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• Google Analytics Privacy Issues : Is It Really That Bad ?

  2 juin 2022, par Erin

  If you find yourself asking : “What’s the deal with Google Analytics privacy ?”, you probably have some second thoughts. 

  Your hunch is right. Google Analytics (GA) is a popular web analytics tool, but it’s far from being perfect when it comes to respecting users’ privacy. 

  This post helps you understand tremendous Google Analytics privacy concerns users, consumers and regulators expressed over the years.

  In this blog, we’ll cover :

  What Does Google Analytics Collect About Users ? 

  To understand Google Analytics privacy issues, you need to know how Google treats web users’ data. 

  By default, Google Analytics collects the following information : 

  • Session statistics — duration, page(s) viewed, etc. 
  • Referring website details — a link you came through or keyword used. 
  • Approximate geolocation — country, city. 
  • Browser and device information — mobile vs desktop, OS usage, etc. 

  Google obtains web analytics data about users via two means : an on-site Google Analytics tracking code and cookies.

  A cookie is a unique identifier (ID) assigned to each user visiting a web property. Each cookie stores two data items : unique user ID and website name. 

  With the help of cookies, web analytics solutions can recognise returning visitors and track their actions across the website(s).

  

  • First party cookies are generated by one website and collect user behaviour data from said website only. 
  • Third-party cookies are generated by a third-party website object (for example, an ad) and can track user behaviour data across multiple websites. 

  As it’s easy to imagine, third-party cookies are a goldmine for companies selling online ads. Essentially, they allow ad platforms to continue watching how the user navigates the web after clicking a certain link. 

  Yet, people have little clue as to which data they are sharing and how it is being used. Also, user consent to tracking across websites is only marginally guaranteed by existing Google Analytics controls. 

  Why Third-Party Cookie Data Collection By GA Is Problematic 

  Cookies can transmit personally identifiable information (PII) such as name, log in details, IP address, saved payment method and so on. Some of these details can end up with advertisers without consumers’ direct knowledge or consent.

  Regulatory frameworks such as General Data Protection Regulation (GDPR) in Europe and California Consumer Privacy Act (CCPA) emerged as a response to uncontrolled user behaviour tracking.

  Under regulatory pressure, Big Tech companies had to adapt their data collection process.

  Apple was the first to implement by-default third-party blocking in the Safari browser. Then added a tracking consent mechanism for iPhone users starting from iOS 15.2 and later. 

  Google, too, said it would drop third-party cookie usage after The European Commission and UK’s Competition and Markets Authority (CMA) launched antitrust investigations into its activity. 

  To shake off the data watchdogs, Google released a Privacy Sandbox — a set of progressive tech, operational and compliance changes for ensuring greater consumer privacy. 

  Google’s biggest promise : deprecate third-party cookies usage for all web and mobile products. 

  Originally, Google promised to drop third-party cookies by 2022, but that didn’t happen. Instead, Google delayed cookie tracking depreciation for Chrome until the second half of 2023. 

  Why did they push back on this despite hefty fines from regulators ?

  Because online ads make Google a lot of money.

  In 2021, Alphabet Inc (parent company of Google), made $256.7 billion in revenue, of which $209.49 billion came from selling advertising. 

  Lax Google Analytics privacy enforcement — and its wide usage by website owners — help Google make those billions from collecting and selling user data. 

  How Google Uses Collected Google Analytics Data for Advertising 

  Over 28 million websites (or roughly 85% of the Internet) have Google Analytics tracking codes installed. 

  Even if one day we get a Google Analytics version without cookies, it still won’t address all the privacy concerns regulators and consumers have. 

  Over the years, Google has accumulated an extensive collection of user data. The company’s engineers used it to build state-of-the-art deep learning models, now employed to build advanced user profiles. 

  Deep learning is the process of training a machine to recognise data patterns. Then this “knowledge” is used to produce highly-accurate predictive insights. The more data you have for model training — the better its future accuracy will be. 

  Google has amassed huge deposits of data from its collection of products — GA, YouTube, Gmail, Google Docs and Google Maps among others. Now they are using this data to build a third-party cookies-less alternative mechanism for modelling people’s preferences, habits, lifestyles, etc. 

  Their latest model is called Google Topics. 

  This comes only after Google’s failed attempt to replace cookie-based training with Federated Learning of Cohorts (FLoC) model. But the solution wasn’t offering enough user transparency and user controls among other issues.

