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• Benefits and Shortcomings of Multi-Touch Attribution

  13 mars 2023, par Erin — Analytics Tips

  Few sales happen instantly. Consumers take their time to discover, evaluate and become convinced to go with your offer. 

  Multi-channel attribution (also known as multi-touch attribution or MTA) helps businesses better understand which marketing tactics impact consumers’ decisions at different stages of their buying journey. Then double down on what’s working to secure more sales. 

  Unlike standard analytics, multi-channel modelling combines data from various channels to determine their cumulative and independent impact on your conversion rates. 

  The main benefit of multi-touch attribution is obvious : See top-performing channels, as well as those involved in assisted conversions. The drawback of multi-touch attribution : It comes with a more complex setup process. 

  If you’re on the fence about getting started with multi-touch attribution, here’s a summary of the main arguments for and against it. 

  What Are the Benefits of Multi-Touch Attribution ?

  Remember an old parable of blind men and an elephant ?

  Each one touched the elephant and drew conclusions about how it might look. The group ended up with different perceptions of the animal and thought the others were lying…until they decided to work together on establishing the truth.

  Multi-channel analytics works in a similar way : It reconciles data from various channels and campaign types into one complete picture. So that you can get aligned on the efficacy of different campaign types and gain some other benefits too. 

  Better Understanding of Customer Journeys 

  On average, it takes 8 interactions with a prospect to generate a conversion. These interactions happen in three stages : 

  • Awareness : You need to introduce your company to the target buyers and pique their interest in your solution (top-of-the-funnel). 
  • Consideration : The next step is to channel this casual interest into deliberate research and evaluation of your offer (middle-of-the-funnel). 
  • Decision : Finally, you need to get the buyer to commit to your offer and close the deal (bottom-of-the-funnel). 

  You can analyse funnels using various attribution models — last-click, fist-click, position-based attribution, etc. Each model, however, will spotlight the different element(s) of your sales funnel. 

  For example, a single-touch attribution model like last-click zooms in on the bottom-of-the-funnel stage. You can evaluate which channels (or on-site elements) sealed the deal for the prospect. For example, a site visitor arrived from an affiliate link and started a free trial. In this case, the affiliate (referral traffic) gets 100% credit for the conversion. 

  This measurement tactic, however, doesn’t show which channels brought the customer to the very bottom of your funnel. For instance, they may have interacted with a social media post, your landing pages or a banner ad before that. 

  Multi-touch attribution modelling takes funnel analysis a notch further. In this case, you map more steps in the customer journey — actions, events, and pages that triggered a visitor’s decision to convert — in your website analytics tool.

  

  Then, select a multi-touch attribution model, which provides more backward visibility aka allows you to track more than one channel, preceding the conversion. 

  For example, a Position Based attribution model reports back on all interactions a site visitor had between their first visit and conversion. 

  A prospect first lands at your website via search results (Search traffic), which gets a 40% credit in this model. Two days later, the same person discovers a mention of your website on another blog and visits again (Referral traffic). This time, they save the page as a bookmark and revisit it again in two more days (Direct traffic). Each of these channels will get a 10% credit. A week later, the prospect lands again on your site via Twitter (Social) and makes a request for a demo. Social would then receive a 40% credit for this conversion. Last-click would have only credited social media and first-click — search engines. 

  The bottom line : Multi-channel attribution models show how different channels (and marketing tactics) contribute to conversions at different stages of the customer journey. Without it, you get an incomplete picture.

  Improved Budget Allocation 

  Understanding causal relationships between marketing activities and conversion rates can help you optimise your budgets.

  First-click/last-click attribution models emphasise the role of one channel. This can prompt you toward the wrong conclusions. 

  For instance, your Facebook ads campaigns do great according to a first-touch model. So you decide to increase the budget. What you might be missing though is that you could have an even higher conversion rate and revenue if you fix “funnel leaks” — address high drop-off rates during checkout, improve page layout and address other possible reasons for exiting the page.

