.  0.100
  
  Input #0, avi, from 'input-file.avi':
  
    Duration: 01:18:05.29, start: 0.000000, bitrate: 2025 kb/s
  
      Stream #0:0: Video: mpeg4 (Simple Profile) (XVID / 0x44495658), yuv420p, 720x480 [SAR 1:1 DAR 3:2], 1789 kb/s, 29.97 fps, 29.97 tbr, 29.97 tbn, 29.97 tbc
  
      Stream #0:1: Audio: ac3 ([0] [0][0] / 0x2000), 48000 Hz, stereo, fltp, 224 kb/s
  
  [libx264 @ 0x1e04240] using SAR=1/1
  
  [libx264 @ 0x1e04240] using cpu capabilities: MMX2 SSE2Fast SSSE3 SSE4.2 AVX AVX2 FMA3 LZCNT BMI2
  
  [libx264 @ 0x1e04240] ratecontrol_init: can't open stats file
  
  Output #0, mp4, to '/home/ubuntu/encoded/null':
  
      Stream #0:0: Video: h264, none, q=2-31, 128 kb/s, SAR 1:1 DAR 0:0, 29.97 fps
  
      Metadata:
  
        encoder         : Lavc57.17.100 libx264
  
  Stream mapping:
  
    Stream #0:0 -> #0:0 (mpeg4 (native) -> h264 (libx264))
  
  Error while opening encoder for output stream #0:0 - maybe incorrect parameters such as bit_rate, rate, width or height

  The command as written above works fine on my local computer (running OSX). Would anyone have any suggestions as to how to fix this problem ?

• What is audience segmentation ? The 8 main types and examples

  8 juillet, par Joe

  Marketers must reach the right person at the right time with the most relevant messaging. Customers now expect personalised experiences, which means generic campaigns won’t work. Audience segmentation is the key to doing this. 

  This isn’t an easy process because there are many types of audience segmentation. The wrong approach or poor data management can lead to irrelevant messaging or lost customer trust.

  This article breaks down the most common types of audience segmentation with examples highlighting their usefulness and information on segmenting campaigns without breaking data regulations.

  What is audience segmentation ?

  Audience segmentation involves dividing a customer base into distinct, smaller groups with similar traits or common characteristics. 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.

  Consider this : an urban office worker and a rural farmer have vastly different needs. Targeted marketing efforts aimed at agriculture workers in rural areas can stir up interest 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. For example, they would run a golf club ad in a golf magazine, not the national newspaper.

  Now that businesses have more customer data, audience segments can be narrower and more specific.

  Why audience segmentation matters

  Hyken’s latest Customer Service and CX Research Study revealed that 81% of customers expect a personalised experience.

  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 relevant product recommendations — like a shoe polishing kit after buying nice leather loafers.

  Without audience segmentation, customers can get frustrated with post-sale activities. For example, the same follow-up email won’t make sense for all customers because each is at a different stage of the user journey. 

  Some more benefits that audience segmentation offers : 

  • Personalised targeting is a major advantage. Tailored messaging makes customers feel valued and understood, enhancing their loyalty to the brand. 
  • Businesses can understand users’ unique needs, which helps in better product development. For example, a fitness brand might develop separate offerings for casual exercisers and professional athletes.
  • Marketers can allocate more resources to the most promising segments. For example, a luxury skincare brand might target affluent customers with premium ads and use broader campaigns for entry-level products.

  8 types of audience segmentation

  There are eight types of audience segmentation : demographic, behavioural, psychographic, technographic, transactional, contextual, lifecycle and predictive segmentation.

  

  Let’s take an in-depth look at each of them.

  Demographic segmentation 

  Demographic segmentation divides a larger audience based on data points like location, age or other factors.

  The most basic segmentation factor is location, which is critical in marketing campaigns. Geographic segmentation can use IP addresses to separate marketing efforts by country. 

  But more advanced demographic data points are becoming increasingly sensitive to handle, especially in Europe, where the GDPR makes advanced demographics a more tentative subject. 

