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• CRO Audit : Increase Your Conversions in 10 Simple Steps

  25 mars 2024, par Erin

  You have two options if you’re unhappy with your website’s conversion rates.

  The first is to implement a couple of random tactics you heard on that marketing podcast, which worked for a business completely unrelated to yours. 

  The other is to take a more systematic, measured approach. An approach that finds specific problems with the pages on your site and fixes them one by one. 

  You’re choosing the second option, right ?

  Good, then let’s explain what a conversion rate optimisation audit is and how you can complete one using our step-by-step process.

  What is a CRO audit ?

  A conversion rate optimisation audit (CRO audit) systematically evaluates your website. It identifies opportunities to enhance your website’s performance and improve conversion rates. 

  During the audit, you’ll analyse your website’s entire customer journey, collect valuable user behaviour data and cross reference that with web analytics to find site elements (forms, calls-to-actions, etc.) that you can optimise.

  

  It’s one (and usually the first) part of a wider CRO strategy. 

  For example, an online retailer might run a CRO audit to discover why cart abandonment rates are high. The audit may throw up several potential problems (like a confusing checkout form and poor navigation), which the retailer can then spend time optimising using A/B tests. 

  Why run a CRO audit ?

  A CRO audit can be a lot of work, but it’s well worth the effort. Here are the benefits you can expect from running one.

  Generate targeted and relevant insights

  You’ve probably already tested some “best practice” conversion rate optimisations, like changing the colour of your CTA button, adding social proof or highlighting benefits to your headlines. 

  These are great, but they aren’t tailored to your audience. Running a CRO audit will ensure you find (and rectify) the conversion bottlenecks and barriers that impact your users, not someone else’s.

  Improve conversion rates

  Ultimately, CRO audits are about improving conversion rates and increasing revenue. Finding and eliminating barriers to conversion makes it much more likely that users will convert. 

  But that’s not all. CRO audits also improve the user experience and customer satisfaction. The audit process will help you understand how users behave on your website, allowing you to create a more user-friendly customer experience. 

  A 10-step process for running your first CRO audit 

  Want to conduct your first CRO audit ? Follow the ten-step process we outline below :

  

  1. Define your goals

  Start your CRO audit by setting conversion goals that marry with the wider goals of your business. The more clearly you define your goals, the easier it will be to evaluate your website for opportunities. 

  Your goals could include :

  • Booking more trials
  • Getting more email subscribers
  • Reducing cart abandonments

  You should also define the specific actions users need to take for you to achieve these goals. For example, users will have to click on your call-to-action and complete a form to book more trials. On the other hand, reducing cart abandonments requires users to add items to their cart and click through all of the forms during the checkout process. 

  If you’re unsure where to start, we recommend reading our CRO statistics roundup to see how your site compares to industry averages for metrics like conversion and click-through rates. 

  You’ll also want to ensure you track these conversion goals in your web analytics software. In Matomo, it only takes a few minutes to set up a new conversion goal, and the goals dashboard makes it easy to see your performance at a glance. 

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  2. Review your analytics

  With your goals in mind, the next step is to dive into your website analytics and identify pages that need improvement.

  Consider the following conversion metrics when analysing pages :

  • Conversion rate
  • Average time on page
  • Average order value
  • Click-through rate

  Ensure you’re analysing metrics aligning with the goals you set in step one. Average order value could be a great metric to track if you want to reduce cart abandonments, for example, but it’s unsuitable to get more email subscribers.

  3. Research the user experience

  Next, you’ll want to gather user experience data to better understand how potential customers use your website and why they aren’t converting as often as you’d like. 

  You can use several tools for user behaviour analysis, but we recommend heatmaps and session recordings.

  Heatmaps visually represent how users click, move and scroll your website. It will show where visitors place their attention and which page elements are ignored. 

  Take a look at this example below from our website. As you can see, the navigation, headline and CTA get the most attention. If we weren’t seeing as many conversions as we liked and our CTAs were getting ignored, that might be a sign to change their colour or placement. 

  

  Session recordings capture the actions users take as they browse your website. They let you watch a video playback of how visitors behave, capturing clicks and scrolls so you can see each visitor’s steps in order. 