  

  Google Topics promises to limit the granularity of data advertisers get about users. 

  But it’s still a web user surveillance method. With Google Topics, the company will continue collecting user data via Chrome (and likely other Google products) — and share it with advertisers. 

  Because as we said before : Google is in the business of profiting off consumers’ data. 

  Two Major Ways Google Takes Advantage of Customer Data

  Every bit of data Google collects across its ecosystem of products can be used in two ways :

  • For ad targeting and personalisation 
  • To improve Google’s products 

  The latter also helps the former. 

  Advanced Ad Personalisation and Targeting

  GA provides the company with ample data on users’ 

  • Recent and frequent searches 
  • Location history
  • Visited websites
  • Used apps 
  • Videos and ads viewed 
  • Personal data like age or gender 

  The company’s privacy policy explicitly states that :
  

  

  Google also admits to using collected data to “measure the effectiveness of advertising” and “personalise content and ads you see on Google.” 

  But there are no further elaborations on how exactly customers’ data is used — and what you can do to prevent it from being shared with third parties. 

  In some cases, Google also “forgets” to inform users about its in-product tracking.

  Journalists from CNBC and The New York Times independently concluded that Google monitors users’ Gmail activity. In particular, the company scans your inbox for recent purchases, trips, flights and bills notifications. 

  While Google says that this information isn’t sold to advertisers (directly), they still may use the “saved information about your orders in other Google services”. 

  Once again, this means you have little control or knowledge of subsequent data usage. 

  Improving Product Usability 

  Google has many “arms” to collect different data points — from user’s search history to frequently-travelled physical routes. 

  They also reserve the right to use these insights for improving existing products. 

  Here’s what it means : by combining different types of data points obtained from various products, Google can pierce a detailed picture of a person’s life. Even if such user profile data is anonymised, it is still alarmingly accurate. 

  Douglas Schmidt, a computer science researcher at Vanderbilt University, well summarised the matter : 

  “[Google’s] business model is to collect as much data about you as possible and cross-correlate it so they can try to link your online persona with your offline persona. This tracking is just absolutely essential to their business. ‘Surveillance capitalism’ is a perfect phrase for it.”

  Google Data Collection Obsession Is Backed Into Its Business Model 

  OK, but Google offers some privacy controls to users ? Yes. Google only sees and uses the information you voluntarily enter or permit them to access. 

  But as the Washington Post correspondent points out :

  “[Big Tech] companies get to set all the rules, as long as they run those rules by consumers in convoluted terms of service that even those capable of decoding the legalistic language rarely bother to read. Other mechanisms for notice and consent, such as opt-outs and opt-ins, create similar problems. Control for the consumer is mostly an illusion.”

  Google openly claims to be “one of many ad networks that personalise ads based on your activity online”. 

  The wrinkle is that they have more data than all other advertising networks (arguably combined). This helps Google sell high-precision targeting and contextually personalised ads for billions of dollars annually.

  Given that Google has stakes in so many products — it’s really hard to de-Google your business and minimise tracking and data collection from the company.
  

  They are also creating a monopoly on data collection and ownership. This fact makes regulators concerned. The 2021 antitrust lawsuit from the European Commission says : 

  “The formal investigation will notably examine whether Google is distorting competition by restricting access by third parties to user data for advertising purposes on websites and apps while reserving such data for its own use.”

  In other words : By using consumer data to its unfair advantage, Google allegedly shuts off competition.

  But that’s not the only matter worrying regulators and consumers alike. Over the years, Google also received numerous other lawsuits for breaching people’s privacy, over and over again. 

  Here’s a timeline : 

  • 2019 : UK citizens issued a class action suit against Google for imposing cookies to override users’ privacy settings in the Safari browser. 
  • 2020 : US citizens pushed for a $5 billion class-action suit for tracking their activity through browsers set in “private” mode.
  • 2022 : Another class-action lawsuit in the US for deceptive privacy controls and unconsented location data tracking by Google mobile apps. 
  • 2022 : Google reached a $100 million class-action settlement for breaching Illinois biometrics privacy laws in Google Photos. 

  Separately, Google has a very complex history with GDPR compliance. 

  How Google Analytics Contributes to the Web Privacy Problem 

  Google Analytics is the key puzzle piece that supports Google’s data-driven business model. 

