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• What is Funnel Analysis ? A Complete Guide for Quick Results

  25 janvier 2024, par Erin

  Your funnel is leaking.

  You’re losing visitors.

  You’re losing conversions and sales.

  But you don’t know how it’s happening, where it’s happening, or what to do about it.

  The reason ? You aren’t properly analysing your funnels.

  If you want to improve conversions and grow your business, you need to understand how to properly assess your sales funnels to set yourself up for success.

  In this guide, we’ll show you what funnel analysis is, why it’s important, and what steps you need to take to leverage it to improve conversions.

  What is funnel analysis ?

  Every business uses sales funnels, whether they know it or not.

  But most people aren’t analysing them, costing them conversions.

  

  Funnel analysis is a marketing method to analyse the events leading to specific conversion points. 

  It aims to look at the entire journey of potential customers from the moment they first touch base with your website or business to the moment they click “buy.”

  It’s assessing what your audience is doing at every step of the journey.

  By assessing what actions are taking place at scale, you can see where you’re falling short in your sales funnel.

  You’ll see :

  1. Where prospects are falling off.
  2. Where people are converting well.

  By gaining this understanding, you’ll better understand the health of your website’s sales funnels and overall marketing strategy.

  With that knowledge, you can optimise your marketing strategy to patch those leaks, improve conversions and grow your business.

  Why funnel analysis is important

  Funnel analysis is critical because your funnel is your business.

  When you analyse your funnel, you’re analysing your business.

  You’re looking at what’s working and what’s not so you can grow revenue and profit margins.

  Funnel analysis lets you monitor user behaviour to show you the motivation and intention behind their decisions.

  Here are five reasons you need to incorporate funnel analysis into your workflow.

  

  1. Gives insights into your funnel problems

  The core purpose of funnel analysis is to look at what’s going on on your website.

  What are the most effective steps to conversion ?

  Where do users drop off in the conversion process ?

  And which pages contribute the most to conversion or drop-offs ?

  Funnel analysis helps you understand what’s going on with your site visitors. Plus, it helps you see what’s wrong with your funnel.

  If you aren’t sure what’s happening with your funnel, you won’t know what to improve to grow your revenue.

  2. Improves conversions

  When you know what’s going on with your funnel, you’ll know how to improve it.

  To improve your conversion funnel, you need to close the leaks. These are areas where website visitors are falling off.

  It’s the moment the conversion is lost.

  You need to use funnel analysis to give insight into these problem areas. Once you can see where the issue is, you can patch that leak and improve the percentage of visitors who convert.

  For example, if your conversion rate on your flagship product page has plateaued and you can’t figure out how to increase conversions, implementing a funnel analysis tactic like heatmaps will show you that visitors are spending time reading your product description. Still, they’re not spending much time near your call to action.

  

  This might tell you that you need to update your description copy or adjust your button (i.e. colour, size, copy). You can increase conversions by making those changes in your funnel analysis insights.

  3. Improves the customer experience

  Funnel analysis helps you see where visitors spend their time, what elements they interact with and where they fall off.

  One of the key benefits of analysing your funnel is you’ll be able to help improve the experience your visitors have on your website.

  For example, if you have informational videos on a specific web page to educate your visitors, you might use the Media Analytics feature in your web analytics solution to find out that they’re not spending much time watching them.

  This could lead you to believe that the content itself isn’t good or relevant to them.

  But, after implementing session recordings within your funnel analysis, you see people clicking a ton near the play button. This might tell you that they’re having trouble clicking the actual button on the video player due to poor UX.

  In this scenario, you could update the UX on your web page so the videos are easy to click and watch, no matter what device someone uses.

  With more video viewers, you can provide value to your visitors instead of leaving them frustrated trying to watch your videos.

  4. Grows revenue

  This is what you’re likely after : more revenue.

  More often than not, this means you need to focus on improving your conversion rate.

  Funnel analysis helps you find those areas where visitors are exiting so you can patch those leaks up and turn more visitors into customers.

  Let’s say you have a conversion rate of 1.7%.

