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• GA360 Sunset : Is Now the Time to Switch ?

  20 mai 2024, par Erin

  Google pushed the sunset date of Universal Analytics 360 to July 2024, giving enterprise users more time to transition to Google Analytics 4. This extension is also seen by some as time to find a suitable alternative. 

  While Google positions GA4 as an upgrade to Universal Analytics, the new platform has faced its fair share of backlash. 

  So before you rush to meet the new sunset deadline, ask yourself this question : Is now the time to switch to a Google Analytics alternative ?

  In this article, we’ll explain what the new GA360 sunset date means and show you what you could gain by choosing a privacy-friendly alternative. 

  What’s happening with the final GA360 sunset ?

  Google has given Universal Analytics 360 properties with a current 360 licence a one-time extension, which will end on 1 July 2024.

  Why did Google extend the sunset ?

  In a blog post on Google, Russell Ketchum, Director of Product Management at Google Analytics, provided more details about the final GA360 sunset. 

  In short, the tech giant realised it would take large enterprise accounts (which typically have complex analytics setups) much longer to transition smoothly. The extension gives them time to migrate to GA4 and check everything is tracking correctly. 

  What’s more, Google is also focused on improving the GA4 experience before more GA360 users migrate :

  “We’re focusing our efforts and investments on Google Analytics 4 to deliver a solution built to adapt to a changing ecosystem. Because of this, throughout 2023 we’ll be shifting support away from Universal Analytics 360 and will move our full focus to Google Analytics 4 in 2024. As a result, performance will likely degrade in Universal Analytics 360 until the new sunset date.”

  Despite the extension, the July sunset is definitive. 

  Starting the week of 1 July 2024, you won’t be able to access any Universal Analytics properties or the API (not even with read-only access), and all data will be deleted.

  In other words, it’s not just data collection that will cease at the start of July. You won’t be able to access the platform, and all your data will be deleted. 

  What GA360 features is Google deprecating, and when ?

  If you’re wondering which GA360 features are being deprecated and when, here is the timeline for Google’s final GA360 sunset :

  • 1 January 2024 : From the beginning of the year, Google doesn’t guarantee all features and functionalities in UA 360 will continue to work as expected. 
  • 29 January 2024 : Google began deprecating a string of advertising and measurement features as it shifts resources to focus on GA4. These features include :
    • Realtime reports
    • Lifetime Value report
    • Model Explorer
    • Cohort Analysis
    • Conversion Probability report
    • GDN Impression Beta
  • Early March 2024 : Google began deprecating more advertising and measurement features. Deprecated advertising features include Demographic and Interest reports, Publisher reporting, Phone Analytics, Event and Salesforce Data Import, and Realtime BigQuery Export. Deprecated measurement features include Universal Analytics property creation, App Views, Unsampled reports, Custom Tables and annotations.
  • Late March 2024 : This is the last recommended date for migration to GA4 to give users three months to validate data and settings. By this date, Google recommends that you migrate your UA’s Google Ads links to GA4, create new Google Ad conversions based on GA4 events, and add GA4 audiences to campaigns and ad groups for retargeting. 
  • 1 July 2024 : From 1 July 2024, you won’t be able to access any UA properties, and all data will be deleted.

  What’s different about GA4 360 ? 

  GA4 comes with a new set of metrics, setups and reports that change how you analyse your data. We highlight the key differences between Universal Analytics and GA4 below. 

  

  New dashboard

  The layout of GA4 is completely different from Universal Analytics, so much so that the UX can be very complex for first-time and experienced GA users alike. Reports or metrics that used to be available in a couple of clicks in UA now take five or more to find. While you can do more in theory with GA4, it takes much more work. 

  New measurements

  The biggest difference between GA4 and UA is how Google measures data. GA4 tracks events — and everything counts as an event. That includes pageviews, scrolls, clicks, file downloads and contact form submissions. 

  The idea is to anonymise data while letting you track complex buyer journeys across multiple devices. However, it can be very confusing, even for experienced marketers and analysts. 