  If Google was to release a privacy-focused Google Analytics alternative, it’d lose access to valuable web users’ data and a big portion of digital ad revenues. 

  Remember : Google collects more data than it shares with web analytics users and advertisers. But they keep a lot of it for personal usage — and keep looking for ways to share this intel with advertisers (in a way that keeps regulators off their tail).

  For Google Analytics to become truly ethical and privacy-focused, Google would need to change their entire revenue model — which is something they are unlikely to do.

  Where does this leave Google Analytics users ? 

  In a slippery territory. By proxy, companies using GA are complicit with Google’s shady data collection and usage practice. They become part of the problem.

  In fact, Google Analytics usage opens a business to two types of risks : 

  • Reputational. 77% of global consumers say that transparency around how data is collected and used is important to them when interacting with different brands. That’s why data breaches and data misuse by brands lead to major public outrages on social media and boycotts in some cases. 
  • Legal. EU regulators are on a continuous crusade against Google Analytics 4 (GA4) as it is in breach of GDPR. French and Austrian watchdogs ruled the “service” illegal. Since Google Analytics is not GDPR compliant, it opens any business using it to lawsuits (which is already happening).

  But there’s a way out.

  Choose a Privacy-Friendly Google Analytics Alternative 

  Google Analytics is a popular web analytics service, but not the only one available. You have alternatives such as Matomo. 

  Our guiding principle is : respecting privacy.

  Unlike Google Analytics, we leave data ownership 100% in users’ hands. Matomo lets you implement privacy-centred controls for user data collection.

  Plus, you can self-host Matomo On-Premise or choose Matomo Cloud with data securely stored in the EU and in compliance with GDPR.

  The best part ? You can try our ethical alternative to Google Analytics for free. No credit card required ! Start your free 21-day trial now. 

  21 day free trial. No credit card required.

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  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  

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• What is Multi-Touch Attribution ? (And How To Get Started)

  2 février 2023, par Erin — Analytics Tips

  Good marketing thrives on data. Or more precisely — its interpretation. Using modern analytics software, we can determine which marketing actions steer prospects towards the desired action (a conversion event). 

  An attribution model in marketing is a set of rules that determine how various marketing tactics and channels impact the visitor’s progress towards a conversion. 

  Yet, as customer journeys become more complicated and involve multiple “touches”, standard marketing reports no longer tell the full picture. 

  That’s when multi-touch attribution analysis comes to the fore. 

  What is Multi-Touch Attribution ?

  Multi-touch attribution (also known as multi-channel attribution or cross-channel attribution) measures the impact of all touchpoints on the consumer journey on conversion. 

  Unlike single-touch reporting, multi-touch attribution models give credit to each marketing element — a social media ad, an on-site banner, an email link click, etc. By seeing impacts from every touchpoint and channel, marketers can avoid false assumptions or subpar budget allocations.

  To better understand the concept, let’s interpret the same customer journey using a standard single-touch report vs a multi-touch attribution model. 

  Picture this : Jammie is shopping around for a privacy-centred web analytics solution. She saw a recommendation on Twitter and ended up on the Matomo website. After browsing a few product pages and checking comparisons with other web analytics tools, she signs up for a webinar. One week after attending, Jammie is convinced that Matomo is the right tool for her business and goes directly to the Matomo website a starts a free trial. 

  • A standard single-touch report would attribute 100% of the conversion to direct traffic, which doesn’t give an accurate view of the multiple touchpoints that led Jammie to start a free trial. 
  • A multi-channel attribution report would showcase all the channels involved in the free trial conversion — social media, website content, the webinar, and then the direct traffic source.

  In other words : Multi-touch attribution helps you understand how prospects move through the sales funnel and which elements tinder them towards the desired outcome. 

  Types of Attribution Models

  As marketers, we know that multiple factors play into a conversion — channel type, timing, user’s stage on the buyer journey and so on. Various attribution models exist to reflect this variability. 

  

  First Interaction attribution model (otherwise known as first touch) gives all credit for the conversion to the first channel (for example — a referral link) and doesn’t report on all the other interactions a user had with your company (e.g., clicked a newsletter link, engaged with a landing page, or browsed the blog campaign).

  First-touch helps optimise the top of your funnel and establish which channels bring the best leads. However, it doesn’t offer any insight into other factors that persuaded a user to convert. 