  Session recordings will show you how users navigate and where they drop off. 

  4. Analyse your forms

  Whether your forms are too confusing or too long, there are plenty of reasons for users to abandon your forms. 

  But how many forms are they abandoning exactly and which forms are there ?

  That’s what form analysis is for. 

  Running a form analysis will highlight which forms need work and reveal whether forms could be contributing to a page’s poor conversion rate. It’s how Concrete CMS tripled its leads in just a few days.

  Matomo’s Form Analytics feature makes running form analysis easy.

  

  Just open up the forms dashboard to get a snapshot of your forms’ key metrics, including average hesitation time, starter rate and submission rates. 

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  5. Analyse your conversion funnel

  Next, analyse the conversion funnel to see if there’s an obvious bottleneck or several pages where visitors abandon your desired action. Common conversion abandonment points are shopping carts and forms.

  

  For example, you could find there is a drop-off in conversions between checking out and making a purchase or between booking a demo and signing up for a subscription. Understanding where these drop-offs occur lets you dig deeper and make targeted improvements.

  Don’t worry if you’ve got a very long funnel. Start at the bottom and work backward. Problems with the pages at the very end of your funnel tasked with converting customers (landing pages, checkout pages, etc.) will have the biggest impact on your conversion rate. So, it makes sense to start there. 

  6. Analyse campaigns and traffic sources (marketing attribution)

  It’s now time to analyse traffic quality to ensure you’re powering your conversion optimisation efforts with the best traffic possible. 

  This can also help you find your best customers so you can focus on acquiring more of them and tailoring your optimisation efforts to their preferences. 

  Run a marketing attribution report to see which traffic sources generate the most conversions and have the highest conversion rates. 

  

  Using marketing attribution is crucial here because it gives a fuller picture of how customers move through their journey, recognising the impact of various touchpoints in making a decision, unlike last-click attribution, which only credits the final touchpoint before a conversion.

  7. Use surveys and other qualitative data sources

  Increase the amount of qualitative data you have access to by speaking directly to customers. Surveys, interviews and other user feedback methods add depth and context to your user behaviour research.

  Sure, you aren’t getting feedback from hundreds of customers like you do with heatmaps or session recordings, but the information can sometimes be much richer. Users will often tell you outright why they didn’t take a specific action in a survey response (or what convinced them to convert). 

  Running surveys is now even easier in Matomo, thanks to the Matomo Surveys third-party plugin. This lets you add a customisable survey popup to your site, the data from which is automatically added to Matomo and can be combined with Matomo segments.

  8. Develop a conversion hypothesis

  Using all of the insights you’ve gathered up to this point, you can now hypothesise what’s wrong and how you can fix it. 

  Here’s a template you can use :

  

  This could end up looking something like the following :

  Based on evidence gathered from web analytics and heatmaps, moving our signup form above the fold will fix our lack of free trial signups, improving signups by 50%.

  

  Make sure you write your hypothesis down somewhere. Matomo lets you document your hypothesis when creating an A/B test, so it’s easy to reflect on when the test finishes. 

  9. Run A/B tests

  Now, it’s time to put your theory into practice by running an A/B test.

  Create an experiment using a platform like Matomo that creates two different versions of your page : the original and one with the change you mentioned in your hypothesis. 

  There’s no set time for you to run an A/B test. Just keep running it until the outcome is statistically significant. This is something your A/B testing platform should do automatically. 

  A statistically significant result means it would be very unlikely the outcome doesn’t happen in the long term.

  

  As you can see in the image above, the wide header variation has significantly outperformed both the original and the other variation. So we can be pretty confident about making the change permanent. 

  If the outcome of your A/B test also validates your conversion hypothesis, you can implement the change. If not, analyse the data, brainstorm another hypothesis and run another A/B test. 

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  10. Monitor and iterate

  You need to develop a culture of continuous improvement to succeed with conversion rate optimisation. That means constantly monitoring your conversion goals and running tests to improve your metrics. 

  While you don’t need to run a conversion audit every month, you should run audits regularly throughout the year.