  New metrics

  You won’t be able to track the same metrics in GA4 as in Universal Analytics. Rather than bounce rate, for example, you are forced to track engagement rate, which is the percentage of engaged sessions. These sessions last at least ten seconds, at least two pageviews or at least one conversion event. 

  Confused ? You’re not alone. 

  New reports

  Most reports you’ll be familiar with in Universal Analytics have been replaced in GA4. The new platform also has a completely different reporting interface, with every report grouped under the following five headings : realtime, audience, acquisition, behaviour and conversions. It can be hard for experienced marketers, let alone beginners, to find their way around these new reports. 

  AI insights

  GA4 has machine learning (ML) capabilities that allow you to generate AI insights from your data. Specifically, GA4 has predictive analytics features that let you track three trends : 

  • Purchase probability : the likelihood that a consumer will make a purchase in a given timeframe.
  • Churn probability : the likelihood a customer will churn in a given period.
  • Predictive revenue : the amount of revenue a user is likely to generate over a given period. 

  Google generates these insights using historical data and machine learning algorithms. 

  Cross-platform capabilities

  GA4 also offers cross-platform capabilities, meaning it can track user interactions across websites and mobile apps, giving businesses a holistic view of customer behaviour. This allows for better decision-making throughout the customer journey.

  Does GA4 360 come with other risks ?

  Aside from the poor usability, complexity and steep learning curve, upgrading your GA360 property to GA4 comes with several other risks.

  GA4 has a rocky relationship with privacy regulations, and while you can use it in a GDPR-compliant way at the moment, there’s no guarantee you’ll be able to do so in the future. 

  This presents the prospect of fines for non-compliance. A worse risk, however, is regulators forcing you to change web analytics platforms in the future—something that’s already happened in the EU. Migrating to a new application can be incredibly painful and time-consuming, especially when you can choose a privacy-friendly alternative that avoids the possibility of this scenario. 

  If all this wasn’t bad enough, switching to GA4 risks your historical Universal Analytics data. That’s because you can’t import Universal Analytics data into GA4, even if you migrate ahead of the sunset deadline.

  Why you should consider a GA4 360 alternative instead

  With the GA360 sunset on the horizon, what are your options if you don’t want to deal with GA4’s problems ? 

  The easiest solution is to migrate to a GA4 360 alternative instead. And there are plenty of reasons to migrate from Google Analytics to a privacy-friendly alternative like Matomo. 

  Keep historical data

  As we’ve explained, Google isn’t letting users import their Universal Analytics data from GA360 to GA4. The easiest way to keep it is by switching to a Google Analytics alternative like Matomo that lets you import your historical data. 

  Any business using Google Analytics, whether a GA360 user or otherwise, can import data into Matomo using our Google Analytics Importer plugin. It’s the best way to avoid disruption or losing data when moving on from Universal Analytics.

  Collect 100% accurate data

  Google Analytics implements data sampling and machine learning to fill gaps in your data and generate the kind of predictive insights we mentioned earlier. For standard GA4 users, data sampling starts at 10 million events. For GA4 360 users, data sampling starts at one billion events. Nevertheless, Google Analytics data may not accurately reflect your web traffic. 

  You can fix this using a Google Analytics alternative like Matomo that doesn’t use data sampling. That way, you can be confident that your data-driven decisions are being made with 100% accurate user data. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  Guarantee user privacy first

  Google has a stormy relationship with the EU-US Data Privacy Framework—being banned and added back to the framework in recent years.

  Currently, organisations governed by GDPR can use Google Analytics to collect data about EU residents, but there’s no guarantee of their ability to do so in the future. Nor does the Framework prevent Google from using EU customer data for ulterior purposes such as marketing and training large language models. 

  By switching to a privacy-focused alternative like Matomo, you don’t have to worry about your user’s data ending up in the wrong hands.

  Upgrade to an all-in-one analytics tool

  Switching from Google Analytics can actually give organisations access to more features. That’s because some GA4 alternatives, like Matomo, offer advanced conversion optimisation features like heatmaps, session recordings, A/B testing, form analytics and more right out of the box. 