  Last Interaction attribution model (also known as last touch) allocates 100% credit to the last channel before conversion — be it direct traffic, paid ad, or an internal product page.

  The data is useful for optimising the bottom-of-the-funnel (BoFU) elements. But you have no visibility into assisted conversions — interactions a user had prior to conversion. 

  Last Non-Direct attribution model model excludes direct traffic and assigns 100% credit for a conversion to the last channel a user interacted with before converting. For instance, a social media post will receive 100% of credit if a shopper buys a product three days later. 

  This model is more telling about the other channels, involved in the sales process. Yet, you’re seeing only one step backwards, which may not be sufficient for companies with longer sales cycles.

  Linear attribution model distributes an equal credit for a conversion between all tracked touchpoints.

  For instance, with a four touchpoint conversion (e.g., an organic visit, then a direct visit, then a social visit, then a visit and conversion from an ad campaign) each touchpoint would receive 25% credit for that single conversion.

  This is the simplest multi-channel attribution modelling technique many tools support. The nuance is that linear models don’t reflect the true impact of various events. After all, a paid ad that introduced your brand to the shopper and a time-sensitive discount code at the checkout page probably did more than the blog content a shopper browsed in between. 

  Position Based attribution model allocates a 40% credit to the first and the last touchpoints and then spreads the remaining 20% across the touchpoints between the first and last. 

  This attribution model comes in handy for optimising conversions across the top and the bottom of the funnel. But it doesn’t provide much insight into the middle, which can skew your decision-making. For instance, you may overlook cases when a shopper landed via a social media post, then was re-engaged via email, and proceeded to checkout after an organic visit. Without email marketing, that sale may not have happened.

  Time decay attribution model adjusts the credit, based on the timing of the interactions. Touchpoints that preceded the conversion get the highest score, while the first ones get less weight (e.g., 5%-5%-10%-15%-25%-30%).

  This multi-channel attribution model works great for tracking the bottom of the funnel, but it underestimates the impact of brand awareness campaigns or assisted conversions at mid-stage. 

  Why Use Multi-Touch Attribution Modelling

  Multi-touch attribution provides you with the full picture of your funnel. With accurate data across all touchpoints, you can employ targeted conversion rate optimisation (CRO) strategies to maximise the impact of each campaign. 

  Most marketers and analysts prefer using multi-touch attribution modelling — and for some good reasons.

  Issues multi-touch attribution solves 

  • Funnel visibility. Understand which tactics play an important role at the top, middle and bottom of your funnel, instead of second-guessing what’s working or not. 
  • Budget allocations. Spend money on channels and tactics that bring a positive return on investment (ROI). 
  • Assisted conversions. Learn how different elements and touchpoints cumulatively contribute to the ultimate goal — a conversion event — to optimise accordingly. 
  • Channel segmentation. Determine which assets drive the most qualified and engaged leads to replicate them at scale.
  • Campaign benchmarking. Compare how different marketing activities from affiliate marketing to social media perform against the same metrics.

  How To Get Started With Multi-Touch Attribution 

  To make multi-touch attribution part of your analytics setup, follow the next steps :

  1. Define Your Marketing Objectives 

  Multi-touch attribution helps you better understand what led people to convert on your site. But to capture that, you need to first map the standard purchase journeys, which include a series of touchpoints — instances, when a prospect forms an opinion about your business.

  Touchpoints include :

  • On-site interactions (e.g., reading a blog post, browsing product pages, using an on-site calculator, etc.)
  • Off-site interactions (e.g., reading a review, clicking a social media link, interacting with an ad, etc.)

  Combined these interactions make up your sales funnel — a designated path you’ve set up to lead people toward the desired action (aka a conversion). 

  Depending on your business model, you can count any of the following as a conversion :

  • Purchase 
  • Account registration 
  • Free trial request 
  • Contact form submission 
  • Online reservation 
  • Demo call request 
  • Newsletter subscription

  So your first task is to create a set of conversion objectives for your business and add them as Goals or Conversions in your web analytics solution. Then brainstorm how various touchpoints contribute to these objectives. 

  Web analytics tools with multi-channel attribution, like Matomo, allow you to obtain an extra dimension of data on touchpoints via Tracked Events. Using Event Tracking, you can analyse how many people started doing a desired action (e.g., typing details into the form) but never completed the task. This way you can quickly identify “leaking” touchpoints in your funnel and fix them. 