  

  By knowing when and why people abandon their purchase journey, you can improve your marketing velocity (aka the speed of seeing the campaign results) and your marketing costs (aka the budgets you allocate toward different assets, touchpoints and campaign types). 

  Or as one of the godfathers of marketing technology, Dan McGaw, explained in a webinar :

  “Once you have a multi-touch attribution model, you [can] actually know the return on ad spend on a per-campaign basis. Sometimes, you can get it down to keywords. Sometimes, you can get down to all kinds of other information, but you start to realise, “Oh, this campaign sucks. I should shut this off.” And then really, that’s what it’s about. It’s seeing those campaigns that suck and turning them off and then taking that budget and putting it into the campaigns that are working”.

  More Accurate Measurements 

  The big boon of multi-channel marketing attribution is that you can zoom in on various elements of your funnel and gain granular data on the asset’s performance. 

  In other words : You get more accurate insights into the different elements involved in customer journeys. But for accurate analytics measurements, you must configure accurate tracking. 

  Define your objectives first : How do you want a multi-touch attribution tool to help you ? Multi-channel attribution analysis helps you answer important questions such as :

  • How many touchpoints are involved in the conversions ? 
  • How long does it take for a lead to convert on average ? 
  • When and where do different audience groups convert ? 
  • What is your average win rate for different types of campaigns ?

  Your objectives will dictate which multi-channel modelling approach will work best for your business — as well as the data you’ll need to collect. 

  At the highest level, you need to collect two data points :

  • Conversions : Desired actions from your prospects — a sale, a newsletter subscription, a form submission, etc. Record them as tracked Goals. 
  • Touchpoints : Specific interactions between your brand and targets — specific page visits, referral traffic from a particular marketing channel, etc. Record them as tracked Events. 

  Your attribution modelling software will then establish correlation patterns between actions (conversions) and assets (touchpoints), which triggered them. 

  The accuracy of these measurements, however, will depend on the quality of data and the type of attribution modelling used. 

  Data quality stands for your ability to procure accurate, complete and comprehensive information from various touchpoints. For instance, some data won’t be available if the user rejected a cookie consent banner (unless you’re using a privacy-focused web analytics tool like Matomo). 

  Different attribution modelling techniques come with inherent shortcomings too as they don’t accurately represent the average sales cycle length or track visitor-level data, which allows you to understand which customer segments convert best.

  Learn more about selecting the optimal multi-channel attribution model for your business.

  What Are the Limitations of Multi-Touch Attribution ?

  Overall, multi-touch attribution offers a more comprehensive view of the conversion paths. However, each attribution model (except for custom ones) comes with inherent assumptions about the contribution of different channels (e.g,. 25%-25%-25%-25% in linear attribution or 40%-10%-10%-40% in position-based attribution). These conversion credit allocations may not accurately represent the realities of your industry. 

  Also, most attribution models don’t reflect incremental revenue you gain from existing customers, which aren’t converting through analysed channels. For example, account upgrades to a higher tier, triggered via an in-app offer. Or warranty upsell, made via a marketing email. 

  In addition, you should keep in mind several other limitations of multi-touch attribution software.

  Limited Marketing Mix Analysis 

  Multi-touch attribution tools work in conjunction with your website analytics app (as they draw most data from it). Because of that, such models inherit the same visibility into your marketing mix — a combo of tactics you use to influence consumer decisions.

  Multi-touch attribution tools cannot evaluate the impact of :

  • Dark social channels 
  • Word-of-mouth 
  • Offline promotional events
  • TV or out-of-home ad campaigns 

  If you want to incorporate this data into your multi-attribution reporting, you’ll have to procure extra data from other systems — CRM, ad measurement partners, etc, — and create complex custom analytics models for its evaluation.

  Time-Based Constraints 

  Most analytics apps provide a maximum 90-day lookback window for attribution. This can be short for companies with longer sales cycles. 