  It’s also possible to use age, education level, and occupation to target marketing campaigns. It’s essential to navigate this terrain thoughtfully, responsibly, and strictly adhere to privacy regulations.

  Potential data points :

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

  Example of effective demographic segmentation :

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

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

  

  (Image Source)

  Each collection features 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 — just single out the factors when building a campaign. And it’s unnecessary to rely on data mining to get information for segmentation. 

  Consider incorporating a short survey into email sign-up forms so people can self-select their interests and preferences. This is a great way to segment ethically and without the need for data-mining companies. Responses can offer valuable insights into audience preferences while enhancing engagement, decreasing bounce rates, and improving conversion rates.

  Behavioural segmentation

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

  Potential data points :

  • Page visits
  • Referral source
  • Clicks
  • Downloads
  • Video plays
  • Conversions (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 like Matomo to uncover patterns. By segmenting actions like specific clicks and downloads, identify what can significantly enhance visitor conversions. 

  

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

  Then, set up a conditional CTA within the video player. Make it pop up after the user finishes watching the video. Use a specific form and assign it to a particular segment for each case study. This way, you can get 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 involves segmenting audiences based on interpretations 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. However, for rugby athletes, the ad is very relevant.

  

  (Image Source)

  Brands that want to avoid social platforms can use surveys about hobbies and interests to segment their target audience ethically.

  Technographic segmentation

  Technographic segmentation separates customers based on the 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 :

  After noticing a serious influx of tablet users accessing their platform, a leading news outlet optimised their tablet browsing experience. They overhauled the website interface, focusing on smoother navigation and better tablet-readability. These changes gave users a more enjoyable reading experience tailored precisely to their device.

  Transactional segmentation

  Transactional segmentation uses customers’ past purchases to match marketing messages with user needs.

  Consumers often relate personalisation with their actual transactions rather than their social media profiles. 

  Potential data points :

  • Average order value
  • Product categories purchased within X months
  • Most recent purchase date

  Example of effective transactional segmentation :

  Relevant product recommendations and coupons are among the best uses of transactional segmentation. These individualised marketing emails can strengthen brand loyalty and increase revenue.

  A pet supply store identifies a segment of customers who consistently purchase cat food but not other pet products. To encourage repeat purchases within this segment, the store creates targeted email campaigns offering discounts or loyalty rewards for cat-related items.

  Contextual segmentation 

  Contextual segmentation helps marketers connect with audiences based on real-time factors like time of day, weather or location. It’s like offering someone exactly what they need when they need it the most.

  Potential data points :

  • GPS location
  • Browsing activity
  • Device type

  Examples of contextual segmentation :

  A ride-hailing app might promote discounted rides during rush hour in busy cities or suggest carpooling options on rainy days. Similarly, an outdoor gear retailer could target users in snowy regions with ads for winter jackets or snow boots.

  The key is relevance. Messages that align with what someone needs at that moment feel helpful rather than intrusive. Businesses need tools like geolocation tracking and real-time analytics to make this work. 

  Also, keep it subtle and respectful. While personalisation is powerful, being overly intrusive can backfire. For example, instead of bombarding someone with notifications every time they pass a store, focus on moments when an offer truly adds value — like during bad weather or peak commute times.

  Lifecycle segmentation 

  Lifecycle segmentation is about crafting interactions based on where customers are in their journey with a brand.

  

  Lifecycle segmentation isn’t just about selling ; it’s about building relationships. After a big purchase like furniture, sending care tips instead of another sales pitch shows customers that the brand cares about their experience beyond just the sale.

  This approach helps brands avoid generic messaging that might alienate customers. By understanding the customer’s lifecycle stage, businesses can tailor their communications to meet specific needs, whether nurturing new relationships or rewarding long-term loyalty.

  Potential data points :

  • Purchase history
  • Sign-up dates

  Examples of effective lifecycle segmentation :

  An online clothing store might send first-time buyers a discount code to encourage repeat purchases. On the other hand, if someone hasn’t shopped in months, they might get an email with “We miss you” messaging and a special deal to bring them back.