  2. Select an Attribution Model 

  Multi-attribution models have inherent tradeoffs. Linear attribution model doesn’t always represent the role and importance of each channel. Position-based attribution model emphasises the role of the last and first channel while diminishing the importance of assisted conversions. Time-decay model, on the contrary, downplays the role awareness-related campaigns played.

  To select the right attribution model for your business consider your objectives. Is it more important for you to understand your best top of funnel channels to optimise customer acquisition costs (CAC) ? Or would you rather maximise your on-site conversion rates ? 

  Your industry and the average cycle length should also guide your choice. Position-based models can work best for eCommerce and SaaS businesses where both CAC and on-site conversion rates play an important role. Manufacturing companies or educational services providers, on the contrary, will benefit more from a time-decay model as it better represents the lengthy sales cycles. 

  3. Collect and Organise Data From All Touchpoints 

  Multi-touch attribution models are based on available funnel data. So to get started, you will need to determine which data sources you have and how to best leverage them for attribution modelling. 

  Types of data you should collect : 

  • General web analytics data : Insights on visitors’ on-site actions — visited pages, clicked links, form submissions and more.
  • Goals (Conversions) : Reports on successful conversions across different types of assets. 
  • Behavioural user data : Some tools also offer advanced features such as heatmaps, session recording and A/B tests. These too provide ample data into user behaviours, which you can use to map and optimise various touchpoints.

  You can also implement extra tracking, for instance for contact form submissions, live chat contacts or email marketing campaigns to identify repeat users in your system. Just remember to stay on the good side of data protection laws and respect your visitors’ privacy. 

  Separately, you can obtain top-of-the-funnel data by analysing referral traffic sources (channel, campaign type, used keyword, etc). A Tag Manager comes in handy as it allows you to zoom in on particular assets (e.g., a newsletter, an affiliate, a social campaign, etc). 

  Combined, these data points can be parsed by an app, supporting multi-touch attribution (or a custom algorithm) and reported back to you as specific findings. 

  Sounds easy, right ? Well, the devil is in the details. Getting ample, accurate data for multi-touch attribution modelling isn’t easy. 

  Marketing analytics has an accuracy problem, mainly for two reasons :

  • Cookie consent banner rejection 
  • Data sampling application

  Please note that we are not able to provide legal advice, so it’s important that you consult with your own DPO to ensure compliance with all relevant laws and regulations.

  If you’re collecting web analytics in the EU, you know that showing a cookie consent banner is a GDPR must-do. But many consumers don’t often rush to accept cookie consent banners. The average consent rate for cookies in 2021 stood at 54% in Italy, 45% in France, and 44% in Germany. The consent rates are likely lower in 2023, as Google was forced to roll out a “reject all” button for cookie tracking in Europe, while privacy organisations lodge complaints against individual businesses for deceptive banners. 

  For marketers, cookie rejection means substantial gaps in analytics data. The good news is that you can fill in those gaps by using a privacy-centred web analytics tool like Matomo. 

  Matomo takes extra safeguards to protect user privacy and supports fully cookieless tracking. Because of that, Matomo is legally exempt from tracking consent in France. Plus, you can configure to use our analytics tool without consent banners in other markets outside of Germany and the UK. This way you get to retain the data you need for audience modelling without breaching any privacy regulations. 

  Data sampling application partially stems from the above. When a web analytics or multi-channel attribution tool cannot secure first-hand data, the “guessing game” begins. Google Analytics, as well as other tools, often rely on synthetic AI-generated data to fill in the reporting gaps. Respectively, your multi-attribution model doesn’t depict the real state of affairs. Instead, it shows AI-produced guesstimates of what transpired whenever not enough real-world evidence is available.

  4. Evaluate and Select an Attribution Tool 

  Google Analytics (GA) offers several multi-touch attribution models for free (linear, time-decay and position-based). The disadvantage of GA multi-touch attribution is its lower accuracy due to cookie rejection and data sampling application.

  At the same time, you cannot create custom credit allocations for the proposed models, unless you have the paid version of GA, Google Analytics 360. This version of GA comes with a custom Attribution Modeling Tool (AMT). The price tag, however, starts at USD $50,000 per year. 