  

  Marketing channels can be overlooked or underappreciated when your attribution window is too short. Because of that, you may curtail spending on brand awareness campaigns, which, in turn, will reduce the number of people entering the later stages of your funnel. 

  At the same time, many businesses would also want to track a look-forward window — the revenue you’ll get from one customer over their lifetime. In this case, not all tools may allow you to capture accurate information on repeat conversions — through re-purchases, account tier updates, add-ons, upsells, etc. 

  Again, to get an accurate picture you’ll need to understand how far into the future you should track conversions. Will you only record your first sales as a revenue number or monitor customer lifetime value (CLV) over 3, 6 or 12 months ? 

  The latter is more challenging to do. But CLV data can add another depth of dimension to your modelling accuracy. With Matomo, you set up this type of tracking by using our visitors’ tracking feature. We can help you track select visitors with known identifiers (e.g. name or email address) to discover their visiting patterns over time. 

  

  Limited Access to Raw Data 

  In web analytics, raw data stands for unprocessed website visitor information, stripped from any filters, segmentation or sampling applied. 

  Data sampling is a practice of analysing data subsets (instead of complete records) to extrapolate findings towards the entire data set. Google Analytics 4 applies data sampling once you hit over 500k sessions at the property level. So instead of accurate, real-life reporting, you receive approximations, generated by machine learning models. Data sampling is one of the main reasons behind Google Analytics’ accuracy issues. 

  In multi-channel attribution modelling, usage of sampled data creates further inconsistencies between the reports and the actual state of affairs. For instance, if your website generates 5 million page views, GA multi-touch analytical reports are based on the 500K sample size aka only 90% of the collected information. This hardly represents the real effect of all marketing channels and can lead to subpar decision-making. 

  With Matomo, the above is never an issue. We don’t apply data sampling to any websites (no matter the volume of traffic) and generate all the reports, including multi-channel attribution ones, based on 100% real user data. 

  AI Application 

  On the other hand, websites with smaller traffic volumes often have limited sampling datasets for building attribution models. Some tracking data may also be not available because the visitor rejected a cookie banner, for instance. On average, less than 50% of users in Australia, France, Germany, Denmark and the US among other countries always consent to all cookies. 

  To compensate for such scenarios, some multi-touch attribution solutions apply AI algorithms to “fill in the blanks”, which impacts the reporting accuracy. Once again, you get approximate data of what probably happened. However, Matomo is legally exempt from showing a cookie consent banner in most EU markets. Meaning you can collect 100% accurate data to make data-driven decisions.

  Difficult Technical Implementation 

  Ever since attribution modelling got traction in digital marketing, more and more tools started to emerge.

  

  Most web analytics apps include multi-touch attribution reports. Then there are standalone multi-channel attribution platforms, offering extra features for conversion rate optimization, offline channel tracking, data-driven custom modelling, etc. 

  Most advanced solutions aren’t available out of the box. Instead, you have to install several applications, configure integrations with requested data sources, and then use the provided interfaces to code together custom data models. Such solutions are great if you have a technical marketer or a data science team. But a steep learning curve and high setup costs make them less attractive for smaller teams. 

  Conclusion 

  Multi-touch attribution modelling lifts the curtain in more steps, involved in various customer journeys. By understanding which touchpoints contribute to conversions, you can better plan your campaign types and budget allocations. 

  That said, to benefit from multi-touch attribution modelling, marketers also need to do the preliminary work : Determine the key goals, set up event and conversion tracking, and then — select the optimal attribution model type and tool. 

  Matomo combines simplicity with sophistication. We provide marketers with familiar, intuitive interfaces for setting up conversion tracking across the funnel. Then generate attribution reports, based on 100% accurate data (without any sampling or “guesstimation” applied). You can also get access to raw analytics data to create custom attribution models or plug it into another tool ! 

