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  • GA360 vs GA4 : Key Differences and Challenges

    20 mai 2024, par Erin

    While the standard Universal Analytics (UA) was sunset for free users in July 2023, Google Analytics 360 (GA360) users could postpone the switch to GA4 for another 12 months. But time is running out. As July is rapidly approaching, GA360 customers need to prepare for the switch to Google Analytics 4 (GA4) or another solution. 

    This comparison post will help you understand the differences between GA360 vs. GA4. We’ll dive beneath the surface, examining each solution’s privacy implications and their usability, features, new metrics and measurement methods.

    What is Google Analytics 4 (Standard) ?

    GA4 is the latest version of Google Analytics, succeeding Universal Analytics. It was designed to address privacy issues with Universal Analytics, which made compliance with privacy regulations like GDPR difficult.

    It completely replaced Universal Analytics for free users in July 2023. GA4 Standard features many differences from the original UA, including :

    • Tracking and analysis are now events-based.
    • Insights are primarily powered by machine learning. (There are fewer reports and manual analysis tools).
    • Many users find the user interface to be too complex compared to Universal Analytics.

    The new tracking, reports and metrics already make GA4 feel like a completely different web analytics platform. The user interface itself also includes notable changes in navigation and implementation. These changes make the transition hard for experienced analysts and digital marketers alike. 

    For a more in-depth look at the differences, read our comparison of Google Analytics 4 and Universal Analytics.

    What is Google Analytics 360

    Google Analytics 360 is a paid version of Google Analytics, mostly aimed at enterprises that need to analyse a large amount of data.

    It significantly increases standard limits on data collection, sampling and processing. It also improves data granularity with more custom events and dimensions.

    Transitioning from Universal Analytics 360 to GA4 360

    You may still use the Universal Analytics tag and interface if you’ve been a Google Analytics 360 customer for multiple years. However, access to Universal Analytics 360 will be discontinued on July 1, 2024. Unlike the initial UA sunset (free version), you won’t be able to access the interface or your data after that, so it will be deleted.

    That means you will have to adapt to the new GA4 user interface, reports and metrics before the sunset or find an alternative solution.

    What is the difference between GA4 360 and free GA4 ?

    The key differences between GA4 360 and free GA4 are higher data limits, enterprise support, uptime guarantees and more robust administrative controls.

    Diagram of the key differences between GA360 and GA4

    GA4 offers most of the same features across the paid and free versions, but there are certain limits on data sampling, data processing and integrations. With the free version, you also can’t define as detailed events using event parameters as you can with GA4 360.

    Higher data collection, accuracy, storage and processing limits

    The biggest difference that GA4 360 brings to the table is more oomph in data collection, accuracy and analysis.

    You can collect more specific data (with 100 event parameters instead of 25 for custom metrics). GA4 360 lets you divide users using more custom dimensions based on events or user characteristics. Instead of 50 per property, you get up to 125 per property.

    And with up to 400 custom audiences, 360 is better for companies that heavily segment their users. More audiences, events and metrics per property mean more detailed insights.

    Sampling limits are also of a completely different scale. The max sample size in GA4 360 is 100x the free version of GA4, with up to 1 billion events per query. This makes analysis a lot more accurate for high-volume users. A slice of 10 million events is hardly representative if you have 200 million monthly events.

    Finally, GA4 360 lets you store all of that data for longer (up to 50 months vs up to 14 months). While new privacy regulations demand that you store user data only for the shortest time possible, website analytics data is often used for year-over-year analysis.

    Enterprise-grade support and uptime guarantees

    Because GA360 users are generally enterprises, Google offers service-level agreements for uptime and technical support response times.

    • Tracking : 99.9% uptime guarantee
    • Reporting : 99% uptime guarantee
    • Data processing : within 4 hours at a 98% uptime guarantee

    The free version of GA4 includes no such guarantees and limited access to professional support in the first place.

    Integrations

    GA4 360 increases limits for BigQuery and Google Ads Manager exports.

    Table showing integration differences between GA4 and Analytics 360

    The standard limits in the free version are 1 million events per day to BigQuery. In GA4 360, this is increased to billions of events per day. You also get up to 400 audiences for Search Ads 360 instead of the 100 limit in standard GA4.