  

  This makes Matomo a great choice for marketing teams that want to minimise their tech stack and use one tool for both web and behavioural analytics. 

  Get real-time reports

  GA4 isn’t the best tool for analysing website visitors in real time. That’s because it can take up to 4 hours to process new reports in GA360.

  However, Google Analytics alternatives like Matomo have a range of real-time reports you can leverage.

  

  In Matomo, the Real Time Visitor World Map and other reports are processed every 15 minutes. There is also a Visits in Real-time report, which refreshes every five seconds and shows a wealth of data for each visitor. 

  Matomo makes migration easy

  Whether it’s the poor usability, steep learning curve, inaccurate data or privacy issues, there’s every reason to think twice about migrating your UA360 account to GA4. 

  So why not migrate to a Google Analytics alternative like Matomo instead ? One that doesn’t sample data, guarantees your customers’ privacy, offers all the features GA4 doesn’t and is already used by over 1 million sites worldwide.

  Making the switch is easy. Matomo is one of the few web analytics tools that lets you import historical Google Analytics data. In doing so, you can continue to access your historical data and develop more meaningful insights by not having to start from scratch.

  If you’re ready to start a Google Analytics migration, you can try Matomo free for 21 days — no credit card required. 

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• Google Optimize vs Matomo A/B Testing : Everything You Need to Know

  17 mars 2023, par Erin — Analytics Tips

  Google Optimize is a popular A/B testing tool marketers use to validate the performance of different marketing assets, website design elements and promotional offers. 

  But by September 2023, Google will sunset both free and paid versions of the Optimize product. 

  If you’re searching for an equally robust, but GDPR compliant, privacy-friendly alternative to Google Optimize, have a look at Matomo A/B Testing. 

  Integrated with our analytics platform and conversion rate optimisation (CRO) tools, Matomo allows you to run A/B and A/B/n tests without any usage caps or compromises in user privacy.

  Disclaimer : Please note that the information provided in this blog post is for general informational purposes only and is not intended to provide legal advice. Every situation is unique and requires a specific legal analysis. If you have any questions regarding the legal implications of any matter, please consult with your legal team or seek advice from a qualified legal professional.

  Google Optimize vs Matomo : Key Capabilities Compared 

  This guide shows how Matomo A/B testing stacks against Google Optimize in terms of features, reporting, integrations and pricing.

  Supported Platforms 

  Google Optimize supports experiments for dynamic websites and single-page mobile apps only. 

  If you want to run split tests in mobile apps, you’ll have to do so via Firebase — Google’s app development platform. It also has a free tier but paid usage-based subscription kicks in after your product(s) reaches a certain usage threshold. 

  Google Optimize also doesn’t support CRO experiments for web or desktop applications, email campaigns or paid ad campaigns.Matomo A/B Testing, in contrast, allows you to run experiments in virtually every channel. We have three installation options — using JavaScript, server-side technology, or our mobile tracking SDK. These allow you to run split tests in any type of web or mobile app (including games), a desktop product, or on your website. Also, you can do different email marketing tests (e.g., compare subject line variants).

  A/B Testing 

  A/B testing (split testing) is the core feature of both products. Marketers use A/B testing to determine which creative elements such as website microcopy, button placements and banner versions, resonate better with target audiences. 

  You can benchmark different versions against one another to determine which variation resonates more with users. Or you can test an A version against B, C, D and beyond. This is called A/B/n testing. 

  Both Matomo A/B testing and Google Optimize let you test either separate page elements or two completely different landing page designs, using redirect tests. You can show different variants to different user groups (aka apply targeting criteria). For example, activate tests only for certain device types, locations or types of on-site behaviour. 

  The advantage of Matomo is that we don’t limit the number of concurrent experiments you can run. With Google Optimize, you’re limited to 5 simultaneous experiments. Likewise, 

  Matomo lets you select an unlimited number of experiment objectives, whereas Google caps the maximum choice to 3 predefined options per experiment. 