  Start using accurate, easy-to-use multi-channel attribution with Matomo. Start your free 21-day trial now. No credit card requried. 

• How to Track Website Visitors : Benefits, Tools and FAQs

  31 août 2023, par Erin — Analytics Tips, Marketing

  Businesses spend a ton of time, money and effort into creating websites that are not only helpful and captivating, but also highly effective at converting visitors. They’ll create content, revise designs, add new pages and change forms, all in the hope of getting visitors to stay on the site and convert into leads or customers.

  When you track website visitors, you can see which of your efforts are moving the needle. While many people are familiar with pageviews as a metric, website visitor tracking can be much more in-depth and insightful.

  In this article, we’ll cover how website visitor tracking works, what you can track, and how this information can improve sales and marketing results. We’ll also explain global privacy concerns and how businesses can choose the right tracking software. 

  What is website visitor tracking ? 

  Website visitor tracking uses software and applications to track and analyse how visitors interact with your website. It’s a vital tool to help businesses understand whether their website design and content are having the desired effect.

  

  Website visitor tracking includes very broad, non-specific data, like how many times visitors have come to your site. But it can also get very specific, with personal information about the user and even recordings of their visit to your site. Site visits, which may include visiting several different pages of the same site, are often referred to as “sessions.”

  Although Google Analytics is the most widely used website visitor tracking software, it isn’t the most comprehensive or powerful. Companies that want a more in-depth understanding of their website may need to consider running a more precise tool alongside Google Analytics, like Matomo.

  As we’ll cover later, website tracking has many important business applications, but it also poses privacy and security concerns, causing some states and countries to impose strict regulations. Privacy laws and your company’s values should also impact what web analytics tool you choose.

  How website tracking works

  Website tracking starts with the collection of data as users interact with the website. Tracking technologies like cookies, JavaScript and pixels are embedded into web pages. These technologies then gather data about user behaviour, session details and user actions, such as pageviews, clicks, form submissions and more.

  More advanced tracking systems assign unique identifiers (such as cookies or visitor IDs) to individual users. This enables tracking of user journeys across multiple sessions and pages. These detailed journeys can often tell a different story and provide different insights than aggregated numbers do. 

  All this collected data is transmitted from the user’s browser to a centralised tracking system, which can be a third-party web analytics tool or a self-hosted solution. The collected data is stored in databases and processed to generate meaningful insights. This process involves organising the data, aggregating metrics, and creating reports.

  Analytics tools process the collected data to generate reports and visualisations that provide insights into user behaviour. Metrics such as pageviews, bounce rates, conversion rates and user paths are analysed. Good web analytics tools are able to present these insights in a user-friendly way. Analysts and marketing professionals then use this knowledge to make informed decisions to improve the user experience (UX).

  Advanced tracking systems allow data segmentation and filtering based on various criteria, such as user demographics, traffic sources, devices and more. This enables deeper analysis of specific user groups. For example, you might find that your conversion rate is much lower when your website is viewed on a mobile device. You can then dig deeper into that segment of data to find out why and experiment with changes that might increase mobile conversions.

  3 types of website tracking and their benefits

  There are three main categories of website tracking, and they each provide different information that can be used by sales, marketing, engineering and others. Here, we cover those three types and how businesses use them to understand customers and create better experiences.

  Website analytics 

  Website analytics is all about understanding the traffic your website receives. This type of tracking allows you to learn how the website performs based on pageviews, real-time traffic, bounce rate and conversions. 

  For example, you would use website analytics to determine how effectively your homepage drives people toward a product or pricing page. You can use pageviews and previous page statistics to learn how many people who land on your homepage read your blog posts. From there, you could use web analytics to determine the conversion rate of the call to action at the end of each article.

  

  User behaviour

  While website analytics focuses on the website’s performance, user behaviour tracking is about monitoring and quantifying user behaviour. One of the most obvious aspects of user behaviour is what they click on, but there are many other actions you can track. 