    Roll-up analytics for agencies and enterprises

    If you manage a wide range of digital properties, checking each one separately isn’t very effective. You can export the data into a tool like Looker Studio (formerly Google Data Studio), but this requires extra work.

    With GA360, you can create “roll-up properties” to analyse data from multiple properties in the same space. It’s the best way to analyse larger trends and patterns across sites and apps.

    Administration and user access controls

    Beyond roll-up reporting, the other unique “advanced features” found in GA360 are related to administration and user access controls.

    Table Showing administrative feature differences between GA4 and Analytics 360

    First, GA360 lets you create custom user roles, giving different access levels to different properties. Sub-properties and roll-up properties are also useful tools for data governance purposes. They make it easier to limit access for specific analysts to the area they’re directly working on.

    You can also design custom reports for specific roles and employees based on their access levels.

    Pricing 

    While GA4 is free, Google Analytics 360 is priced based on your traffic volume. 

    With the introduction of GA4, Google implemented a revised pricing model. For GA4 360, pricing typically begins at USD $50,000/year which covers up to 25 million events per month. Beyond this limit, costs increase based on data usage, scaling accordingly.

    What’s not different : the interface, metrics, reports and basic features

    GA4 360 is the same analytics tool as the free version of GA4, with higher usage limits and a few enterprise features. You get more advanced tracking capabilities and more accurate analysis in the same GA4 packaging.

    If you already use and love GA4 but need to process more data, that’s great news. But if you’re using UA 360 and are hesitant to switch to the new interface, not so much. 

    Making the transition from UA to GA4 isn’t easy. Transferring the data means you need to figure out how to work with the API or use Google BigQuery.

    Plus, you have to deal with new metrics, reports and a new interface. For example, you don’t get to keep your custom funnel reports. You need to use “funnel explorations.”

    Going from UA to GA4 can feel like starting from scratch in a completely new web analytics tool.

    Which version of Google Analytics 4 is right for you ?

    Standard GA4 is a cost-effective web analytics option, but it’s not without its problems :

    • If you’re used to the UA interface, it feels clunky and difficult to analyse.
    • Data sampling is prevalent in the free version, leading to inaccuracies that can negatively affect decision-making and performance.

    And that’s just scratching the surface of common GA4 issues.

    Google Analytics 4 360 is a more reliable web analytics solution for enterprises. However, it suffers from many issues that made the GA4 transition painful for many free UA users last year.

    • You need to rebuild reports and adjust to the new complex interface.
    • To transfer historical data, you must use spreadsheets, the API, or BigQuery.

    You will still lose some of the data due to changes to the metrics and reporting.

    What if neither option is right for you ? Key considerations for choosing a Google Analytics alternative

    Despite what Google would like you to think, GA4 isn’t the only option for website analytics in 2024 — far from it. For companies that are used to UA 360, the right alternative can offer unique benefits to your company.

    Privacy regulations and future-proofing your analytics and marketing

    Although less flagrant than UA, GA4 is still in murky waters regarding compliance with GDPR and other privacy regulations. 

    And the issue isn’t just that you can get fined (which is bad enough). As part of a ruling, you may be ordered to change your analytics platform and protocol, which can completely disrupt your marketing workflow.

    When most marketing teams rely on web analytics to judge the ROI of their campaigns, this can be catastrophic. You may even have to pause campaigns as your team makes the adjustments.

    Avoid this risk completely by going with a privacy-friendly alternative.

    Features beyond basic web analytics

    To understand your users, you need to look at more than just events and conversions.

    That’s why some web analytics solutions have built-in behavioural analytics tools. Features like heatmaps (a visual pattern of popular clicks, scrolling and cursor movement) can help you understand how users interact with specific pages.

    Matomo's heatmaps feature

    Matomo allows you to consolidate behavioural analytics and regular web analytics into a single platform. You don’t need separate tools and subscriptions for heatmaps, session recordings, from analytics, media analytics and A/B testing. You can do all of this with Matomo.