  Matomo Cloud offers multi-channel conversion attribution as a feature and it is available as a plug-in on the marketplace for Matomo On-Premise. We support linear, position-based, first-interaction, last-interaction, last non-direct and time-decay modelling, based fully on first-hand data. You also get more precise insights because cookie consent isn’t an issue with us. 

  Most multi-channel attribution tools, like Google Analytics and Matomo, provide out-of-the-box multi-touch attribution models. But other tools, like Matomo On-Premise, also provide full access to raw data so you can develop your own multi-touch attribution models and do custom attribution analysis. The ability to create custom attribution analysis is particularly beneficial for data analysts or organisations with complex and unique buyer journeys. 

  Conclusion

  Ultimately, multi-channel attribution gives marketers greater visibility into the customer journey. By analysing multiple touchpoints, you can establish how various marketing efforts contribute to conversions. Then use this information to inform your promotional strategy, budget allocations and CRO efforts. 

  The key to benefiting the most from multi-touch attribution is accurate data. If your analytics solution isn’t telling you the full story, your multi-touch model won’t either. 

  Collect accurate visitor data for multi-touch attribution modelling with Matomo. Start your free 21-day trial now. 

• 5-Step Conversion Rate Optimisation Checklist

  27 octobre 2023, par Erin

  Did you know the average conversion rate across e-commerce businesses in August 2023 was 2.03% ? In the past year, conversion rates have increased by 0.39%.

  Make no mistake. Just because conversion rates are higher this year doesn’t make it any easier to convert visitors.

  Cracking the secrets to improving conversion rates is crucial to running a successful website or business.

  Your site is the digital headquarters all of your marketing efforts funnel toward. With every visitor comes an opportunity to convert them into a lead (or sale).

  Keep reading if you want to improve your lead generation or convert more visitors into customers. In this article, we’ll break down a simple five-step conversion rate optimisation checklist you need to follow to maximise your conversions.

  What is conversion rate optimisation ?

  Before we dive into the steps you need to follow to optimise your conversions, let’s back up and talk conversion rate optimisation.

  

  Conversion rate optimisation, or CRO for short, is the process of increasing the number of website visitors who take a specific action. 

  In most cases, this means :

  • Turning more visitors into leads by getting them to join an email list
  • Convincing a visitor to fill out a contact form for a consultation
  • Converting a visitor into a paying customer by purchasing a product

  However, conversion rate optimisation can be used for any action you want someone to take on your site. That could be downloading a free guide, clicking on a specific link, commenting on a blog post or sharing your website with a friend.

  Why following a CRO checklist is important

  Conversion rate optimisation is both a valuable practice and an absolute necessity for any business or marketer. While it can be a bit complex, especially when you start diving into A/B testing, there are a variety of advantages :

  Get the most out of your efforts

  When all is said and done, if you can’t convert the traffic already coming to your site, dumping a ton of time and resources into traffic generation (whether paid or organic) won’t solve your problem.

  Instead, you need to look at the root of the problem : your conversion rate.

  By doubling down on conversions and following a conversion rate optimisation checklist, you’ll get the greatest result for the effort you’re already putting into your site.

  Increase audience size

  To increase your audience size, you need to increase your traffic, right ? Not exactly.

  While your audience may be considered people who have seen your content or follow you on social media, a high-value audience is one you can market to directly on an ongoing basis.

  Your website gives you the playground to convert visitors into high-value audience members. This is done by creating conversion-focused email signup forms and optimising your website for sale conversions.

  Generate more sales

  Boosting sales through CRO is the core objective. By optimising product pages, simplifying the checkout process, and employing persuasive strategies, you can systematically increase your sales and maximise the value of your existing traffic.

  Reduce customer acquisition costs (CAC)

  With conversion optimisation, you can convert a higher percentage of your website visitors into paid customers. Even if you don’t spend more on acquiring new customers, you’ll be able to generate more sales overall. 

  The result is that your customer acquisition costs will drop, allowing you to increase your total acquisitions to your customer base.

  Improve profitability

  While reduced customer acquisition costs mean you can pour more money into customer acquisition at a cheaper rate, you could simply maintain your costs while driving sales, resulting in increased profitability.

  If you can spend the same amount on acquisition but bring in 20% more customers (due to using a CRO checklist), your profit margins will automatically increase.

  5-step CRO checklist

  To double down on conversion rate optimisation, you need to follow a checklist to ensure you don’t miss any major optimisation opportunities.