  The time a user spends on a page can help you determine whether the content on the page is engaging. Some tracking tools can also measure how far down the page a user scrolls, which reveals whether some content is even being seen. 

  Session recordings are another popular tool for analysing user behaviour. They not only show concrete actions, like clicks, but can also show how the user moves throughout the page. Where do they stop ? What do they scroll right past ? This is one example of how user behaviour data can be quantitative or qualitative.

  Visitor information

  Tracking can also include gathering or uncovering information about visitors to your site. This might include demographic information, such as language and location, or details like what device a website visitor is using and on which browser they view your website. 

  This type of data helps your web and marketing teams make better decisions about how to design and format the site. If you know, for example, that the website for your business-to-business (B2B) software is overwhelmingly viewed on desktop computers, that will affect how you structure your pages and choose images. 

  Similarly, if visitor information tells you that you have a significant audience in France, your marketing team might develop new content to appeal to those potential customers.

  Use website visitor tracking to improve marketing, sales and UX 

  Website visitor tracking has various applications for different parts of your business, from marketing to sales and much more. When you understand the impact tracking has on different teams, you can better evaluate your company’s needs and build buy-in among stakeholders.

  Marketing

  At many companies, the marketing team owns and determines what kind of content is on your website. From landing pages to blog posts to the navigation bar, you want to create an experience that drives people toward making a purchase. When marketers can track website visitors, they can get a real look at how visitors respond to and engage with their marketing efforts. Pageviews, conversion rates and time spent on pages help them better understand what your customers care about and what messaging resonates.

  But web analytics can even help marketing teams better understand how their external marketing campaigns are performing. Tracking tools like Matomo reveal your most important traffic sources. The term “traffic source” refers to the content or web property from which someone arrives at your site. 

  For instance, you might notice that an older page got a big boost in traffic this month. You can then check the traffic sources, where you find that an influential LinkedIn user posted a link to the page. This presents an opportunity to adjust the influencer or social media aspects of your marketing strategy.

  

  Beyond traffic sources, Matomo can provide a visual user journey (also known as User Flow), showing which pages visitors tend to view in a session and even in what order they progress. This gives you a bird’s-eye view of the customer journey.

  Sales

  Just like your marketing team, your sales team can benefit from tracking and analysing website visitor information. Data about user behaviour and visitor demographics helps sales representatives better understand the people they’re talking to. Segmented visitor tracking data can even provide clues as to how to appeal to different buyer personas.

  Sales leadership can use web analytics to gauge interest over time, tie visitors to revenue and develop more accurate sales forecasts and goals. 

  

  And it’s not just aggregated website tracking data that your sales team can use to better serve customers. They can also use insights about an individual visitor to tailor their approach. Matomo’s Visits Log report and Visitor Profiles allow you to see which pages a prospect has viewed. This tells your sales team which products and features the prospect is most interested in, leading to more relevant interactions and more effective sales efforts.

  User experience and web development

  The way users interact with and experience your website has a big impact on their impression of your brand and, ultimately, whether they become customers. While marketing often controls much of a website’s content, the backend and technical operation of the site usually falls to a web development or engineering team. Website analytics and tracking inform their work, too.

  Along with data about website traffic and conversion rates, web development teams often monitor bounce rates (the percentage of people who leave your website entirely after landing on a page) and page load time (the time it takes for an individual web page to load for a user). Besides the fact that slow loading times inconvenience visitors, they can also negatively affect your search engine optimization (SEO).

  

  Along with session recordings, user experience teams and web developers may use heatmaps to find out what parts of a page draw a visitor’s attention and where they are most likely to convert or take some other action. They can then use these insights to make a web page more intuitive and useful.

  Visitor tracking and privacy regulations 

  There are different data privacy standards in other parts of the world, which are designed to ensure that businesses collect and use consumer data ethically. The most-discussed of these privacy standards is the General Data Protection Regulation (GDPR), which was instituted by the European Union (EU) but affects businesses worldwide. However, it’s important to note that individual countries or states can have different privacy laws.