  How often should you conduct a CRO audit ? 

  You should conduct a CRO audit fairly regularly. 

  We recommend creating a CRO schedule that sees you run a CRO audit every six to 12 months. That will ensure you continue identifying problem pages and keeping your conversion rates competitive. 

  Regular CRO audits will also account for evolving consumer behaviours, changes in your industry and your own business goals, all of which can impact your approach conversion rate optimisation. 

  Run your CRO audit with Matomo

  A CRO audit process is the only way you can identify conversion optimisation methods that will work for your site and your target audience. It’s a methodical, data-backed strategy for making targeted improvements to send conversion rates soaring. 

  There are a lot of steps to complete, but you don’t need dozens of tools to run a CRO audit process. 

  Just one : Matomo.

  Unlike other web analytics platforms, like Google Analytics, Matomo has the built-in tools and plugins to help with every step of the CRO audit process, from web analytics to conversion funnel analysis and A/B testing. With its accurate, unsampled data and privacy-friendly tracking, Matomo is the ideal choice for optimising conversions. 

  Learn how to increase your conversions with Matomo, and start a free 21-day trial today. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• 7 Best Marketing Attribution Software in 2024

  22 février 2024, par Erin

  It can be hard to accurately track the impact of your marketing efforts across marketing channels and campaigns. That’s where marketing attribution software comes in. 

  It goes beyond basic web analytics solutions that just look at the final click. Instead, it shows how different channels, content, and ads are performing at every step of the buyer’s journey, which gives a more accurate picture than just focusing on the last click.

  In this guide, we’ll cover the basics of marketing attribution, list the top marketing attribution software and explain how the issue of privacy is transforming the web analytics industry.

  What is marketing attribution ?

  Marketing attribution is the process of assigning credit to each touchpoint in a buyer’s journey that leads to a desired action (such as a conversion or sale) in order to understand the effectiveness of various marketing channels and campaigns in influencing the customer’s decision-making process.

  Marketers use software tools like website analytics to to track and analyse customer interactions across different touchpoints, allowing them to attribute conversions or sales to specific marketing efforts and optimise their strategies and budgets accordingly.

  Why is marketing attribution so important ?

  If you don’t track your campaigns correctly, it’s easy to spend thousands (or even millions) in an ineffective way. A 2022 survey by Australian marketing agency Next&Co revealed their clients wasted AU$5.46 billion in ineffective ad spend.

  

  That’s 41% of all the ad spend tracked by Next&Co in 2022. A wasted marketing spend percentage this high isn’t exactly a recipe for a high marketing return on investment (ROI). And yet, it’s the average.

  Why is that ? 

  Most companies don’t actively track the results of their marketing campaigns actively enough.

  By improving your marketing attribution, you can determine which channels, ads, and campaigns work and which don’t. Then, you can move the budget from ineffective channels to effective ones.

  Even if you can only identify half of your wastage, this could be 20% or more of your total spend. Just imagine what your bottom line would look like if your marketing budget were 20% more effective.

  That’s the power that marketing attribution, when done right, brings to the table. It’s the road to a higher marketing ROI.

  Common marketing attribution models and how they’re different 

  The default model for attributing completed goals in most analytics tools is either the last interaction or the last non-direct interaction.

  However, some multi-touch models can help you get a more holistic view of the impact of your marketing efforts.

  

  • Last interaction model : attributes the conversion to the final interaction or referring source (campaign or ad).
  • Last non-direct interaction model : attributes the conversion to the final touchpoint that was not a direct visit to your website. (For example, if a search ad took them to a product page, the user bookmarked it and returned directly the next day to finish the purchase. The credit would go to the search ad as it’s the last non-direct touchpoint.)
  • First interaction model : attributes the conversion to the first referring event alone.
  • Linear model : gives equal value to every touchpoint throughout the customer journey. 
  • Time decay model : gives more value to touchpoints the closer they were to the actual sale.
  • Position-based model : gives more value to the first and last touchpoints — often 40% each, while splitting 20% among the rest.

  You can read our guide dedicated to marketing attribution models for more details on these models.