  Predictive segmentation 

  Predictive segmentation uses past behaviour and preferences to understand or predict what customers might want next. Its real power lies in its ability to make customers feel understood without them having to ask for anything.

  Potential data points :

  • Purchase patterns
  • Browsing history
  • Interaction frequency

  Examples of effective predictive segmentation :

  Streaming platforms are great examples — they analyse what shows and genres users watch to recommend related content they might enjoy. Similarly, grocery delivery apps can analyse past orders to suggest when to reorder essentials like milk or bread.

  B2B-specific : Firmographic segmentation

  Beyond the eight 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 :

  • Annual revenue
  • Number of employees
  • Industry
  • Geographic location (main office)

  Example of effective firmographic segmentation :

  Startups and well-established companies will not need the same solution, so segmenting leads by size is one of the most common and effective examples of B2B audience segmentation.

  The difference here is that B2B campaigns involve more manual research. With an account-based marketing approach, you start by researching potential customers. Then, you separate the target audience into smaller segments (or even a one-to-one campaign).

  Audience segmentation challenges (+ how to overcome them) 

  Below, we explore audience segmentation challenges organisations can face and practical ways to overcome them.

  Data privacy 

  Regulations like GDPR and CCPA require businesses to handle customer data responsibly. Ignoring these rules can lead to hefty fines and harm a brand’s reputation. Customers are also more aware of and sensitive to how their data is used, making transparency essential.

  Businesses should adopt clear data policies and provide opt-out options to build trust and demonstrate respect for user preferences. 

  

  (Image Source) 

  Privacy-focused analytics tools can help businesses handle these requirements effectively. For example, Matomo allows businesses to anonymise user data and offers features that give users control over their tracking preferences.

  Data quality

  Inconsistent, outdated or duplicate data can result in irrelevant messaging that frustrates customers instead of engaging them.

  This is why businesses should regularly audit their data sources for accuracy and completeness.

  Integrate multiple data sources into a unified platform for a more in-depth customer view. Implement data cleansing processes to remove duplicates, outdated records, and errors. 

  Segment management 

  Managing too many segments can become overwhelming, especially for businesses with limited resources. Creating and maintaining numerous audience groups requires significant time and effort, which may not always be feasible.

  Automated tools and analytics platforms can help. Matomo Segments can analyse reports on specific audience groups based on criteria such as visit patterns, interactions, campaign sources, ecommerce behaviour, demographics and technology usage for more targeted analysis.

  Detailed reporting of each segment’s characteristics can further simplify the process. By prioritising high-impact segments — those that offer the best potential return on investment — businesses can focus their efforts where they matter most.

  Behaviour shifts 

  Customer behaviour constantly evolves due to changing trends, new technology and shifting social and economic conditions. 

  Segmentation strategies that worked in the past can quickly become outdated. 

  Businesses need to monitor market trends and adjust their strategies accordingly. Flexibility is key here — segmentation should never be static.

  For example, if a sudden spike in mobile traffic is detected, campaigns can be optimised for mobile-first users.

  Tools and technologies that help 

  Here are some key segmentation tools to support your efforts : 

  • Analytics platforms : Get insights into audience behaviour with Matomo. Track user interactions, such as website visits, clicks and time spent on pages, to identify patterns and segment users based on their online activity.
  • CRM systems : Utilize customer records to create meaningful segments based on characteristics like purchase history or engagement levels.
  • Marketing automation platforms : Streamline personalised messages by automating emails, social media posts or SMS campaigns for specific audience segments.
  • Consent management tools : Collect and manage user consent, implement transparent data tracking and provide users with opt-out options. 
  • Survey tools : Gather first-party data directly from customers. 
  • Social listening solutions : Monitor conversations and brand mentions across social media to gauge audience sentiment.

  Start segmenting and analysing audiences more deeply with Matomo

  Modern consumers expect to get relevant content, and segmentation can make this possible.