  Many privacy laws govern how websites can use cookies to track visitors. With a user’s consent, cookies can help websites identify and remember visitors. However, many web visitors will reject cookie consent banners. When this happens, analysts and marketers can’t collect information from these visitors and have to work with incomplete tracking data. Incomplete data leads to poor decision-making. What’s more, cookie consent banners can create a poor user experience and often annoy web visitors.

  With Matomo’s industry-leading measures to protect user privacy, France’s data protection agency (CNIL) has confirmed that Matomo is exempt from tracking consent in France. Matomo users have peace of mind knowing they can uphold the GDPR and collect data without needing to collect and track cookie consent. Only in Germany and the UK are cookie consent banners still required.

  Choosing user tracking software

  The benefits and value of tracking website visitors are enormous, but not all tracking software is equal. Different tools have different core functionalities. For instance, some focus on user behaviour over traditional web analytics. Others offer detailed website performance data but offer little in the way of visitor information. It’s a good idea to start by identifying your company’s most important tracking goals.

  Along with core features, look for useful tools to experiment with and optimise your website with. For example, Matomo enables A/B testing while many other tools do not.

  

  Along with users of your website, you also need to think about the employees who will be using the tracking software. The interface can have a big impact on the value you get from a tool. Matomo’s session recording functionality, for example, not only provides you with video but with a colour-coded timeline identifying important user actions.

  

  Privacy standards and compliance should also be a part of the conversation. Different tools use different tracking methods, impacting accuracy and security and can even cause legal trouble. You should consider which data privacy laws you are subject to, as well as the privacy expectations of your users.

  

  Some industries have especially high data security standards. Government and healthcare organisations, for example, may require visitor tracking software that is hosted on their premises. While there are many purely cloud-based software-as-a-service (SaaS) tracking tools, Matomo is available both On-Premise (also known as self-hosted) and in the Cloud.

  Frequently asked questions

  Here are answers to some of people’s most common questions about tracking website visitors.

  Can you track who visited your website ?

  In most cases, tracking your website’s traffic is possible. Still, the extent of the tracking depends on the visitor-tracking technology you use and the privacy settings and precautions the visitor uses. For example, some technologies can pinpoint users by IP address. In other cases, you may only have access to anonymized data.

  Is it legal to track someone’s IP address ?

  It is legal for websites and businesses to track someone’s IP address in the sense that they can identify that someone from the same IP address is visiting a page repeatedly. Under the General Data Protection Regulation (GDPR), IP addresses are considered personally identifiable information (PII). The GDPR mandates that websites only log and store a user’s IP address with the user’s consent.

  How do you find where visitors are clicking the most ?

  Heatmap tools are among the most common tools for learning where visitors click the most on your website. Heatmaps use colour-coding to show what parts of a web page users either click on or hover over the most.

  Unique tracking URLs are another way to determine what part of your website gets the most clicks. For example, if you have three links on a page that all go to the same destination, you can use tracking links to determine how many clicks each link generates.

  Matomo also offers a Tag Manager within the platform that lets you manage and unify all your tracking and marketing tags to find out where visitors are clicking.

  What is the best tool for website visitor tracking ?

  Like most tools, the best website visitor tracking tool depends on your needs. Each tool offers different functionalities, user interfaces and different levels of accuracy and privacy. Matomo is a good choice for companies that value privacy, compliance and accuracy.

  Tracking for powerful insights and better performance

  Tracking website visitors is now a well-ingrained part of business operations. From sales reps seeking to understand their leads to marketers honing their ad spend, tracking helps teams do their jobs better.

  Take the time to consider what you want to learn from website tracking and let those priorities guide your choice of visitor tracking software. Whatever your industry or needs, user privacy and compliance must be a priority.

  Find out how much detail and insight Matomo can give you with our free 21-day trial — no credit card required.

• 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.