  Objectives are criteria the underlying statistical model will use to determine the best-performing version. Typically, marketers use metrics such as page views, session duration, bounce rate or generated revenue as conversion goals. 

  

  Multivariate testing (MVT)

  Multivariate testing (MVT) allows you to “pack” several A/B tests into one active experiment. In other words : You create a stack of variants to determine which combination drives the best marketing outcomes. 

  For example, an MVT experiment can include five versions of a web page, where each has a different slogan, product image, call-to-action, etc. Visitors are then served with a different variation. The tracking code collects data on their behaviours and desired outcomes (objectives) and reports the results.

  MVT saves marketers time as it’s a great alternative to doing separate A/B tests for each variable. Both Matomo and Google Optimize support this feature. However, Google Optimize caps the number of possible combinations at 16, whereas Matomo has no limits. 

  Redirect Tests

  Redirect tests, also known as split URL tests, allow you to serve two entirely different web page versions to users and compare their performance. This option comes in handy when you’re redesigning your website or want to test a localised page version in a new market. 

  Also, redirect tests are a great way to validate the performance of bottom-of-the-funnel (BoFU) pages as a checkout page (for eCommerce websites), a pricing page (for SaaS apps) or a contact/booking form (for a B2B service businesses). 

  You can do split URL tests with Google Optimize and Matomo A/B Testing. 

  Experiment Design 

  Google Optimize provides a visual editor for making simple page changes to your website (e.g., changing button colour or adding several headline variations). You can then preview the changes before publishing an experiment. For more complex experiments (e.g., testing different page block sequences), you’ll have to codify experiments using custom JavaScript, HTML and CSS.

  In Matomo, all A/B tests are configured on the server-side (i.e., by editing your website’s raw HTML) or client-side via JavaScript. Afterwards, you use the Matomo interface to start or schedule an experiment, set objectives and view reports. 

  Experiment Configuration 

  Marketers know how complex customer journeys can be. Multiple factors — from location and device to time of the day and discount size — can impact your conversion rates. That’s why a great CRO app allows you to configure multiple tracking conditions. 

  Matomo A/B testing comes with granular controls. First of all, you can decide which percentage of total web visitors participate in any given experiment. By default, the number is set to 100%, but you can change it to any other option. 

  Likewise, you can change which percentage of traffic each variant gets in an experiment. For example, your original version can get 30% of traffic, while options A and B receive 40% each. We also allow users to specify custom parameters for experiment participation. You can only show your variants to people in specific geo-location or returning visitors only. 

  Finally, you can select any type of meaningful objective to evaluate each variant’s performance. With Matomo, you can either use standard website analytics metrics (e.g., total page views, bounce rate, CTR, visit direction, etc) or custom goals (e.g., form click, asset download, eCommerce order, etc). 

  In other words : You’re in charge of deciding on your campaign targeting criteria, duration and evaluation objectives.

  A free Google Optimize account comes with three main types of user targeting options : 

  • Geo-targeting at city, region, metro and country levels. 

  • Technology targeting  by browser, OS or device type, first-party cookie, etc. 
  • Behavioural targeting based on metrics like “time since first arrival” and “page referrer” (referral traffic source). 

  Users can also configure other types of tracking scenarios (for example to only serve tests to signed-in users), using condition-based rules. 

  Reporting 

  Both Matomo and Google Optimize use different statistical models to evaluate which variation performs best. 

  Matomo relies on statistical hypothesis testing, which we use to count unique visitors and report on conversion rates. We analyse all user data (with no data sampling applied), meaning you get accurate reporting, based on first-hand data, rather than deductions. For that reason, we ask users to avoid drawing conclusions before their experiment participation numbers reach a statistically significant result. Typically, we recommend running an experiment for at least several business cycles to get a comprehensive report. 

  Google Optimize, in turn, uses Bayesian inference — a statistical method, which relies on a random sample of users to compare the performance rates of each creative against one another. While a Bayesian model generates CRO reports faster and at a bigger scale, it’s based on inferences.

