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

  17 mars 2023, par Erin — Analytics Tips

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

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

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

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

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

  Google Optimize vs Matomo : Key Capabilities Compared 

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

  Supported Platforms 

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

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

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

  A/B Testing 

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

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

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

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

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

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

  

  Multivariate testing (MVT)

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

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

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

  Redirect Tests

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

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

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

  Experiment Design 

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

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

  Experiment Configuration 

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

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

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

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

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

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

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

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

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

  Reporting 

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

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

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

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

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

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

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

  User Privacy & GDPR Compliance 

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

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

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

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

  Digital Experience Intelligence 

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

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

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

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

  Integrations 

  Both Matomo and Google Optimize integrate with multiple other tools. 

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

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

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

  Pricing 

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

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

  Google Optimize vs Matomo A/B Testing : Comparison Table

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

• Google Analytics 4 (GA4) vs Universal Analytics (UA)

  24 janvier 2022, par Erin — Analytics Tips

  March 2022 Update : It’s official ! Google announced that Universal Analytics will no longer process any new data as of 1 July 2023. Google is now pushing Universal Analytics users to switch to the latest version of GA – Google Analytics 4. 

  Currently, Google Analytics 4 is unable to accept historical data from Universal Analytics. Users need to take action before July 2022, to ensure they have 12 months of data built up before the sunset of Universal Analytics

  So how do Universal Analytics and Google Analytics 4 compare ? And what alternative options do you have ? Let’s dive in. 

  In this blog, we’ll cover :

  What is Google Analytics 4 ? 

  In October 2020, Google launched Google Analytics 4, a completely redesigned analytics platform. This follows on from the previous version known as Universal Analytics (or UA).

  Amongst its touted benefits, GA4 promises a completely new way to model data and even the ability to predict future revenue. 

  However, the reception of GA4 has been largely negative. In fact, some users from the digital marketing community have said that GA4 is awful, unusable and so bad it can bring you to tears.

  

  

  Google Analytics 4 vs Universal Analytics

  There are some pretty big differences between Google Analytics 4 and Universal Analytics but for this blog, we’ll cover the top three.

  1. Redesigned user interface (UI)

  GA4 features a completely redesigned UI to Universal Analytics’ popular interface. This dramatic change has left many users in confusion and fuelled some users to declare that “most of the time you are going round in circles to find what you’re looking for.”

  

  2. Event-based tracking

  Google Analytics 4 also brings with it a new data model which is purely event-based. This event-based model moves away from the typical “pageview” metric that underpins Universal Analytics.

  3. Machine learning insights

  Google Analytics 4 promises to “predict the future behavior of your users” with their machine-learning-powered predictive metrics. This feature can “use shared aggregated and anonymous data to improve model quality”. Sounds powerful, right ?

  Unfortunately, it only works if at least 1,000 returning users triggered the relevant predictive condition over a seven-day period. Also, if the model isn’t sustained over a “period of time” then it won’t work. And according to Google, if “the model quality for your property falls below the minimum threshold, then Analytics will stop updating the corresponding predictions”.

  This means GA4’s machine learning insights probably won’t work for the majority of analytics users.

  Ultimately, GA4 is just not ready to replace Google’s Universal Analytics for most users. There are too many missing features.

  What’s missing in Google Analytics 4 ?

  Quite a lot. Even though it offers a completely new approach to analytics, there are a lot of key features and functions missing in GA4.

  Behavior Flow

  The Behavior Flow report in Universal Analytics helps to visualise the path users take from one page or Event to the next. It’s extremely useful when you’re looking for quick and clear insight. But it no longer exists in Google Analytics 4, and instead, two new overcomplicated reports have been introduced to replace it – funnel exploration report and path exploration report.

  The decision to remove this critical report will leave many users feeling disappointed and frustrated. 

  Limitations on custom dimensions

  You can create custom dimensions in Google Analytics 4 to capture advanced information. For example, if a user reads a blog post you can supplement that data with custom dimensions like author name or blog post length. But, you can only use up to 50, and for some that will make functionality like this almost pointless.

  Machine learning (ML) limitations

  Google Analytics 4 promises powerful ML insights to predict the likelihood of users converting based on their behaviors. The problem ? You need 1,000 returning users in one week. For most small-medium businesses this just isn’t possible.