    With insights about visits, sales, conversions, and usability in the same place, it’s a lot easier to improve your website.

    Try Matomo for Free

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

    Start for free

    No credit card required

    Usability and familiar metrics

    The move to event tracking means new metrics, reports and tools. So, if you’re used to Universal Analytics, it can be tricky to transition to GA4. 

    But there’s no need to start from zero, learning to work with a brand-new interface. Many competing web analytics platforms offer familiar reports and metrics — ones your team has gotten used to. This will help you speed up the time to value with a shorter learning curve.

    Why Matomo is a better option than GA4 360 for UA 360 users

    Matomo offers privacy-friendly tracking, built from the ground up to comply with regulations — including IP anonymisation and DoNotTrack settings. You also get 100% ownership of the data, which means we will never use your data for our own profit (unlike Google and other data giants).

    This is a big deal, as breaking GDPR rules can lead to fines of up to 4% of your annual revenue. At the same time, you’ll also future-proof your marketing workflow by choosing a web analytics provider built with privacy regulations in mind.

    Plus, for legacy UA 360 users, the Matomo interface will also feel a lot more intuitive and familiar. Matomo also provides marketing attribution models you know, like first click, which GA4 has removed.

    Finally, you can access various behavioural analytics tools in a single platform — heatmaps, session recordings, form analytics, A/B testing and more. That means you don’t need to pay for separate solutions for conversion rate optimisation efforts.

    And the transition is smooth. Matomo lets you import Universal Analytics data and offers ready-made Google Ads integration and Looker Studio Connector.

    Join over 1 million websites that choose Matomo as their web analytics solution. Try it free for a 21-days. No credit card required.

  • A Complete Guide to Metrics in Google Analytics

    11 janvier 2024, par Erin

    There’s no denying that Google Analytics is the most popular web analytics solution today. Many marketers choose it to understand user behaviour. But when it offers so many different types of metrics, it can be overwhelming to choose which ones to focus on. In this article, we’ll dive into how metrics work in Google Analytics 4 and how to decide which metrics may be most useful to you, depending on your analytics needs.

    However, there are alternative web analytics solutions that can provide more accurate data and supplement GA’s existing features. Keep reading to learn how to overcome Google Analytics limitations so you can get the more out of your web analytics.

    What is a metric in Google Analytics ?

    In Google Analytics, a metric is a quantitative measurement or numerical data that provides insights into specific aspects of user behaviour. Metrics represent the counts or sums of user interactions, events or other data points. You can use GA metrics to better understand how people engage with a website or mobile app. 

    Unlike the previous Universal Analytics (the previous version of GA), GA4 is event-centric and has automated and simplified the event tracking process. Compared to Universal Analytics, GA4 is more user-centric and lets you hone in on individual user journeys. Some examples of common key metrics in GA4 are : 

    • Sessions : A group of user interactions on your website that occur within a specific time period. A session concludes when there is no user activity for 30 minutes.
    • Total Users : The cumulative count of individuals who accessed your site within a specified date range.
    • Engagement Rate : The percentage of visits to your website or app that included engagement (e.g., one more pageview, one or more conversion, etc.), determined by dividing engaged sessions by sessions.
    Main overview dashboard in GA4 displaying metrics

    Metrics are invaluable when it comes to website and conversion optimisation. Whether you’re on the marketing team, creating content or designing web pages, understanding how your users interact with your digital platforms is essential.

    GA4 metrics vs. dimensions

    GA4 uses metrics to discuss quantitative measurements and dimensions as qualitative descriptors that provide additional context to metrics. To make things crystal clear, here are some examples of how metrics and dimensions are used together : 

    • “Session duration” = metric, “device type” = dimension 
      • In this situation, the dimension can segment the data by device type so you can optimise the user experience for different devices.
    • “Bounce rate” = metric, “traffic source/medium” = dimension 
      • Here, the dimension helps you segment by traffic source to understand how different acquisition channels are performing. 
    • “Conversion rate” = metric, “Landing page” = dimension 
      • When the conversion rate data is segmented by landing page, you can better see the most effective landing pages. 