  Model developers need to have the necessary skills to translate subjective prior beliefs about the probability of a certain event into a mathematical formula. Since Google Optimize is a proprietary tool, you cannot audit the underlying model design and verify its accuracy. In other words, you trust that it was created with the right judgement. 

  In comparison, Matomo started as an open-source project, and our source code can be audited independently by anyone at any time. 

  Another reporting difference to mind is the reporting delays. Matomo Cloud generates A/B reports within 6 hours and in only 1 hour for Matomo On-Premise. Google Optimize, in turn, requires 12 hours from the first experiment setup to start reporting on results. 

  When you configure a test experiment and want to quickly verify that everything is set up correctly, this can be an inconvenience.

  User Privacy & GDPR Compliance 

  Google Optimize works in conjunction with Google Analytics, which isn’t GDPR compliant. 

  For all website traffic from the EU, you’re therefore obliged to show a cookie consent banner. The kicker, however, is that you can only show an Optimize experiment after the user gives consent to tracking. If the user doesn’t, they will only see an original page version. Considering that almost 40% of global consumers reject cookie consent banners, this can significantly affect your results.

  This renders Google Optimize mostly useless in the EU since it would only allow you to run tests with a fraction ( 60%) of EU traffic — and even less if you apply any extra targeting criteria. 

  In comparison, Matomo is fully GDPR compliant. Therefore, our users are legally exempt from displaying cookie-consent banners in most EU markets (with Germany and the UK being an exception). Since Matomo A/B testing is part of Matomo web analytics, you don’t have to worry about GDPR compliance or breaches in user privacy. 

  Digital Experience Intelligence 

  You can get comprehensive statistical data on variants’ performance with Google Optimize. But you don’t get further insights on why some tests are more successful than others. 

  Matomo enables you to collect more insights with two extra features :

  • User session recordings : Monitor how users behave on different page versions. Observe clicks, mouse movements, scrolls, page changes, and form interactions to better understand the users’ cumulative digital experience. 
  • Heatmaps : Determine which elements attract the most users’ attention to fine-tune your split tests. With a standard CRO tool, you only assume that a certain page element does matter for most users. A heatmap can help you determine for sure. 

  Both of these features are bundled into your Matomo Cloud subscription. 

  Integrations 

  Both Matomo and Google Optimize integrate with multiple other tools. 

  Google Optimize has native integrations with other products in the marketing family — GA, Google Ads, Google Tag Manager, Google BigQuery, Accelerated Mobile Pages (AMP), and Firebase. Separately, other popular marketing apps have created custom connectors for integrating Google Optimize data. 

  Matomo A/B Testing, in turn, can be combined with other web analytics and CRO features such as Funnels, Multi-Channel Attribution, Tag Manager, Form Analytics, Heatmaps, Session Recording, and more ! 

  You can also conveniently export your website analytics or CRO data using Matomo Analytics API to analyse it in another app. 

  Pricing 

  Google Optimize is a free tool but has usage caps. If you want to schedule more than 5 concurrent experiments or test more than 16 variants at once, you’ll have to upgrade to Optimize 360. Optimize 360 prices aren’t listed publicly but are said to be closer to six figures per year. 

  Matomo A/B Testing is available with every Cloud subscription (starting from €19) and Matomo On-Premise users can also get A/B Testing as a plugin (starting from €199/year). In each case, there are no caps or data limits. 

  Google Optimize vs Matomo A/B Testing : Comparison Table

  Features/capabilities	Google Optimize	Matomo A/B test
  Supported channels	Web	Web, mobile, email, digital campaigns
  A/B testing
  Multivariate testing (MVT)
  Split URL tests
  Web analytics integration	Native with UA/GA4	Native with Matomo You can also migrate historical UA (GA3) data to Matomo
  Audience segmentation	Basic	Advanced
  Geo-targeting
  Technology targeting
  Behavioural targeting	Basic	Advanced
  Reporting model	Bayesian analysis	Statistical hypothesis testing
  Report availability	Within 12 hours after setup	6 hours for Matomo Cloud 1 hour for Matomo On-Premise
  Heatmaps		Included with Matomo Cloud
  Session recordings		Included with Matomo Cloud
  GDPR compliance
  Support	Self-help desk on a free tier	Self-help guides, user forum, email
  Price	Free limited tier	From €19 for Cloud subscription From €199/year as plugin for On-Premise

  Final Thoughts : Who Benefits the Most From an A/B Testing Tool ?