  Types of marketing attribution software and the impact of privacy regulations

  Until recently, digital advertising was the “scientific” advertisers’ utopia. Everything could be measured, with cookies from giants like Google and Facebook stalking every user across the web.

  But with the advent of regulations like GDPR and the CCPA, you can no longer blindly trust Google Analytics or the Meta Pixel without consequences.

  Multi-channel attribution tools with third-party cookies and GDPR

  Google, Meta, and other companies used to track and combine user data from their own platforms and websites across the web that installed their tags. These third-party cookies have long been under fire and have caused several GDPR fines.

  

  The alternative : analytics platforms with first-party cookies

  In a post-GDPR digital marketing landscape, a compliant-by-default web analytics platform like Matomo is a more reliable and accurate alternative.

  Plus, with a platform like Matomo, you don’t need to rely on data from digital advertising platforms like Facebook Ads and Google Ads. You can accurately track referral sources using our campaign tracking parameters.

  7 best marketing attribution software in 2024

  Below is the list of our favourite marketing attribution tools in 2024. If you find and use one that suits your needs correctly, you can quickly boost your marketing performance.

  1. Matomo — Accurate and easiest to set up for marketing attribution

  Matomo is a privacy-friendly web analytics suite that empowers you to accurately attribute marketing efforts and gain valuable insights while prioritising user privacy and compliance.

  Matomo integrates with e-commerce platforms like WooCommerce and Magenta. That makes it easy for B2C marketing teams to track the revenue impact of their campaigns.

  

  You can also compare a variety of attribution models against each other. B2B teams can use our API to integrate Matomo with their CRM.

  Pros :

  • Relies on first-party cookies for tracking, ensuring accurate data collection and attribution of user actions
  • Includes additional features like Heatmaps, Session Recordings, Form Analytics, A/B Testing, and more
  • Easy to set up and use
  • Features most common multi-touch attribution models

  Cons :

  • Limited to owned channels (website and e-commerce store) due to first-party cookies and data (but you can integrate other data sources through a CRM)

  Pricing

  The self-hosted version is free. The cloud hosted version starts at $19 per month and includes a 21-day free trial. No credit card requierd. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  2. WhatConverts — Great option for leads-based businesses with high ad spend

  WhatConverts is a marketing attribution tool with a focus on lead tracking. With most web analytics setups, it adds call and text tracking to the typical form-only tracking.

  

  Pros :

  • Reliable call and text tracking
  • Revenue attribution to specific leads (and, by extension, campaigns and ads)

  Cons :

  • Focused exclusively on leads — little utility for e-commerce companies 

  Pricing

  The cheapest plan starts at $30/month but does not include analytics integrations or form tracking. To access this and advanced flow tracking and attribution features, you need the Elite plan, which starts at $160/month.

  3. HubSpot Marketing Hub — Ideal CRM for larger B2B companies

  HubSpot is a marketing CRM with attribution features for tracking and analysis.

  

  The platform is very broad — encompassing CRM, email automation and other tools — which makes it challenging to use effectively. The price tag is also quite steep for smaller companies and marketing teams.

  Pros :

  • Concretely tracks revenue to multiple different touchpoints and marketing channels
  • Includes several different multi-touch attribution models
  • Allows offline conversion tracking

  Cons :

  • The price point is too high for smaller teams
  • Cam be difficult to set up effectively

  Pricing

  Since marketing attribution is only included in HubSpot Marketing Hub’s Professional and Enterprise plans, pricing starts at $800/month (paid annually). If you commit for a year but pay monthly, the price is $890/month for the professional plan. This goes up with additional add-ons and as your contacts increase as well. 

  4. ActiveCampaign — Good CRM option for small B2B companies

  ActiveCampaign is a CRM and marketing automation platform that can help you trace leads and revenue back to their source.

  

  Although it has a similar scope of features to HubSpot, it is more affordable and slightly easier to use for beginners.

  Pros :

  • Tracks sales revenue back to specific marketing touchpoints
  • Powerful marketing automation features

  Cons :

  • B2B companies may need to purchase two plans, one ActiveCampaign marketing and one CRM.