    You can get into the nitty gritty of granular analysis by combining metrics and dimensions to better understand specific user interactions.

    How do Google Analytics metrics work ?

    Before diving into the most important metrics you should track, let’s review how metrics in GA4 work. 

    GA4 overview dashboard of engagement metrics
    1. Tracking code implementation

    The process begins with implementing Google Analytics 4 tracking code into the HTML of web pages. This tracking code is JavaScript added to each website page — it collects data related to user interactions, events and other important tidbits.

    1. Data collection

    As users interact with the website or app, the Google Analytics 4 tracking code captures various data points (i.e., page views, clicks, form submissions, custom events, etc.). This raw data is compiled and sent to Google Analytics servers for processing.

    1. Data processing algorithms

    When the data reaches Google Analytics servers, data processing algorithms come into play. These algorithms analyse the incoming raw data to identify the dataset’s trends, relationships and patterns. This part of the process involves cleaning and organising the data.

    1. Segmentation and customisation

    As discussed in the previous section, Google Analytics 4 allows for segmentation and customisation of data with dimensions. To analyse specific data groups, you can define segments based on various dimensions (e.g., traffic source, device type). Custom events and user properties can also be defined to tailor the tracking to the unique needs of your website or app.

    1. Report generation

    Google Analytics 4 can make comprehensive reports and dashboards based on the processed and segmented data. These reports, often in the form of graphs and charts, help identify patterns and trends in the data.

    What are the most important Google Analytics metrics to track ? 

    In this section, we’ll identify and define key metrics for marketing teams to track in Google Analytics 4. 

    1. Pageviews are the total number of times a specific page or screen on your website or app is viewed by visitors. Pageviews are calculated each time a web page is loaded or reloaded in a browser. You can use this metric to measure the popularity of certain content on your website and what users are interested in. 
    2. Event tracking monitors user interactions with content on a website or app (i.e., clicks, downloads, video views, etc.). Event tracking provides detailed insights into user engagement so you can better understand how users interact with dynamic content. 
    3. Retention rate can be analysed with a pre-made overview report that Google Analytics 4 provides. This user metric measures the percentage of visitors who return to your website or app after their first visit within a specific time period. Retention rate = (users with subsequent visits / total users in the initial cohort) x 100. Use this information to understand how relevant or effective your content, user experience and marketing efforts are in retaining visitors. You probably have more loyal/returning buyers if you have a high retention rate. 
    4. Average session duration calculates the average time users spend on your website or app per session. Average session duration = total duration of all sessions / # of sessions. A high average session duration indicates how interested and engaged users are with your content. 
    5. Site searches and search queries on your website are automatically tracked by Google Analytics 4. These metrics include search terms, number of searches and user engagement post-search. You can use site search metrics to better understand user intent and refine content based on users’ searches. 
    6. Entrance and exit pages show where users first enter and leave your site. This metric is calculated by the percentage of sessions that start or end on a specific page. Knowing where users are entering and leaving your site can help identify places for content optimisation. 
    7. Device and browser info includes data about which devices and browsers websites or apps visitors use. This is another metric that Google Analytics 4 automatically collects and categorises during user sessions. You can use this data to improve the user experience on relevant devices and browsers. 
    8. Bounce rate is the percentage of single-page sessions where users leave your site or app without interacting further. Bounce rate = (# of single-page sessions / total # of sessions) x 100. Bounce rate is useful for determining how effective your landing pages are — pages with high bounce rates can be tweaked and optimised to enhance user engagement.

    Examples of how Matomo can elevate your web analytics

    Although Google Analytics is a powerful tool for understanding user behaviour, it also has privacy concerns, limitations and a list of issues. Another web analytics solution like Matomo can help fill those gaps so you can get the most out of your analytics.