  But doing so in a privacy-sensitive way is not always easy. Organisations need to adopt an approach that doesn’t break regulations while still allowing them to segment their audiences. 

  That’s where Matomo comes in. Matomo champions privacy compliance while offering comprehensive insights and segmentation capabilities. It provides features for privacy control, enables cookieless configurations, and supports compliance with GDPR and other regulations — all without compromising user privacy. 

  Take advantage of Matomo’s 21-day free trial to explore its capabilities firsthand — no credit card required.

• Turn insights into action with the best marketing analytics tools

  20 août, par Joe

  Behind every great marketing team is a marketing analytics platform that collects performance data and identifies ways to improve. 

  But with hundreds of tools to choose from in a market valued at over $5.6 billion, how can you find the best platform that offers cross-channel tracking and advanced analysis while staying on the right side of privacy laws ?

  We’re here to help. 

  In this article, let’s review seven of the top marketing analytics tools, highlighting their standout features, pricing, and common community critiques. You’ll learn why choosing the right tool is crucial and what factors to consider when making a decision. 

  What are marketing analytics tools ?

  Marketing analytics tools capture and analyse data from various marketing channels, such as your website, social media profiles, and paid ad campaigns. 

  Marketers use these platforms to find ways to optimise campaigns and drive more conversions. Marketing attribution tools, for example, measure marketing effectiveness and help marketers understand which channels drive the most conversions. As a result, they can optimise budgets, allocating more money to the most effective channels. 

  

  Multi-Channel conversion attribution in Matomo
  (Image Source)

  Marketers can also reduce friction from the customer journey. Behavioural analytics tools like heatmaps and session recordings help marketing teams understand what’s stopping users from converting and run experiments to increase conversion rates. 

  Marketers can use an all-in-one analytics tool or a platform-specific alternative. Some analytics only track your social media efforts, for example. Others, like Matomo, let you track web visitors, paid ad performance, SEO data and attribute conversions from multiple campaigns. 

  The features and capabilities of marketing analytics tools can also vary by industry. For example, financial marketing analytics platforms will prioritise compliance and data security, while e-commerce teams focus on user behaviour analysis. Advanced tools now leverage machine learning to predict trends and automate insights, making them indispensable for data-driven decision-making.

  7 of the best marketing analytics tools

  With numerous marketing analytics platforms to choose from, it can be challenging to determine the best one for your business. 

  We’ve done the hard work, though. Below you’ll find reviews of seven of the leading tools, why they’re great and what customers say about them.

  1. Matomo

  Matomo Analytics is a leading ethical open-source marketing analytics platform that powers over a million websites in more than 190+ countries.

  

  Main dashboard in Matomo
  (Image Source)

  Why Matomo : Matomo empowers organisations to get the insights they need without compromising user privacy. Businesses can significantly reduce the amount of personal identifiable information they collect and comply with privacy laws like GDPR and CCPA. At the same time, they can use visitor logs to track the entire customer journey, assess the value of marketing channels using multi-touch attribution and analyse visitor behaviour using heatmaps and session recordings.

  Standout features include multi-touch attribution, visitor logs, goal tracking, custom reports, e-commerce tools, form analytics, tag manager, Google Analytics Importer, heatmaps and session recordings. 

  Integrations : Matomo integrates with more than 100 content management systems, e-commerce platforms and frameworks, including WordPress, Cloudflare, Magento, Google Ads, Drupal, WooCommerce and Wix.

  Strengths :

  • 100% accurate, unsampled data
  • Privacy-focused marketing analytics
  • Complete data ownership 
  • Open-source software 
  • Self-hosting and cloud-based options
  • A built-in GDPR Manager

  Common community critiques :

  • Non-technical users can experience a learning curve with some of the platform’s more advanced features
  • Premium features are proprietary

  Pricing : Matomo On-Premise is free to use. Matomo Cloud costs $23 per month and comes with a 21-day free trial (no credit card required).

  2. Heap by Contentsquare

  Heap by Contentsquare is a digital insights platform that gives businesses a near-real-time understanding of their users’ digital journeys.