  Pricing

  Unlike HubSpot, ActiveCampaign offers a much more affordable plan, starting at $29/month billed annually (for up to 1,000 contacts). The marketing and sales CRM bundle starts at $93/month with up to five users.

  5. Salesforce Data Cloud for Marketing — Ideal CRM for enterprises

  Salesforce is a robust and feature-rich CRM that many enterprises rely on for their sales teams.

  

  That makes Salesforce’s marketing attribution platform a logical choice for existing Salesforce users.

  Pros :

  • Uses prospect and sales data from CRM to attribute revenue
  • Revenue prediction analytics
  • Lead scoring to help your sales team focus on high-value leads

  Cons :

  • Difficult to set up and use
  • Clunky and aged user interface
  • Relatively high price point

  Pricing

  The limited Marketing Cloud Account Engagement Growth plan starts at $1,250/month, billed annually. To access advanced cross-channel journeys, you need the Pro plan, which starts at $2,750 monthly.

  6. Terminus — Great for account-based marketing

  If your marketing team uses an account-based marketing (ABM) approach, Terminus might be the right option for you.

  

  It offers ABM tools like target account event tracking and revenue attribution tools for your marketing campaigns.

  Pros :

  • Advanced multi-channel revenue attribution tools with a wide range of reports
  • Track intent touchpoints back to target accounts
  • Reliable revenue predictions help you focus your marketing activities

  Cons :

  • Complex and difficult to set up, understand and use effectively
  • Lacks native integrations with many common advertising platforms and analytics tools

  Pricing

  Terminus offers no standard pricing plans. You must contact their sales team for a custom quote based on your needs.

  7. Adobe Analytics — An analytics for enterprises

  Adobe Analytics is part of the Adobe Experience Cloud, with plenty of big data analysis tools for enterprises. Although the platform is quite powerful, it is equally complex and difficult to use. The price point is also prohibitive for many smaller companies.

  

  Pros :

  • Very extensive reporting tools
  • Predictive analytics give you solid leading indicator for future campaign performance
  • Track multiple digital touchpoints across the entire customer journey

  Cons :

  • Like Google Analytics, Adobe Analytics aggregates your visitor data by default, making compliant “consent-free tracking” — tracking user actions without asking for consent — impossible according to GDPR. (See more differences in Matomo’s comparison against Adobe Analytics and Google Analytics.)
  • Prohibitively expensive for most smaller companies
  • Very steep learning curve for setting up and using it correctly

  Pricing

  Adobe Analytics uses usage-based pricing — which means they adjust the pricing based on the traffic volume to your website. Still, their lower price points aren’t exactly SMB-friendly — multiple sources put Adobe’s lowest starting price point at $2,000–2,500 per month.

  Get accurate marketing attribution with Matomo (without privacy concerns)

  Matomo allows you to do marketing attribution effectively and accurately without compromising your users’ privacy. By default, we only use first-party cookies and offer consent-free tracking – meaning no more annoying cookie consent banners (excluding in Germany and the UK).

  If you want to boost your marketing performance without disregarding your users’ privacy, get started with our 21-day free trial. No credit card required. It’s time to make more informed decisions about your marketing campaigns.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• 10 Key Google Analytics Limitations You Should Be Aware Of

  9 mai 2022, par Erin

  Google Analytics (GA) is the biggest player in the web analytics space. But is it as “universal” as its brand name suggests ?
  

  Over the years users have pointed out a number of major Google Analytics limitations. Many of these are even more visible in Google Analytics 4. 

  Introduced in 2020, Google Analytics 4 (GA4) has been sceptically received. As the sunset date of 1st, July 2023 for the current version, Google Universal Analytics (UA), approaches, the dismay grows stronger.

  To the point where people are pleading with others to intervene : 

  

  Main limitations of Google Analytics

  Google Analytics 4 is advertised as a more privacy-centred, comprehensive and “intelligent” web analytics platform. 