  Split testing is an excellent method for validating various assumptions about your target customers. 

  With A/B testing tools you get a data-backed answer to research hypotheses such as “How different pricing affects purchases ?”, “What contact button placement generates more clicks ?”, “Which registration form performs best with new app subscribers ?” and more. 

  Such insights can be game-changing when you’re trying to improve your demand-generation efforts or conversion rates at the BoFu stage. But to get meaningful results from CRO tests, you need to select measurable, representative objectives.

  For example, split testing different pricing strategies for low-priced, frequently purchased products makes sense as you can run an experiment for a couple of weeks to get a statistically relevant sample. 

  But if you’re in a B2B SaaS product, where the average sales cycle takes weeks (or months) to finalise and things like “time-sensitive discounts” or “one-time promos” don’t really work, getting adequate CRO data will be harder. 

  To see tangible results from CRO, you’ll need to spend more time on test ideation than implementation. Your team needs to figure out : which elements to test, in what order, and why. 

  Effective CRO tests are designed for a specific part of the funnel and assume that you’re capable of effectively identifying and tracking conversions (goals) at the selected stage. This alone can be a complex task since not all customer journeys are alike. For SaaS websites, using a goal like “free trial account registration” can be a good starting point.

  A good test also produces a meaningful difference between the proposed variant and the original version. As Nima Yassini, Partner at Deloitte Digital, rightfully argues :

  “I see people experimenting with the goal of creating an uplift. There’s nothing wrong with that, but if you’re only looking to get wins you will be crushed when the first few tests fail. The industry average says that only one in five to seven tests win, so you need to be prepared to lose most of the time”.

  In many cases, CRO tests don’t provide the data you expected (e.g., people equally click the blue and green buttons). In this case, you need to start building your hypothesis from scratch. 

  At the same time, it’s easy to get caught up in optimising for “vanity metrics” — such that look good in the report, but don’t quite match your marketing objectives. For example, better email headline variations can improve your email open rates. But if users don’t proceed to engage with the email content (e.g. click-through to your website or use a provided discount code), your efforts are still falling short. 

  That’s why developing a baseline strategy is important before committing to an A/B testing tool. Google Optimize appealed to many users because it’s free and allows you to test your split test strategy cost-effectively. 

  With its upcoming depreciation, many marketers are very committed to a more expensive A/B tool (especially when they’re not fully sure about their CRO strategy and its results). 

  Matomo A/B testing is a cost-effective, GDPR-compliant alternative to Google Optimize with a low learning curve and extra competitive features. 

  Discover if Matomo A/B Testing is the ideal Google Optimize alternative for your organization with our free 21-day trial. No credit card required.

• 11 of the Most Effective Conversion Rate Optimisation Best Practices

  14 février 2024, par Erin

  Driving more traffic to your website is hard work, but it’s still only half the battle. 

  You don’t just need to acquire new users ; you need to make sure as many convert as possible to make your digital marketing efforts worthwhile.

  That’s why improving your site’s conversion rate is so important. It will also help you get more value from your existing traffic source and keep you in line with your competitors. It’s also probably a lot easier than you think — especially if you adopt optimisation strategies that have been proven to be profitable time and time again. 

  In this article, we’ll show some of the most powerful, innovative and tried-and-tested conversion rate optimisation strategies you can implement immediately. 

  What is conversion rate optimisation ?

  First, let’s look at what conversion rate optimisation means. Conversion rate optimisation is the practice of improving elements of your website to increase the number of users who take a desired action and turn visitors into customers. 