  You get 50,000 visitors per month.

  Your average order is $82.

  Even if you increase your conversion rate by 10% (to 1.87%) through funnel analysis, here’s the monthly difference in revenue :

  Before : $69,700
  After : $76,670

  In one year, you’ll make nearly $80,000 in additional revenue from funnel analysis alone.

  Different types of funnel analysis

  There are a few different types of funnel analysis.

  How you define success in your funnel all comes down to one of these four pillars.

  Depending on your goals, business and industry, you may want to assess the different funnel analyses at different times.

  1. Pageview funnel analysis

  Pageview funnel analysis is about understanding how well your website content is performing. 

  It helps you enhance user experience, making visitors stay longer on your site. By identifying poor performing pages (pages with high exit rates), you can pinpoint areas that need optimisation for better engagement.

  2. Conversion funnel analysis

  Next up, we’re looking at conversion funnel analysis.

  This type of funnel analysis is crucial for marketers aiming to turn website visitors into action-takers. This involves tracking and optimising conversion goals, such as signing up for newsletters, downloading ebooks, submitting forms or signing up for free trials. 

  The primary goal of conversion funnel analysis is to boost your website’s overall conversion rates.

  3. E-commerce funnel analysis

  For businesses selling products online, e-commerce funnel analysis is essential. 

  It involves measuring whether your products are being purchased and finding drop-off points in the purchasing process. 

  By optimising the e-commerce funnel, you can enhance revenue and improve the overall efficiency of your sales process.

  How to conduct funnel analysis

  Now that you understand what funnel analysis is, why it’s important, and the different types of analysis, it’s time to show you how to do it yourself.

  To get started with funnel analysis, you need to have the right web analytics solution.

  Here are the most common funnel analysis tools and methods you can use :

  1. Funnel analytics

  If you want to choose a single tool to conduct funnel analysis, it’s an all-in-one web analytics tool, like Matomo.

  

  With Matomo’s Funnel Analytics, you can dive into your whole funnel and analyse each step (and each step’s conversion rate).

  

  For instance, if you look at the example above, you can see the proceed rate at each funnel step before the conversion page.

  This means you can improve each proceed rate, to drive more traffic to your conversion page in order to increase conversion rates.

  In the above snapshot from Matomo, it shows visitors starting on the job board overview page, moving on to view specific job listings. The goal is to convert these visitors into job applicants.

  However, a significant issue arises at the job view stage, where 95% of visitors don’t proceed to job application. To increase conversions, we need to first concentrate on improving the job view page.

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  2. Heatmaps

  Heatmaps is a behaviour analytics tool that lets you see different visitor activities, including :

  • Mouse movement
  • How far down visitors scroll
  • Clicks

  You can see which elements were clicked on and which weren’t and how far people scroll down your page.

  

  A heatmap lets you see which parts of a page are getting the most attention and which parts go unnoticed by your users.

  For example, if, during your funnel analysis, you see that a lot of visitors are falling off after they land on the checkout page, then you might want to add a heatmap on your checkout page to see where and why people are exiting.

  3. Session recordings

  Want to see what individual users are doing and how they’re interacting with your site ?

  Then, you’ll want to check out session recordings.

  A session recording is a video playback of a visitor’s time on your website.

  

  It’s the most effective method to observe your visitors’ interactions with your site, eliminating uncertainty when identifying areas for funnel improvement.

  Session recordings instill confidence in your optimisation efforts by providing insights into why and where visitors may be dropping off in the funnel.

  4. A/B testing

  If you want to take the guesswork out of optimising your funnel and increasing your conversions, you need to start A/B testing.

  An A/B test is where you create two versions of a web page to determine which one converts better.

  

  For example, if your heatmaps and session recordings show that your users are dropping off near your call to action, it may be time to test a new version.

  You may find that by simply testing a different colour button, you may increase conversions by 20% or more.

  5. Form analytics

  Are you trying to get more leads to fill out forms on your site ?

  Well, Form Analytics can help you understand how your website visitors interact with your signup forms.

  You can view metrics such as starter rate, conversion rate, average hesitation time and average time spent.