  

  Demo dashboard in Heap
  (Image Source)

  Why Heap : Heap helps businesses paint a complete picture of their customers. It automatically records every user interaction (clicks, page views, form submissions and more) without manual event tagging to give marketers access to every metric and allow for retroactive analysis. 

  Standout features include data science tools that identify customer friction, journey analysis, session replays, heatmaps, pre-built dashboards and customer cohort analysis.

  Strengths :

  • Automatic event tracking eliminates the need for manual tagging, saving time and reducing implementation errors.
  • Setting up Heap is easy with a single code snippet. You don’t need advanced technical skills.
  • Real-time reporting and live data feeds help marketers quickly spot opportunities and issues. 

  Common community critiques :

  • The volume of data capture can create more noise than signal, which clouds analysis
  • Users can find the platform’s interface unintuitive
  • Businesses can accidentally collect personally identifiable information (PII) if they don’t configure the platform correctly

  Pricing : Heap has a limited free plan for up to 10,000 monthly sessions. Pricing for Growth, Pro and Premier plans is available upon request. 

  3. Mixpanel

  Mixpanel is a product and marketing analytics platform that helps SaaS and mobile marketers track user retention and engagement. 

  

  Product metrics dashboard in Mixpanel
  (Image Source)

  Why Mixpanel : Unlike traditional analytics tools that focus on pageviews and sessions, Mixpanel uses event-based analytics to track, analyse, and optimise user actions. It also has AI-powered predictive analytics that help marketers identify trends and proactively address churn. 

  Standout features include predictive analytics, funnel analysis, GA4 migration, A/B testing and real-time reports

  Strengths :

  • Intuitive dashboards and reports make Mixpanel accessible for non-technical users
  • Extensive integrations ensure seamless data flow across your tech stack
  • Advanced cohort analysis and customer segmentation support targeting and personalisation efforts

  Common community critiques :

  • The wide range of features means there’s a steep learning curve for new users
  • Pricing rises quickly for enterprise users
  • Event tracking can be difficult to set up

  Pricing : Mixpanel has a free forever plan with limited features. Premium plans give you one million monthly events free and then charge $.00028 per event after that.

  4. Funnel

  Funnel is a low-code marketing data platform that automates the collection and transformation of marketing data from hundreds of sources. 

  

  Performance marketing dashboard in Funnel
  (Image source)

  Why Funnel : Funnel is the ideal choice for marketers operating across dozens of different channels. It helps you gain a holistic view of marketing performance by pulling in data from over 500 sources, cleansing and visualising it.

  Standout features include a vast number of integration partners, automated data collection and transformation, two-year data storage and custom integrations.

  Strengths :

  • Low-code setup makes Funnel accessible to anyone
  • Highly responsive customer support
  • Custom metrics for personalised reporting

  Common community critiques :

  • The visualisation features are fairly basic. Marketers often need to use other tools like Tableau.
  • The platform has a steep learning curve
  • Delays can occur when processing data from third-party sources

  Pricing : Available upon request

  5. HubSpot

  HubSpot is a comprehensive analytics platform that helps marketers improve every stage of the buyer’s journey. Detailed insights and robust automation capabilities let marketers manage campaigns, track leads and optimise customer experiences. 

  

  Marketing dashboard in HubSpot
  (Image Source)

  Why HubSpot : HubSpot’s all-in-one platform is ideal for marketing and sales teams that want to paint a complete picture of their combined efforts. Analytics features let marketers track visitors and campaign performance, while automation tools nurture prospects and turn visitors into MQLs.

  Standout features include an easy-to-use dashboard, marketing automation, A/B testing and pre-made reports. 

  Strengths :

  • A very intuitive dashboard makes it easy for users of all abilities to navigate
  • Powerful automation features help marketers save time
  • There’s strong customer support and a large community of certified partners

  Common community critiques :

  • Pricing is expensive and increases quickly 
  • Engagement tracking is less granular than dedicated behavioural analytics tools
  • The wide range of features can lead to analysis paralysis

  Pricing : Marketing Hub Professional starts at $800 per month. Marketing Hub Enterprise starts from $3,600 per month.