  And if you do get this level of traffic in a week, there’s another hurdle. According to Google, if “the model quality for your property falls below the minimum threshold, then GA will stop updating the corresponding predictions.” To add insult to injury Google suggests that this might make all ML insights unavailable. But they can’t say for certain… 

  Views

  One cornerstone of Universal Analytics is the ability to configure views. Views allow you to set certain analytics environments for testing or cleaning up data by filtering out internal traffic, for example. 

  Views are great for quickly and easily filtering data. Preset views that contain just the information you want to see are the ideal analytics setup for smaller businesses, casual users, and do-it-yourself marketing departments.

  

  There are a few workarounds but they’re “messy [,] annoying and clunky,” says a disenfranchised Redditor.

  Another helpful Reddit user stumbled upon an unhelpful statement from Google. Google says that they “do not offer [the views] feature in Google Analytics 4 but are planning similar functionality in the future.” There’s no specific date yet though.

  Bounce rate

  Those that rely on bounce rate to understand their site’s performance will be disappointed to find out that bounce rate is also not available in GA4. Instead, Google is pushing a new metric known as “Engagement Rate”. With this metric, Google now uses their own formula to establish if a visitor is engaged with a site.

  Lack of integration

  Currently, GA4 isn’t ready to integrate with many core digital marketing tools and doesn’t accept non-Google data imports. This makes it difficult for users to analyse ROI and ROAS for campaigns measured in other tools. 

  Content Grouping

  Yet another key feature that Google has done away with is Content Grouping. However, as with some of the other missing features in GA4, there is a workaround, but it’s not simple for casual users to implement. In order to keep using Content Grouping, you’ll need to create event-scoped custom dimensions.

  Annotations 

  A key feature of Universal Analytics is the ability to add custom Annotations in views. Annotations are useful for marking dates that site changes were made for analysis in the future. However, Google has removed the Annotations feature and offered no alternative or workaround.

  Historical data imports are not available

  The new approach to data modelling in GA4 adds new functionality that UA can’t match. However, it also means that you can’t import historical UA data into GA4. 

  Google’s suggestion for this one ? Keep running UA with GA4 and duplicate events for your GA4 property. Now you will have two different implementations running alongside each other and doing slightly different things. Which doesn’t sound like a particularly streamlined solution, and adds another level of complexity.

  Should you switch to Google Analytics 4 ?

  So the burning question is, should you switch from Universal Analytics to Google Analytics 4 ? It really depends on whether you have the available resources and if you believe this tool is still right for your organisation. At the time of writing, GA4 is not ready for day-to-day use in most organisations.

  If you’re a casual user or someone looking for quick, clear insights then you will likely struggle with the switch to GA4. It appears that the new Google Analytics 4 has been designed for enterprise-scale businesses with large internal teams of analysts.

  

  Unfortunately, for most casual users, business owners and do-it-yourself marketers there are complex workarounds and time-consuming implementations to handle. Ultimately, it’s up to you to decide if the effort to migrate and relearn GA is worth it.

  Right now is the best time to draw the line and make a decision to either switch to GA4 or look for a better alternative to Google Analytics.

  Google Analytics alternative

  Matomo is one of the best Google Analytics alternatives offering an easy to use design with enhanced insights on our Cloud, On-Premise and on Matomo for WordPress solutions. 

  

  Matomo is an open-source analytics solution that provides a comprehensive, user-friendly and compliance-focused alternative to both Google Analytics 4 and Universal Analytics.

  The key benefits of using Matomo include :

  • Easy to use – Matomo provides a simpler interface and understandable KPIs. See for yourself with our live demo. 
  • Compliance – Future-proof your tech stack for looming privacy regulations. Matomo covers all of your ePrivacy, GDPR, HIPAA, CCPA, and PECR data compliance requirements. 
  • Data privacy and ownership – Your analytics data is 100% yours to own, with no external parties looking in.
  • Flexible, all-in-one solution – Get features like A/B Testing, Heatmaps, Session Recordings, SEO Web Vitals, Tag Manager, Media Analytics, Search Engine Keyword Performance, custom reports and much more. 
  • Integrations galore – Expand your Matomo capabilities by adding integrations from over 100 leading technologies.

  Plus, unlike GA4, Matomo will accept your historical data from UA so you don’t have to start all over again. Check out our 7 step guide to migrating from Google Analytics to find out how.