    Examples of how Matomo and GA4 can elevate each other
    1. Cross-verify and validate your observations from Google Analytics by comparing data from Matomo’s Heatmaps and Session Recordings for the same pages. This process grants you access to these advanced features that GA4 does not offer.
    Matomo's heatmaps feature
    1. Matomo provides you with greater accuracy thanks to its privacy-friendly design. Unlike GA4, Matomo can be configured to operate without cookies. This means increased accuracy without intrusive cookie consent screens interrupting the user experience. It’s a win for you and for your users. Matomo also doesn’t apply data sampling so you can rest assured that the data you see is 100% accurate.
    1. Unlike GA4, Matomo offers direct access to customer support so you can save time sifting through community forum threads and online documentation. Gain personalised assistance and guidance for your analytics questions, and resolve issues efficiently.
    Screenshot of the Form Analytics Dashboard, showing data and insights on form usage and performance
    1. Matomo’s Form Analytics and Media Analytics extend your analytics capabilities beyond just pageviews and event tracking.

      Tracking user interactions with forms can tell you which fields users struggle with, common drop-off points, in addition to which parts of the form successfully guide visitors towards submission.

      See first-hand how Concrete CMS 3x their leads using Matomo’s Form Analytics.

      Media Analytics can provide insight into how users interact with image, video, or audio content on your website. You can use this feature to assess the relevance and popularity of specific content by knowing what your audience is engaged by.

    Try Matomo for Free

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

    Start for free

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    Final thoughts

    Although Google Analytics is a powerful tool on its own, Matomo can elevate your web analytics by offering advanced features, data accuracy and a privacy-friendly design. Don’t play a guessing game with your data — Matomo provides 100% accurate data so you don’t have to rely on AI or machine learning to fill in the gaps. Matomo can be configured cookieless which also provides you with more accurate data and a better user experience. 

    Lastly, Matomo is fully compliant with some of the world’s strictest privacy regulations like GPDR. You won’t have to sacrifice compliance for accurate, high quality data. 

    Start your 21-day free trial of Matomo — no credit card required.

  • What Is Incrementality & Why Is It Important in Marketing ?

    26 mars 2024, par Erin

    Imagine this : you just launched your latest campaign and it was a major success.

    You blew last month’s results out of the water.

    You combined a variety of tactics, channels and ad creatives to make it work.

    Now, it’s time to build the next campaign.

    The only issue ?

    You don’t know what made it successful or how much your recent efforts impacted the results.

    You’ve been building your brand for years. You’ve built up a variety of marketing pillars that are working for you. So, how do you know how much of your campaign is from years of effort or a new tactic you just implemented ?

    The key is incrementality.

    This is a way to properly attribute the right weight to your marketing tactics.

    In this article, we break down what incrementality is in marketing, how it differs from traditional attribution and how you can calculate and track it to grow your business.

    What is incrementality in marketing ?

    Incrementality in marketing is growth that can be directly credited to a marketing effort above and beyond the success of the branding.

    It looks at how much a specific tactic positively impacted a campaign on top of overall branding and marketing strategies.

    What is incrementally in marketing?

    For example, this could be how much a specific tactic, campaign or channel helped increase conversions, email sign-ups or organic traffic.

    The primary purpose of incrementally in marketing is to more accurately determine the impact a single marketing variable had on the success of a project.

    It removes every other factor and isolates the specific method to help marketers double down on that strategy or move on to new tactics.

    With Matomo, you can track conversions simply. With our last non-direct channel attribution system, you’ll be able to quickly see what channels are converting (and which aren’t) so you can gain insights into incrementality. 

    See why over 1 million websites choose Matomo today.

    Try Matomo for Free

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

    Start for free

    No credit card required

    How incrementality differs from attribution

    In marketing and advertising, it’s crucial to understand what tactics and activities drive growth.

    Incrementality and attribution help marketers and business owners understand what efforts impact their results.

    But they’re not the same.

    Here’s how they differ :

    Incrementality vs. attribution

    Incrementality explained

    Incrementality measures how much a specific marketing campaign or activity drives additional sales or growth.

    Simply put, it’s analysing the difference between having never implemented the campaign (or tactic or channel) in the first place versus the impact of the activity.

    In other words, how much revenue would you have generated this month without campaign A ?

    And how much additional revenue did you generate directly due to campaign A ?

    The reality is that dozens of factors impact revenue and growth.

    You aren’t just pouring your marketing into one specific channel or campaign at a time.

