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• 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.

  

  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. 

  

  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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  

  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.

  

  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.

  3. 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.

  

  4. 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.

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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.

  Try Matomo for Free

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• 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.

  

  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.

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  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 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.

  

  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 :

  

  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

  2. Split your audience into two groups :

  1. • Control group (60% of the segment)
     • Test group (40% of the segment)

  3. Target the control group with your marketing tactic (the simpler the tactic, the better).

  4. Target the test group with a different marketing tactic.

  5. 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.

  6. 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.

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  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 :

  

  • • 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.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• A Beginner’s Guide to Omnichannel Analytics

  14 avril 2024, par Erin

  Linear customer journeys are as obsolete as dial-up internet and floppy disks. As a marketing manager, you know better than anyone that customers interact with your brand hundreds of times across dozens of channels before purchasing. That can make tracking them a nightmare unless you build an omnichannel analytics solution. 

  Alas, if only it were that simple. 

  Unfortunately, it’s not enough to collect data on your customers’ complex journeys just by buying an omnichannel platform. You need to generate actionable insights by using marketing attribution to tie channels to conversions. 

  This article will explain how to build a useful omnichannel analytics solution that lets you understand and improve the customer journey.

  What is omnichannel analytics ?

  Omnichannel analytics collects and analyses customer data from every touchpoint and device. The goal is to collect all this omnichannel data in one place, creating a single, real-time, unified view of your customer’s journey.

  

  Unfortunately, most businesses haven’t achieved this yet. As Karen Lellouche Tordjman and Marco Bertini say :

  “Despite all the buzz around the concept of omnichannel, most companies still view customer journeys as a linear sequence of standardised touchpoints within a given channel. But the future of customer engagement transforms touchpoints from nodes along a predefined distribution path to full-blown portals that can serve as points of sale or pathways to many other digital and virtual interactions. They link to chatbots, kiosks, robo-advisors, and other tools that customers — especially younger ones — want to engage with.”

  However, doing so is more important than ever — especially when consumers have over 300 digital touchpoints, and the average number of touchpoints in the B2B buyer journey is 27.

  Not only that, but customers expect personalised experiences across every platform — that’s the kind you can only create when you have access to omnichannel data.

  

  What might omnichannel analytics look like in practice for an e-commerce store ?

  An online store would integrate data from channels like its website, mobile app, social media accounts, Google Ads and customer service records. This would show how customers find its brand, how they use each channel to interact with it and which channels convert the most customers. 

  This would allow the e-commerce store to tailor marketing channels to customers’ needs. For instance, they could focus social media use on product discovery and customer support. Google Ads campaigns could target the best-converting products. While all this is happening, the store could also ensure every channel looks the same and delivers the same experience. 

  What are the benefits of omnichannel analytics ?

  Why go to all the trouble of creating a comprehensive view of the customer’s experience ? Because you stand to gain some pretty significant benefits when implementing omnichannel analytics.

  

  Understand the customer journey

  You want to understand how your customers behave, right ? No other method will allow you to fully understand your customer journey the way omnichannel analytics does. 

  It doesn’t matter how customers engage with your brand — whether that’s your website, app, social media profiles or physical stores — omnichannel analytics capture every interaction.

  With this 360-degree view of your customers, it’s easy to understand how they move between channels, where they encounter issues and what bottlenecks prevent them from converting. 

  Deliver better personalisation

  We don’t have to tell you that personalisation matters. But do you know just how important it is ? Since 56% of customers will become repeat buyers after a personalised experience, delivering them as often as possible is critical. 

  Omnichannel analytics helps in your quest for personalisation by highlighting the individual preferences of customer segments. For example, e-commerce stores can use omnichannel analytics to understand how shoppers behave across different devices and tailor their offers accordingly. 

  Upgrade the customer experience

  Omnichannel analytics gives you the insights to improve every aspect of the customer experience. 

  For starters, you can ensure a consistent brand experience across all your top channels by making sure they look and behave the same.

  Then, you can use omnichannel insights to tailor each channel to your customers’ requirements. For example, most people interacting with your brand on social media may seek support. Knowing that you can create dedicated support accounts to assist users. 

  Improve marketing campaigns

  Which marketing campaigns or traffic sources convert the most customers ? How can you improve these campaigns ? Omnichannel analytics has the answers. 

  When you implement omnichannel analytics you automatically track the performance of every marketing channel by attributing each conversion to one or more traffic sources. This lets you see whether Google Ads bring in more customers than your SEO efforts. Or whether social media ads are the most profitable acquisition channel. 

  Armed with this information, you can improve your marketing efforts — either by focusing on your profitable channels or rectifying problems that stop less profitable channels from converting.

  What are the challenges of omnichannel analytics ?