  Common conversion goals include :

  • Making a purchase
  • Adding an item to a shopping cart
  • Signing up for a newsletter
  • Registering for a free trial
  • Downloading an ebook
  • Watching a video

  It doesn’t matter what your goal is. Using one of the following conversion rate optimisation best practices can send your conversions soaring. 

  11 conversion rate optimisation best practices 

  Are you ready to roll up your sleeves and get to work ? Then use one or more of the following best practices to improve your return on investment. 

  Set a clear goals and hypothesis

  When running an A/B or multivariate test, you need a clear idea of what you are testing and why. 

  A goal (a statement about what you want to achieve) and a hypothesis (a statement about what you expect to happen) clarify the problem you are trying to solve and give you a definitive way to judge the experiment’s results. 

  Confused ? Just use this template :

  We aim to [insert goal] by testing [insert test] on [insert page]. We expect that [insert test] will increase [insert metric] because [insert reason].

  Make sure your goals are directly related to the experiment. If you are testing your CTA button, the goal should be getting more users to click the button. It shouldn’t be a goal further down the conversion funnel, like making a purchase. 

  Start with A/B tests

  A/B testing is one of the easiest and most effective ways to run experiments to improve your current conversion rate. So, it’s no wonder that the A/B testing software market was expected to be worth $1.2 billion in 2023 and hit $3.6 billion by 2033. 

  Also known as split testing, A/B testing allows you to directly compare the conversion performance of two elements on your page, like the colour of your CTA button or your headline copy.

  

  You can go even further with multivariate testing, which lets you test two or more changes against a single control. 

  For example, the screenshot above shows the results of a multivariate test between a standard header, a wide header and a small header using Matomo’s A/B testing tool. As you can see, the wider header has a much higher conversion, and the increase was statistically significant. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  Tweak your CTAs

  Calls to action (CTAs) are page elements that prompt users to respond immediately. They are usually buttons but can also be images or plain text links. 

  What your CTAs say, how they look, and where they are placed can greatly impact your site’s conversion rates. As such, this is one of the elements you’ll want to optimise first. 

  There are several tweaks you can test, including your CTA’s :

  • Colour 
  • Length 
  • Copy
  • Placement 

  You can even test the impact of removing CTA banners and using text-based CTAs on your conversion rates.

  You should test out personalising CTAs, too. Research shows that personalised CTAs perform 202% better than standard calls to action. 

  Revise your web copy

  You can use several strategies to improve your website’s copy and generate more conversions. 

  Optimising copy for search engines can increase traffic and generate more conversions, for example. But that shouldn’t make your copy any less impactful. Bear search engines in mind, by all means, but make sure you are speaking to the needs and desires of your potential customers. Your copy needs to convince users that your product can solve their problems. 

  Nowhere is this more important than your headlines. These will be the first thing users read, so make sure they sell your USP and highlight pain points.

  Don’t just guess at the kind of messaging that will move the needle, however. Constantly test new headlines and continue doing so even after you’ve started seeing success. The results may surprise you. TruckersReport, a site that helps people become truck drivers, boosted opt-ins by 21.7% by revising its landing page headline, among other changes. 

  Make sure there are no spelling mistakes in your copy, either. Misspelt words, poor grammar and bad formatting make your website look unprofessional and untrustworthy. Even if the rest of your copy is incredibly enticing, these rookie errors can be enough to turn customers off. 

  Simplify your site’s navigation

  A website’s navigation is an often overlooked factor in conversion rate optimisation, but simplifying it can make it much easier for users to take action. 

  If you’ve ever used a poorly designed e-commerce store, you know how confusing and overwhelming bad navigation can be. Research shows that a whopping 82% of stores don’t divide their navigation into manageable chunks. 

  The trick is to simplify your navigation as much as possible. As you can see in the screenshot below, our navigation only has five headers and a call to action. It’s easy to find exactly what you’re looking for, and you can’t miss the big green CTA button. 

  

  Alternatively, you can test what happens when you completely remove your navigation. Brands usually do this on landing pages where the only action they want the user to take is to make a purchase. 

  

  It’s exactly the strategy we’ve used on our free trial landing page. 