    Chances are, you’ve got your hands on several marketing initiatives like SEO, PPC, organic social media, paid search, email marketing and more.

    Beyond that, you’ve built a brand with a not-so-tangible impact on your recurring revenue.

    So, the question is, if you took away your new campaign, would you still be generating the same amount of revenue ?

    And, if you add in that campaign, how much additional revenue and growth did it directly create ?

    That is incrementality. It’s how much a campaign went above and beyond to add new revenue that wouldn’t have been there otherwise.

    So, how does attribution play into all of this ?

    Attribution explained

    Attribution is simply the process of assigning credit for a conversion to a particular marketing touchpoint.

    While incrementality is about narrowing down the overall revenue impact from a particular campaign, attribution seeks to point to a specific channel to attribute a sale.

    For example, in any given marketing campaign, you have a few marketing tactics.

    Let’s say you’re launching a limited-time product.

    You might have :

    • Paid ads via Facebook and Instagram
    • A blog post sharing how the product works
    • Organic social media posts on Instagram and TikTok
    • Email waitlist campaign building excitement around the upcoming product
    • SMS campaigns to share a limited-time discount

    So, when the time comes for the sale launch, and you generate $30,000 in revenue, what channel gets the credit ?

    Do you give credit to the paid ads on Facebook ? What about Instagram ? They got people to follow you and got them on the email waitlist.

    Do you give credit to email for reminding people of the upcoming sale ? What about your social media posts that reminded people there ?

    Or do you credit your SMS campaign that shared a limited-time discount ?

    Which channel is responsible for the sale ?

    This is what attribution is all about.

    It’s about giving credit where credit is due.

    The reason you want to attribute credit ? So you know what’s working and can double down your efforts on the high-impact marketing activities and channels.

    Leveraging incrementality and attribution together

    Incrementality and attribution aren’t competing methods of analysing what’s working.

    They’re complementary to one another and go hand in hand.

    You can (and should) use attribution and incrementality in your marketing to help understand what activities, campaigns and channels are making the biggest incremental impact on your business growth.

    Why it’s important to measure incrementality

    Incrementality is crucial to measure if you want to pour your time, money and effort into the right marketing channels and tactics.

    Here are a few reasons why you need to measure incrementality if you want to be successful with your marketing and grow your business :

    1. Accurate data

    If you want to be an effective marketer, you need to be accurate.

    You can’t blindly start marketing campaigns in hopes that you will sell many products or services.

    That’s not how it works.

    Sure, you’ll probably make some sales here and there. But to truly be effective with your work, you must measure your activities and channels correctly.

    Incrementality helps you see how each channel, tactic or campaign made a difference in your marketing.

    Matomo gives you 100% accurate data on your website activities. Unlike Google Analytics, we don’t use data sampling which limits how much data is analysed.

    Screenshot example of the Matomo dashboard

    2. Helps you to best determine the right tactics for success

    How can you plan your marketing strategy if you don’t know what’s working ?

    Think about it.

    You’ll be blindly sailing the seas without a compass telling you where to go.

    Measuring incrementality in your marketing tactics and channels helps you understand the best tactics.

    It shows you what’s moving the needle (and what’s not).

    Once you can see the most impactful tactics and channels, you can forge future campaigns that you know will work.

    3. Allows you to get the most out of your marketing budget

    Since incrementality sheds light on what’s moving your business forward, you can confidently implement your efforts on the right tactics and channels.

    Guess what happens when you start doubling down on the most impactful activities ?

    You start increasing revenue, decreasing ad spend and getting a higher return on investment.

    The result is that you will get more out of your marketing budget.

    Not only will you boost revenue, but you’ll also be able to boost profit margins since you’re not wasting money on ineffective tactics.

    4. Increase traffic

    When you see what’s truly working in your business, you can figure out what channels and tactics you should be working.

    Incrementality helps you understand not only what your best revenue tactics are but also what channels and campaigns are bringing in the most traffic.

    When you can increase traffic, you can increase your overall marketing impact.

    5. Increase revenue

    Finally, with increased traffic, the inevitable result is more conversions.

    More conversions mean more revenue.