  Getting started with Matomo is easy. Check out our live demo and start your free 21-day trial. No credit card required.

  In addition to the limitations and complexities of GA4, there are many other significant drawbacks to using Google Analytics.

  Google’s data ethics are a growing concern of many and it is often discussed in the mainstream media. In addition, GA is not GDPR compliant by default and has resulted in 200k+ data protection cases against websites using GA.

  What’s more, the data that Google Analytics actually provides its end-users is extrapolated from samples. GA’s data sampling model means that once you’ve collected a certain amount of data Google Analytics will make educated guesses rather than use up its server space collecting your actual data. 

  The reasons to switch from Google Analytics are rising each day. 

  Wrap up

  The now required update to GA4 will add new layers of complexity, which will leave many casual web analytics users and marketers wondering if there’s a better way. Luckily there is. Get clear insights quickly and easily with Matomo – start your 21-day free trial now.

• Conversion Funnel Optimisation : 10 Ways to Convert More

  24 janvier 2024, par Erin

  Converting leads into happy customers is the ultimate goal of any sales and marketing team. But there are many steps in between those two events, or in other words, funnel stages. 

  Your sales funnel includes all the steps you take to make your audience aware of your product or services and convince them to purchase. Conversion funnel optimisation strategies can help you move users through the stages of your sales funnel. 

  This article will show you how to optimise your conversion funnel and boost sales — no matter how your funnel looks. We’ll go over practical tips you can implement and how you can analyse and measure results.

  Let’s get started.

  What is conversion funnel optimisation ? 

  Conversion funnel optimisation is the strategic and ongoing process of refining and improving the different stages of a sales or marketing funnel to increase the rate at which users complete desired actions.

  A sales funnel represents the stages a potential customer goes through before purchasing. 

  The typical stages of a sales funnel include :

  • Awareness : At the top of the funnel, potential customers become aware of your product or service. 
  • Consideration : In this stage, prospects evaluate the product or service against alternatives. They may compare features, prices and customer reviews to make an informed decision.
  • Conversion : The prospect completes the transaction and becomes an actual customer by purchasing.
  • Loyalty : You can turn one-time buyers into repeat customers and brand advocates. 

  It’s called a “funnel” because, similar to the shape of a funnel, the number of potential customers decreases as they progress through the various stages of the sales process — as you can see illustrated below.

  

  Sales funnels can vary across industries and business models, but the general concept remains the same. The goal is to guide potential customers through each funnel stage, addressing their needs and concerns at each step, ultimately leading to a successful conversion. 

  You can create and monitor a custom funnel for your site’s user journey with a web analytics solution like Matomo.

  Try Matomo for Free

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

  Start for free

  No credit card required

  The importance of conversion funnel optimisation 

  At the heart of conversion funnel optimisation is the quest for higher conversion rates. 

  Refining the customer journey can increase the chances of turning visitors into customers who return repeatedly.

  Specifically, here’s how conversion funnel optimisation can benefit your business :

  • Increased conversions : Marketers can increase the likelihood of turning website visitors into customers by making the user journey more user-friendly and persuasive.
  • Higher revenue : Improved conversion rates aren’t just numbers on a chart ; they translate to tangible revenue. 
  • Increased ROI (return on investment) : By optimising the conversion funnel, you can get more value from your marketing and sales efforts. 
  • Improved customer satisfaction : When customers find it easy and enjoyable to interact with a website or service, it positively influences their satisfaction and likelihood of returning.
  • Data-driven decision-making : Businesses can make informed decisions on budgets and resources based on user behaviour and performance metrics by analysing and optimising conversion funnels.

  ​​Ultimately, conversion funnel optimisation efforts align the entire funnel with overarching business goals.

  10 ways to optimise your conversion funnel 

  Here are 10 ways to optimise your conversion funnel.

  1. Identify and segment your target audience

  The key to a successful conversion funnel begins with a deep understanding of your target audience. 

  Identifying and segmenting your audience lets you speak directly to their pain points, desires and motivations.

  One effective way to know your audience better is by creating detailed buyer personas. These are fictional representations of your ideal customers based on thorough market research and real data. Dive into demographics and behavioural patterns to craft personas that resonate with your audience.

  

  Note that consumer preferences are not static. They evolve, influenced by trends, technological advancements and shifts in societal values. Staying attuned to these changes is crucial as part of optimising your conversion funnel.