  According to Google, the newest version touts : 

  • Machine learning at its core provides better segmentation and fast-track access to granular insights 
  • Privacy-by-design controls, addressing restrictions on cookies and new regulatory demands 
  • More complete understanding of customer journeys across channels and devices 

  Some of these claims hold true. Others crumble upon a deeper investigation. Newly advertised Google Analytics capabilities such as ‘custom events’, ‘predictive insights’ and ‘privacy consent mode’ only have marginal improvements. 

  Complex setup, poor UI and lack of support with migration also leave many other users frustrated with GA4. 

  

  Let’s unpack all the current (and legacy) limitations of Google Analytics you should account for. 

  1. No Historical Data Imports 

  Google rushed users to migrate from Universal Analytics to Google Analytics 4. But they overlooked one important precondition — backwards compatibility. 

  You have no way to import data from Google Universal Analytics to Google Analytics 4. 

  Historical records are essential for analysing growth trends and creating benchmarks for new marketing campaigns. Effectively, you are cut short from past insights — and forced to start strategising from scratch. 

  At present, Google offers two feeble solutions : 

  • Run data collection in parallel and have separate reporting for GA4 and UA until the latter is shut down. Then your UA records are gone. 
  • For Ecommerce data, manually duplicate events from UA at a new GA4 property while trying to figure out the new event names and parameters. 

  Google’s new data collection model is the reason for migration difficulties. 

  In Google Analytics 4, all analytics hits types — page hits, social hits, app/screen view, etc. — are recorded as events. Respectively, the “‘event’ parameter in GA4 is different from one in Google Universal Analytics as the company explains : 

  

  This change makes migration tedious — and Google offers little assistance with proper events and custom dimensions set up. 

  2. Data Collection Limits 

  If you’ve wrapped your head around new GA4 events, congrats ! You did a great job, but the hassle isn’t over. 

  You still need to pay attention to new Google Analytics limits on data collection for event parameters and user properties. 

  

  These apply to :

  • Automatically collected events
  • Enhanced measurement events
  • Recommended events 
  • Custom events 

  When it comes to custom events, GA4 also has a limit of 25 custom parameters per event. Even though it seems a lot, it may not be enough for bigger websites. 

  You can get higher limits by upgrading to Google Analytics 360, but the costs are steep. 

  3. Limited GDPR Compliance 

  Google Analytics has a complex history with European GDPR compliance. 

  A 2020 ruling by the Court of Justice of the European Union (CJEU) invalidated the Privacy Shield framework Google leaned upon. This framework allowed the company to regulate EU-US data transfers of sensitive user data. 

  But after this loophole was closed, Google faced a heavy series of privacy-related fines :

  • French data protection authority, CNIL, ruled that  “the transfers to the US of personal data collected through Google Analytics are illegal” — and proceeded to fine Google for a record-setting €150 million at the beginning of 2022. 
  • Austrian regulators also deemed Google in breach of GDPR requirements and also branded the analytics as illegal. 

  Other EU-member states might soon proceed with similar rulings. These, in turn, can directly affect Google Analytics users, whose businesses could face brand damage and regulatory fines for non-compliance. In fact, companies cannot select where the collected analytics data will be stored — on European servers or abroad — nor can they obtain this information from Google.

  Getting a web analytics platform that allows you to keep data on your own servers or select specific Cloud locations is a great alternative. 

  Google also has been lax with its cookie consent policy and doesn’t properly inform consumers about data collection, storage or subsequent usage. Google Analytics 4 addresses this issue to an extent. 

  By default, GA4 relies on first-party cookies, instead of third-party ones — which is a step forward. But the user privacy controls are hard to configure without losing most of the GA4 functionality. Implementing user consent mode to different types of data collection also requires a heavy setup. 

  4. Strong Reliance on Sampled Data 

  To compensate for ditching third-party cookies, GA4 more heavily leans on sampled data and machine learning to fill the gaps in reporting. 

  In GA4 sampling automatically applies when you :

  • Perform advanced analysis such as cohort analysis, exploration, segment overlap or funnel analysis with not enough data 
  • Have over 10,000,000 data rows and generate any type of non-default report 

  Google also notes that data sampling can occur at lower thresholds when you are trying to get granular insights. If there’s not enough data or because Google thinks it’s too complex to retrieve. 