  There are three challenges when implementing an omnichannel analytics solution :

  

  • Complex customer journeys : Customer journeys aren’t linear and can be incredibly difficult to track. 
  • Regulatory and privacy issues : When you start gathering customer data, you quickly come up against consumer privacy laws. 
  • No underlying goal : There has to be a reason to go to all this effort, but brands don’t always have goals in mind before they start. 

  You can’t do anything about the first challenge. 

  After all, your customer journey will almost never be linear. And isn’t the point of implementing an omnichannel solution to understand these complex journeys in the first place ? Once you set up omnichannel analytics, these journeys will be much easier to decipher. 

  As for the other two :

  Using the right software that respects user privacy and complies with all major privacy laws will avoid regulatory issues. Take Matomo, for instance. Our software was designed with privacy in mind and is configured to follow the strictest privacy laws, such as GDPR. 

  Tying omnichannel analytics to marketing attribution will solve the final challenge by giving your omnichannel efforts a goal. When you tie omnichannel analytics to your marketing efforts, you aren’t just getting a 360-degree view of your customer journey for the sake of it. You are getting that view to improve your marketing efforts and increase sales.

  Try Matomo for Free

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

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  How to set up an omnichannel analytics solution

  Want to set up a seamless analytical environment that incorporates data from every possible source ? Follow these five steps :

  Choose one or more analytics providers

  You can use several tools to build an omnichannel analytics solution. These include web and app analytics tools, customer data platforms that centralise first-party data and business intelligence tools (typically used for visualisation). 

  Which tools you use will depend on your goals and your budget — the loftier your ambitions and the higher your budget, the more tools you can use. 

  Ideally, you should use as few tools as possible to capture your data. Most teams won’t need business intelligence platforms, for example. However, you may or may not need both an analytics platform and a customer data platform. Your decision will depend on how many channels your customers use and how well your analytics tool tracks everything.

  If it can capture web and app usage while integrating with third-party platforms like your back-end e-commerce platform, then it’s probably enough.

  Collect accurate data at every touchpoint 

  Your omnichannel analytics efforts hinge on the quantity and quality of data you can collect. You want to gather data from every touchpoint possible and store that data in as few places as possible. That’s why choosing as few tools as possible in the step above is so important. 

  So, where should you start ? Common data sources include :

  • Your website
  • Apps (iOS and Android)
  • Social media profiles
  • ERPs
  • PoS systems

  At the same time, make sure you’re tracking all relevant metrics. Revenue, customer engagement and conversion-focused metrics like conversion rate, dwell time, cart abandonment rate and churn rate are particularly important. 

  Set up marketing attribution

  Setting up marketing attribution (also known as multi-touch attribution) is essential to tie omnichannel data to business goals. It’s the only way to know exactly how valuable each marketing channel is and where each customer comes from. 

  You’ll want to use multi-touch attribution, given you have data from across the customer journey.

  

  Multi-touch attribution models can include (but are not limited to) :

  • Linear : where each touchpoint is given equal weighting
  • Time decay : where touchpoints are more valuable the nearer they are to conversion
  • Position-based : where the first and last touch points are more valuable than all the others. 

  You don’t have to use just one of the models above, however. One of the benefits of using a web analytics tool like Matomo is that you can choose between different attribution models and compare them.

  Try Matomo for Free

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

  Start for free

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  Create reports that help you visualise data

  Dashboards are your friend here. They’ll let you see KPIs at a glance, allowing you to keep track of day-to-day changes in your customer journey. Ideally, you’ll want a platform that lets you customise dashboard widgets so only relevant KPIs are shown. 

  

  Setting up standard and custom reports is also important. Custom reports allow you to choose metrics and dimensions that align with your goals. They will also allow you to present your data most meaningfully to your team, increasing the likelihood they act upon insights. 

  Analyse data and take action

  Now that you have customer journey data at your fingertips, it’s time to analyse it. After all, there’s no point in implementing an omnichannel analytics solution if you aren’t going to take action. 

  If you’re unsure where to start, re-read the benefits we listed at the start of this article. You could use your omnichannel insights to improve your marketing campaigns by doubling down on the channels that bring in the best customers.

  Or you could identify (and fix) bottlenecks in the customer journey so customers are less likely to fall out of your funnel between certain channels. 

  Just make sure you take action based on your data alone.

  Make the most of omnichannel analytics with Matomo

  A comprehensive web and app analytics platform is vital to any omnichannel analytics strategy. 

  But not just any solution will do. When privacy regulations impede an omnichannel analytics solution, you need a platform to capture accurate data without breaking privacy laws or your users’ trust. 

  That’s where Matomo comes in. Our privacy-friendly web analytics platform ensures accurate tracking of web traffic while keeping you compliant with even the strictest regulations. Moreover, our range of APIs and SDKs makes it easy to track interactions from all your digital products (website, apps, e-commerce back-ends, etc.) in one place. 

  Try Matomo for free for 21 days. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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