  Thus, you must regularly update your buyer personas and adjust your marketing strategies accordingly.

  2. Create content for every stage of the funnel

  Each funnel stage represents a different mindset and needs for your potential customers. Tailoring your content ensures you deliver the right message at the right time to the right audience. 

  Here’s how to tailor your content to fit prospective customers at every conversion funnel stage.

  Awareness-stage content

  Prospects here are seeking information. Your content should be educational and focused on addressing their pain points. Create blog posts, infographics and videos introducing them to your industry, product or service.

  This video we created at Matomo is a prime example of awareness-stage content, grabbing attention and educating viewers about Matomo.

  Consideration-stage content

  Prospects are evaluating their options. Provide content highlighting your product’s unique selling points, such as case studies, product demonstrations and customer testimonials.

  Here’s how we use a versus landing page at Matomo to persuade prospects at this funnel stage.

  

  Conversion-stage content

  This is the final push. Ensure a smooth transition to conversion with content like promotional offers, limited-time discounts and clear calls to action (CTA).

  Loyalty-stage content

  In this stage, you might express gratitude for the purchase through personalised thank-you emails. Follow up with additional resources, tips or exclusive offers to reinforce a positive post-purchase experience. This also positions your brand as a helpful resource beyond the initial sale.

  Reward customer loyalty with exclusive offers, discounts or membership in a loyalty program.

  3. Capture leads

  Lead magnets are incentives offered to potential customers in exchange for their contact information, typically their email addresses. 

  Examples of lead magnets include :

  • Ebooks and whitepapers : In-depth resources that delve into specific topics of interest to your target audience.
  • Webinars and workshops : Live or recorded sessions that offer valuable insights, training or demonstrations.
  • Free trials and demos : Opportunities for potential customers to experience your product or service firsthand.
  • Checklists and templates : Practical tools that help your audience solve specific challenges.
  • Exclusive offers and discounts : Special promotions are available to those who subscribe or provide their contact information.

  For instance, here’s how HubSpot uses templates as lead magnets.

  

  Similarly, you can incorporate your lead magnets into relevant articles or social media posts, email campaigns and other marketing channels.

  4. Optimise your landing pages

  Understanding how visitors interact with your landing pages is a game-changer. So, the first step in optimising your landing pages is to analyse them.

  Enter Matomo’s heatmaps — the secret weapon in landing page optimisation. They visually represent how users interact with your pages, revealing where they linger, what catches their attention and where they may encounter friction. 

  

  Here are a few landing page elements you should pay attention to :

  • Strategic visual elements : Integrate high-quality images, videos and graphics that support your message and guide visitors through the content.
  • Compelling copy : Develop concise and persuasive copy that emphasises the benefits of your offering, addressing user pain points.
  • Effective CTA : Ensure your CTA is prominently displayed, using compelling language and colours that stand out.
  • Mobile responsiveness : Optimise your landing pages for various devices, especially considering the prevalence of mobile users.
  • Minimal form fields : Reduce friction by keeping form fields to a minimum, requesting only essential information.
  • ​​Leverage social proof : Integrate testimonials, reviews and trust badges to build trust and credibility.
  • A/B testing : Experiment with variations in design, copy and CTAs through A/B testing, allowing data to guide your decisions.

  Try Matomo for Free

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

  Start for free

  No credit card required

  5. ​​Use compelling Calls to Action (CTAs)

  Crafting compelling CTAs is an art that involves a careful balance of persuasion, clarity and relevance.

  Here are a few tips you can implement to write CTAs that support your goals :

  • Use language that compels action. Instead of generic phrases like “Click Here,” opt for more persuasive alternatives such as “Unlock Exclusive Access” or “Start Your Free Trial.”
  • Make sure your CTAs are clear and straightforward. Visitors should instantly understand what action you want them to take. 
  • Tailor CTAs to the specific content on the page. Whether it’s a blog post, landing page or email, the CTA should seamlessly connect with the surrounding context.
  • Position your CTAs strategically. They should be prominently displayed and easily noticeable, guiding visitors without intruding.
  • Create a sense of urgency. Encourage immediate action by incorporating language that instils a sense of urgency. Phrases like “Limited Time Offer” or “Act Now” can prompt quicker responses.