  This information allows you to optimise your forms effectively, ultimately maximising your success.

  Let’s look at the performance of a form using Matomo’s Form Analytics feature below.

  

  In the Matomo example, our starter rate stands at a solid 60.1%, but there’s a significant drop to a submitter rate of 29.3%, resulting in a conversion rate of 16.3%.

  Looking closer, people are hesitating for about 16.2 seconds and taking nearly 1 minute 39 seconds on average to complete our form.

  This could indicate our form is confusing and requesting too much. Simplifying it could help increase sign-ups.

  See first-hand how Concrete CMS tripled their leads using Form Analytics in Matomo.

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  Start optimising your funnels with Matomo today

  If you want to optimise your business, you must optimise your funnels.

  Without information on what’s working and what’s not, you’ll never know if your website changes are making a difference.

  Worse yet, you could have underperforming stages in your funnel, but you won’t know unless you start looking.

  Funnel analysis changes that.

  By analysing your funnels regularly, you’ll be able to see where visitors are leaking out of your funnel. That way, you can get more visitors to convert without generating more traffic.

  If you want to improve conversions and grow revenue today, try Matomo’s Funnel Analytics feature.

  You’ll be able to see conversion rates, drop-offs, and fine-tuned details on each step of your funnel so you can turn more potential customers into paying customers.

  Additionally, Matomo comes equipped with features like heatmaps, session recordings, A/B testing, and form analytics to optimise your funnels with confidence.

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

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• 10 Key Google Analytics Limitations You Should Be Aware Of

  9 mai 2022, par Erin

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

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

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

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

  

  Main limitations of Google Analytics

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

  According to Google, the newest version touts : 

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

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

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

  

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

  1. No Historical Data Imports 

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

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

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

  At present, Google offers two feeble solutions : 

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

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

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

  

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

  2. Data Collection Limits 

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

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

  

  These apply to :

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

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

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

  3. Limited GDPR Compliance 

  Google Analytics has a complex history with European GDPR compliance. 

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

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

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

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

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

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

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

  4. Strong Reliance on Sampled Data 

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

  In GA4 sampling automatically applies when you :

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

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

  In their words :

  

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

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

  5. No Proper Data Anonymization 

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

  This reduced your ability to :

  • Remarket 
  • Identify repeating visitors
  • Do advanced conversion attribution 

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

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

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

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

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

  6. No Roll-Up Reporting

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

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

  

  7. Report Processing Latency 

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

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

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

  8. No Native Conversion Optimisation Features

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

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

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

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

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

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

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

  

  9. Deprecated Annotations

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

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

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

  10. No White Label Option 

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

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

  Wrap Up 

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

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

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

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• CRO Audit : Increase Your Conversions in 10 Simple Steps

  25 mars 2024, par Erin

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

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

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

  You’re choosing the second option, right ?

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

  What is a CRO audit ?

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

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

  

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

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

  Why run a CRO audit ?

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

  Generate targeted and relevant insights

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

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

  Improve conversion rates

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

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

  A 10-step process for running your first CRO audit 

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

  

  1. Define your goals

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

  Your goals could include :

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

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

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

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

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  2. Review your analytics

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

  Consider the following conversion metrics when analysing pages :

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

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

  3. Research the user experience

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

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

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

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

  

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

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

  4. Analyse your forms

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

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

  That’s what form analysis is for. 

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

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

  

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

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  5. Analyse your conversion funnel

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

  

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

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

  6. Analyse campaigns and traffic sources (marketing attribution)

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

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

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

  

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

  7. Use surveys and other qualitative data sources

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

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

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

  8. Develop a conversion hypothesis

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

  Here’s a template you can use :

  

  This could end up looking something like the following :

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

  

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

  9. Run A/B tests

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

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

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

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

  

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

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

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  10. Monitor and iterate

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

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

  How often should you conduct a CRO audit ? 

  You should conduct a CRO audit fairly regularly. 

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

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

  Run your CRO audit with Matomo

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

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

  Just one : Matomo.

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

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

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