  6. Whatagraph

  Whatagraph is a marketing analytics and automated reporting platform that helps agencies and in-house teams turn complex, multi-channel marketing data into visually easy-to-understand reports.

  

  Web analytics report in Whatagraph
  (Image Source)

  Why Whatagraph : Whatagraph is a great choice for companies that prioritise data visualisation. It lets users combine data from over 50 sources into customisable dashboards and reports. There are plenty of ready-made templates as well as a drag-and-drop interface in case you want to create your own.

  Standout features include direct integration with 50+ data sources, data blending across different channels, digital ad spend tracking and automated report creation.

  Strengths :

  • A very intuitive and user-friendly interface that lets anyone start building reports immediately
  • Visually appealing reports make it easy to share insights with stakeholders
  • Highly responsive support team

  Common community critiques :

  • No freemium pricing
  • It can take users time to get to grips with Whatagraph’s wide range of features
  • It lacks native integrations for some platforms

  Pricing : Available on request

  7. Google Analytics

  Google Analytics offers two analytics platforms : GA4 and GA360. GA4 is Google’s free analytics solution you’re probably familiar with. GA360 is the premium, enterprise-level version of GA4. It’s built for large organisations with complex analytics needs and high data volumes.

  

  Home page in GA4
  (Image Source)

  Why Google : GA4 is a well-known and widely used analytics platform. It’s free, familiar to most people and has plenty of online resources to help if you get stuck. However, it doesn’t protect user privacy, uses data sampling and lacks advanced features like behavioural analytics. 

  GA360 users can configure the platform to be more privacy-friendly, but there are still better (and cheaper) privacy-friendly alternatives.

  Standout features include event-based tracking, cross-platform tracking, audience segmentation and real-time reporting.

  Strengths :

  • GA4 is free to use
  • There’s no shortage of online guides
  • Cross-platform tracking helps you get a better view of your visitors 

  Common community critiques :

  • Not privacy focused or GDPR-compliant
  • Data sampling muddles insights
  • Both GA4 and GA360 look and are very different from Universal Analytics

  Pricing : GA4 is free to use. GA360 pricing is available on request

  What are the benefits of marketing analytics tools

  Research by Supermetrics reveals that marketing teams are using 230% more data than they did in 2020. 

  Analytics tools are the primary means of generating marketing data, but they have other uses as well. Here are four reasons every department needs a comprehensive analytics platform :

  • Track marketing efforts. Marketing analytics offers a unified view of all your campaigns across channels — from paid ads and social media to email and organic search. By consolidating data from multiple sources, these platforms help marketers monitor campaign performance in real time and prove campaign effectiveness to stakeholders. 
    
  • Improve customer understanding. Analytics platforms that have built-in behavioural tracking capabilities like heatmaps and session recordings help marketers generate qualitative and quantitative data that reveals how users interact with your site, what content resonates and where friction points occur.
    
  • Optimise web and marketing experiences. Marketing is a game of continuous improvement. Analytics platforms help marketing teams attribute conversions to specific campaigns, refine user journeys with A/B testing and improve the overall experience. 
    
  • Drive more conversions. Ultimately, the goal of marketing analytics is to increase conversions, whether that means sales, sign-ups or other events. Performance insights help marketers fine-tune their strategies, target high-value segments, and craft campaigns that move prospects down the funnel more efficiently. In a world where marketing budgets are falling by 15% year-on-year, it’s important to squeeze every drop of ROI from your campaigns. 

  Top features to look for in a marketing analytics tool

  With so many platforms to choose from, picking the right analytics tool can be a challenge. 

  Make it easier for yourself by looking for a tool that offers features to enhance your insights while ensuring your business remains compliant with data privacy regulations. 