  6. Have an active social presence

  Social media platforms are bustling hubs of activity where your target audience spends a significant portion of their online time. Cultivating a social media presence allows you to meet your audience where they are, fostering a direct line of communication.

  Moreover, the integration of shopping features directly into social media platforms transforms them into seamless shopping experiences. Nearly half of Instagram users shop weekly through the platform. 

  Also, the US social commerce sales continue to grow each year and are expected to reach $79.64 billion by 2025.

  

  7. Build a brand community

  Four in five customers consider communities important to how engaged they are with a brand.

  A strong community fosters a sense of belonging and loyalty among members. When customers feel connected to your brand and each other, they are more likely to remain loyal over the long term. 

  Also, satisfied community members often share their positive experiences with others, expanding your brand’s reach without additional marketing efforts.

  For example, Nike’s community for runners is a digital space where individuals share their running journeys, accomplishments and challenges. 

  

  By strategically building and nurturing a community, you not only enhance retention and spur referrals but also create a space where your brand becomes an integral part of your customers’ lives. 

  8. Conduct A/B tests

  A/B testing systematically compares two versions of a webpage, email or other content to determine which performs better.

  Examples of elements to A/B test :

  • CTAs : The language, colour, size and placement of CTAs can significantly impact user engagement. A/B testing allows you to discover which variations prompt the desired actions.
  • Headlines : Crafting compelling headlines is an art. Test different versions to identify which headlines resonate best with your audience, whether they are more drawn to clarity, humour, urgency or curiosity.
  • Images : Test different images to understand your audience’s visual preferences. This could include product images, lifestyle shots or graphics.

  

  With Matomo’s A/B testing feature, you can test various elements to see which is successful in converting visitors or moving them to the next stage of the conversion funnel.

  9. Leverage social proof

  In an era where consumers are inundated with choices, the opinions, reviews and endorsements of others serve as beacons, guiding potential customers through the decision-making process. 

  Simply put — when people see that others have had positive experiences with your brand, it instils trust and confidence.

  

  You can proactively gather social proof and display it prominently across your marketing channels. Here are some examples of social proof you can leverage :

  • Customer reviews : Positive reviews and testimonials from satisfied customers serve as authentic endorsements of your products or services. 
  • Case studies : In-depth case studies that showcase successful collaborations or solutions provided to clients offer a detailed narrative of your brand’s capabilities. These are particularly effective in B2B scenarios or for complex products and services.
  • User-generated content : Encourage customers to share their experiences. This could include photos, videos or posts on social media platforms, providing a dynamic and genuine portrayal of your brand.
  • Influencer endorsements : Collaborating with influencers in your industry or niche can amplify your social proof. When influencers vouch for your products or services, their followers are more likely to take notice.

  10. Measure and analyse performance

  This is a continuous loop of refinement, where you should use analysis and data-driven insights to guide your conversion funnel optimisation efforts.

  Here’s a systematic approach you can take :

  1. Identify the path users take on your site using a feature like Users Flow.
  2. Map the customer journey using a Funnels feature like the one in Matomo. 
  3. Identify the metrics that align with your conversion goals at each stage of the funnel, such as website traffic, conversion rates, click-through rates and customer acquisition costs.
  4. Assess conversion rates at different stages of the funnel. Identify areas with significant drop-offs and investigate factors that might contribute to the decline.
  5. Use heatmaps and session recordings to see first-hand how users interact with your site.
  6. Create an experiment to test and improve a specific area within your funnel using insights from the heatmaps and session recordings.
  7. A/B test, analyse the results to understand which variations performed better. Use this data to refine elements within your funnel.

  See how Concrete CMS 3x their leads with conversion optimisation.

  Conclusion 

  The customer journey is not linear. However, it involves a few specific stages your audience will go through — from first learning about your product or services to considering whether to try it. The goal is to turn them into happy and loyal customers.

  In this article, we went over strategies and practical tips you can use to guide customers through the conversion funnel. From segmenting your audience to capturing leads, optimising landing pages and running A/B tests, there are steps you can take to ensure your audience will move to the next stage.

  And of course, you have to continuously measure and analyse your performance. That’s how you know whether you’re heading in the right direction and, if not, where to correct your course. 

  For that, you need a robust web analytics solution with conversion optimisation features. Try Matomo free for 21 days and start optimising your conversion funnel—no credit card required. 

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