  In their words :

  

  Data sampling adds “guesswork” to your reports, meaning you can’t be 100% sure of data accuracy. The divergence from actual data depends on the size and quality of sampled data. Again, this isn’t something you can control. 

  Unlike Google Analytics 4, Matomo applies no data sampling. Your reports are always accurate and fully representative of actual user behaviours. 

  5. No Proper Data Anonymization 

  Data anonymization allows you to collect basic analytics about users — visits, clicks, page views — but without personally identifiable information (or PII) such as geo-location, assigns tracking ID or other cookie-based data. 

  This reduced your ability to :

  • Remarket 
  • Identify repeating visitors
  • Do advanced conversion attribution 

  But you still get basic data from users who ignored or declined consent to data collection. 

  By default, Google Analytics 4 anonymizes all user IP addresses — an upgrade from UA. However, it still assigned a unique user ID to each user. These count as personal data under GDPR. 

  For comparison, Matomo provides more advanced privacy controls. You can anonymize :

  • Previously tracked raw data 
  • Visitor IP addresses
  • Geo-location information
  • User IDs 

  This can ensure compliance, especially if you operate in a sensitive industry — and delight privacy-mindful users ! 

  6. No Roll-Up Reporting

  Getting a bird’s-eye view of all your data is helpful when you need hotkey access to main sites — global traffic volume, user count or percentage of returning visitors.

  With Roll-Up Reporting, you can see global-performance metrics for multiple localised properties (.co.nz, .co.uk, .com, etc,) in one screen. Then zoom in on specific localised sites when you need to. 

  

  7. Report Processing Latency 

  The average data processing latency is 24-48 hours with Google Analytics. 

  Accounts with over 200,000 daily sessions get data refreshes only once a day. So you won’t be seeing the latest data on core metrics. This can be a bummer during one-day promo events like Black Friday or Cyber Monday when real-time information can prove to be game-changing ! 

  Matomo processes data with lower latency even for high-traffic websites. Currently, we have 6-24 hour latency for cloud deployments. On-premises web analytics can be refreshed even faster — within an hour or instantly, depending on the traffic volumes. 

  8. No Native Conversion Optimisation Features

  Google Analytics users have to use third-party tools to get deeper insights like how people are interacting with your webpage or call-to-action.

  You can use the free Google Optimize tool, but it comes with limits : 

  • No segmentation is available 
  • Only 10 simultaneous running experiments allowed 

  There isn’t a native integration between Google Optimize and Google Analytics 4. Instead, you have to manually link an Optimize Container to an analytics account. Also, you can’t select experiment dimensions in Google Analytics reports.

  What’s more, Google Optimize is a basic CRO tool, best suited for split testing (A/B testing) of copy, visuals, URLs and page layouts. If you want to get more advanced data, you need to pay for extra tools. 

  Matomo comes with a native set of built-in conversion optimization features : 

  • Heatmaps 
  • User session recording 
  • Sales funnel analysis 
  • A/B testing 
  • Form submission analytics 

  

  9. Deprecated Annotations

  Annotations come in handy when you need to provide extra context to other team members. For example, point out unusual traffic spikes or highlight a leak in the sales funnel. 

  This feature was available in Universal Analytics but is now gone in Google Analytics 4. But you can still quickly capture, comment and share knowledge with your team in Matomo. 

  You can add annotations to any graph that shows statistics over time including visitor reports, funnel analysis charts or running A/B tests. 

  10. No White Label Option 

  This might be a minor limitation of Google Analytics, but a tangible one for agency owners. 

  Offering an on-brand, embedded web analytics platform can elevate your customer experience. But white label analytics were never a thing with Google Analytics, unlike Matomo. 

  Wrap Up 

  Google set a high bar for web analytics. But Google Analytics inherent limitations around privacy, reporting and deployment options prompt more users to consider Google Analytics alternatives, like Matomo. 

  With Matomo, you can easily migrate your historical data records and store customer data locally or in a designated cloud location. We operate by a 100% unsampled data principle and provide an array of privacy controls for advanced compliance. 

  Start your 21-day free trial (no credit card required) to see how Matomo compares to Google Analytics ! 

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