    Incrementality gives you a vision of the tactics and channels that are converting the best.

    If you can see that your SMS campaigns are driving the best ROI, then you know that you’ll grow your revenue by pouring more into acquiring SMS leads.

    By calculating incrementality regularly, you can rest assured that you’re only investing time and money into the most impactful activities in terms of revenue generation.

    How to calculate and test incrementality in marketing

    Now that you understand how incrementality works and why it’s important to calculate, the question is : 

    How do you calculate and conduct incrementality tests ?

    Given the ever-changing marketing landscape, it’s crucial to understand how to calculate and test incrementally in your business.

    If you’re not sure how incrementality testing works, then follow these simple steps :

    How to test and analyze incrementality in marketing?

    Your first step to get an incrementality measurement is to conduct what’s referred to as a “holdout test.”

    It’s not a robust test, but it’s an easy way to get the ball rolling with incrementality.

    Here’s how it works :

    1. Choose your target audience.

    With Matomo’s segmentation feature, you can get pretty specific with your target audience, such as :

      • Visitors from the UK
      • Returning visitors
      • Mobile users
      • Visitors who clicked on a specific ad
    1. Split your audience into two groups :
      • Control group (60% of the segment)
      • Test group (40% of the segment)
    1. Target the control group with your marketing tactic (the simpler the tactic, the better).
    1. Target the test group with a different marketing tactic.
    1. Analyse the results. The difference between the control and test groups is the incremental lift in results. The new marketing tactic is either more effective or not.
    1. Repeat the test with a new control group (with an updated tactic) and a new test group (with a new tactic).

    Matomo can help you analyse the results of your campaigns in our Goals feature. Set up business objectives so you can easily track different goals like conversions.

    Try Matomo for Free

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

    Start for free

    No credit card required

    Here’s an example of how this incrementality testing could look in real life.

    Imagine a fitness retailer wants to start showing Facebook ads in their marketing mix.

    The marketing manager decided to conduct a holdout test. If we match our example below with the steps above, this is how the holdout test might look.

    1. They choose people who’ve purchased free weights in the past as their target audience (see how that segmentation works ?).
    2. They split this segment into a control group and a test group.
    3. For this test, they direct their regular marketing campaign to the control group (60% of the segment). The campaign includes promoting a 20% off sale on organic social media posts, email marketing, and SMS.
    4. They direct their regular marketing campaign plus Facebook ads to the test group (40% of the segment).
    5. They ran the campaign for three weeks with the goal for sale conversions and noticed :
      • The control group had a 1.5% conversion rate.
      • The test group (with Facebook ads) had a 2.1% conversion rate.
      • In this scenario, they could see the group who saw the Facebook ads convert better.
      • They created the following formula to measure the incremental lift of the Facebook ads :
    Calculation: Incrementality in marketing.
      • Here’s how the calculation works out : (2.1% – 1.5%) / 1.5% = 40%

    The Facebook ads had a positive 40% incremental lift in conversions during the sale.

    Incrementality testing isn’t a one-and-done process, though.

    While this first test is a great sign for the marketing manager, it doesn’t mean they should immediately throw all their money into Facebook ads.

    They should continue conducting tests to verify the initial test.

    Use Matomo to track incrementality today

    Incrementality can give you insights into exactly what’s working in your marketing (and what’s not) so you can design proven strategies to grow your business.

    If you want more help tracking your marketing efforts, try Matomo today.

    Our web analytics and behaviour analytics platform gives you firsthand data on your website visitors you can use to craft effective marketing strategies.

    Matomo provides 100% accurate data. Unlike other major web analytics platforms, we don’t do data sampling. What you see is what’s really going on in your website. That way, you can make more informed decisions for better results.

    At Matomo, we take privacy very seriously and include several advanced privacy protections to ensure you are in full control.

    As a fully compliant web analytics solution, we’re fully compliant with some of the world’s strictest privacy regulations like GDPR. With Matomo, you get peace of mind knowing you can make data-driven decisions while also being compliant. 

    If you’re ready to launch a data-driven marketing strategy today and grow your business, get started with our 21-day free trial now. No credit card required.

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