  Leverage heatmaps

  Analytics tools — and heatmaps in particular — can help you understand user behaviour and optimise accordingly. 

  Heatmaps are a visual representation of user interaction on your page. Red and yellow represent high levels of user interaction, and blue and green represent low levels of interaction.

  

  As you can see in the screenshot above, our CTA button has some of the highest levels of engagement on the page, telling us that it’s well-positioned. Given the focus on the site’s navigation, we can also assume we are correct to have a CTA button in there — something we can confirm using our web analytics to see how many users click on it.

  Reduce load time

  Speed matters when it comes to conversions. Fact. 

  Research shows a huge difference in conversion rates between quick and slow sites. For example, a site that loads in one second converts three times better than a site that loads in five seconds. 

  That’s why using a web analytics tool is vital to understand page load times and act accordingly if you think slow speeds are hampering your conversions.

  

  Identifying your slowest pages is easy with Matomo. Just sort your pages by the Avg. Use the page load time metric on the page performance report to identify the pages you want to drive conversions. 

  Next, take steps to improve your page’s load time by :

  • Compressing images
  • Compressing code files or using a more lightweight theme
  • Removing unnecessary plugins
  • Using a content delivery network
  • Improving your hosting

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  Add more trust signals

  Trust is essential when you’re trying to convince customers to make a purchase. In fact, consumers rate trust as one of the top three buying factors, far above a brand’s reputation and whether they love the brand. 

  Adding trust signals to your landing pages, such as customer testimonials, customer reviews, case studies, and other forms of social proof, can transform your conversion rates. If consumers see real people and businesses buy from you, they’ll feel reassured to do the same.

  

  It’s a strategy we use ourselves. Just look at the screenshot from our homepage above. Immediately after our free trial CTA, we display the logos of well-known brands that use our product. 

  Security-focused trust signals are also powerful if you are an online store. Installing an SSL certificate, showing logos of trusted payment providers (like PayPal and Mastercard) can convince people they are spending money at a legitimate store.

  Improve your site’s mobile experience

  More and more people are accessing the internet via their smartphones. In 2022, for instance, there were five billion unique mobile Internet users, meaning more than 60% of the internet population used a smartphone to browse online. 

  Moreover, 76% of U.S. adults make purchases using their smartphones. 

  That means you need to ensure your site’s mobile experience is on-point to increase conversions. 

  Your site should use a mobile-first design, meaning it works perfectly on smartphones and then scales up for desktop users. 

  Trust the data

  Opinions are a fantastic form of inspiration for new A/B tests. But they should never be trusted over cold, hard data. If your test shows the opposite of what you and your team thought would happen, then trust the data and not yourself.

  With that in mind, ensure you collect qualitative and quantitative data during your experiments. Web analytics should always form the backbone of conversion tests, but don’t forget to also use heatmaps, screen recordings, and customer surveys. 

  Keep testing

  There’s no such word as “finished” in the world of A/B testing. Continual testing is key if you want to convert more website visitors. 

  Make sure you aren’t stopping tests prematurely, either. Make sure every A/B and multivariate test reaches a sample size that makes the test statistically significant. 

  Understand your users better with Matomo 

  Whether you run an e-commerce store, a SaaS company, or a service-based business, implementing these conversion rate optimisation best practices could be an easy way to lower your bounce rate and boost your conversion rates.

  But remember, best practices aren’t clear-cut rules. What works for one website may not work for yours. That’s why running your own tests and understanding your visitors’ behaviour is important. 

  Matomo’s web analytics platform is the perfect tool for doing just that. Not only does it come with the tools you need to optimise your conversion rate (like an A/B testing tool, heatmaps and session recordings), but you can also trust the data. Unlike Google Analytics 4 and other tools, Matomo doesn’t use data sampling meaning you have 100% accurate data from which to make better decisions. It’s GDPR compliant and can run cookieless, so no need for cookie consent banners (excluding in the UK and Germany).

  Discover how you can improve your website’s conversions with Matomo by starting a free 21-day trial, no credit card required.

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