  Advanced analytics features

  Don’t settle for a simple web analytics tool or try to juggle different analytics platforms for each channel. Instead, choose a single tool that provides a range of advanced analytics features, including the following :

  • Marketing attribution
  • Cohort analysis
  • Session recordings and heatmaps
  • Ecommerce analytics
  • SEO metrics

  By doing so, you’ll get everything you need from a single platform. This will keep costs down and make managing marketing data much easier.

  Data visualisation

  A great marketing analytics tool will offer customizable dashboards and reports that marketers can use to make sense of complex data. Look for :

  • Drag-and-drop interfaces
  • Pre-built templates
  • Detailed visitor profiles

  Data visualisation not only aids decision-making but also helps communicate results clearly to non-technical team members and executives.

  Near-real-time reporting

  Many platforms will claim to offer real-time reporting. But that’s rarely possible. Instead, choose tools with near-real-time reporting that help marketers measure the impact of campaigns as quickly as possible. 

  Matomo, for example, offers a Visits in Real-time Report that lets you see the flow of visitors on your site and shows how many people visited in the last 30 minutes and 24 hours. 

  

  Visits Overview in Matomo

  The report refreshes every 5 seconds to display new visits and tracks a range of visitor attributes, including country, operating system, referrer, time spent on site and whether they are a new or returning visitor. 

  Data security and privacy

  Data privacy should be a top priority for modern marketers. Employing ethical analytics and data practices will mean you don’t have to annoy users with cookie banners. But it also improves trust and minimises legal risk.

  Choose analytics tools that are transparent about data collection, offer robust privacy controls, and comply with regulations like GDPR and CCPA. Features such as anonymised tracking, customisable consent banners and secure data storage help protect both your business and your customers.

  Matomo has all of these features and more, protecting your visitors’ privacy in a dozen different ways. 

  100% data ownership and no sampling

  A lot of analytics platforms don’t let you own or properly use your data. Data sampling — where tools only analyse a portion of your data — is a particular problem in Google Analytics. It clouds insights, meaning marketers make decisions based on guesses, not facts. 

  Who owns your data matters, too. When you use a platform like Google Analytics, you give permission for Google to use your customers’ data for advertising purposes. 

  Instead of trading your customers’ data for free analytics, use a platform that gives you 100% ownership of your data. Matomo does this in a couple of ways :

  • Matomo On-Premise offers 100% data ownership, as it’s hosted on your own servers. You choose where to store it, and we cannot access it. 
    
  • Matomo Analytics for WordPress provides a self-hosted WordPress-specific option that offers the benefits of On-Premise without the technical setup.
    
  • Matomo Cloud subscriptions are governed by our Terms, which state that you own all rights, titles and interests in your users’ data. In other words, we can’t sell it to third parties or claim ownership. 

  While Matomo products may change, our commitment to privacy never will. You’ll always be able to self-host Matomo for free. 

  	Matomo	Heap	Mixpanel	Funnel	HubSpot	Whatagraph	Google Analytics
  Privacy/GDPR-friendly	✔️
  Open-source	✔️
  Self-hosting option	✔️
  Multi-touch attribution	✔️
  Heatmaps & session recordings	✔️	✔️	⚠️¹
  Goal tracking	✔️	✔️	✔️	✔️
  Custom reports	✔️	✔️	✔️	✔️	✔️	✔️	✔️
  E-commerce tracking	✔️	✔️	✔️	✔️
  Tag manager	✔️		✔️	✔️
  GA importer	✔️
  Real-time reporting	✔️	✔️	✔️	✔️	⚠️²	✔️
  Predictive analytics		✔️
  A/B testing	✔️		✔️
  Marketing automation					✔️
  Visualisation / dashboards	✔️	✔️	✔️	⚠️³	✔️	✔️	✔️
  Automated reporting						✔️
  Free plan available	✔️	✔️	✔️		✔️

  Trust Matomo for comprehensive marketing analytics

  The right analytics platform empowers marketers to track campaigns across channels, gain deep insights into customer behaviour, optimise user experiences and ultimately drive more conversions. 

  If you care about collecting data while respecting your users’ privacy, a tool like Matomo is the way to go. Try Matomo free for 21 days. No credit card required.