  The checklist below is designed to help you systematically optimise your website, ensuring you make the most of your traffic by continuously refining its performance.

  1. Forms

  Analysing and optimising your website’s forms is crucial for enhancing conversion rates. Understanding how visitors interact with your forms can uncover pain points and help you streamline the conversion process.

  Ever wonder where your visitors drop off on your forms ? It could be due to lengthy, time-consuming fields or overly complex forms, leading to a frustrating user experience and lower conversion rate. Whatever the reason, you need the right tools to uncover the root of the issue.

  By leveraging Form Analytics, you gain powerful insights into user behaviour and can identify areas where people may encounter difficulties.

  Form Analytics provides the insights to discover :

  • Average time spent on each field : This metric helps you understand where users may be struggling or spending too much time. By optimising these fields, you can streamline the form, reduce user frustration and increase conversions.
  • Identifying drop-off points : Understanding where users drop off provides insights into which form fields may need improvement. Addressing these drop-off points can increase the conversion rate.
  • Unneeded fields with a high blank submission rate : Discovering fields left blank upon submission can highlight areas for simplification. By eliminating unnecessary fields, you can create more concise and user-friendly forms that may entice more visitors to engage with the form.

  

  Hear first-hand how Concrete CMS achieve 3x more leads with insights from Form Analytics. 

  These data-driven insights empower you to optimise your forms, remove guesswork and settle debates about form design. By fine-tuning and streamlining your forms, you can ensure a smoother path to conversion and maximise your success in converting more visitors.

  Try Matomo for Free

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

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  2. Copywriting

  Another crucial element you need to test is your copywriting. Your copywriting is the foundation of your entire website. It helps communicate to your audience what you have to offer and why they need to take action.

  You need to ensure you have a good offer. This isn’t just the product or service you’re putting out there. It’s the complete package. It includes the product, rewards, a unique guarantee, customer service, packaging and promotions.

  Start testing your copy with your headlines. Look at the headers and test different phrases to convert more potential customers into paying customers.

  Here are a few tips to optimise your copy for more conversions :

  • Ensure copy is relevant to your headline and vice versa.
  • Write short words, short sentences and short paragraphs.
  • Use bullets and subheaders to make the copy easy to skim.
  • Don’t focus too heavily on optimising for search engines (SEO). Instead, write for humans.
  • Focus on writing about benefits, not features.
  • Write about how your offer solves the pain points of your audience.

  You can test your copy in several areas once you’ve begun testing your headers – your subheaders, body copy, signup forms and product pages (if you’re e-commerce).

  3. Media : videos and audio

  Next, testing out different media types is crucial. This means incorporating videos and audio into your content.

  Don’t just take a random guess by throwing stuff against the wall, hoping it sticks. Instead, you should use data to develop impactful content.

  Look at your Media Analytics reports in your website analytics solution and see what media people spend the most time on. See what kind of video or audio content already impacts conversions.

  

  Humans are highly visual. You should craft your content so it’s easy to digest. Instead of covering your website in huge chunks of text, split up your copy with engaging content like videos.

  High-quality videos and audio recordings allow your readers to consume more of your content easily, and help persuade them to take action on your site.

  4. Calls to action (CTA)

  This brings us to our next point : your call to action (CTA).

  Are you trying to convert more prospects into leads ? Want to turn more leads into customers ? Trying to get more email subscribers ? Or do you want to generate more sales every month ?

  You could write the most compelling offer flooded with beautiful images, videos and CRO tactics. But your efforts will go to waste if you don’t include a compelling CTA.

  

  Here are a few tips to optimise your CTAs :

  • Keep them congruent on a single web page (e.g., don’t sell a hat and a sweater on the same page, as it can be confusing).
  • Place at least one CTA above the fold on your web pages.
  • Include benefits in your CTA. Rather than “Buy Now,” try “Buy Now to Get 30% Off.”
  • It’s better to be clear and concise than too fancy and unique.

  Optimising your call to action isn’t just about your copywriting. It’s also about design. Test different fonts, sizes, and visual elements like borders, icons and background colours.

  5. Web design

  Your site design will impact how well your visitors convert. You could have incredible copywriting, but if your site is laid out poorly, it will drive people away.

  You must ensure your copy and visual content fit your website design well.

  The first place you need to start with your site is your homepage design.

  Your site design consists of the theme or template, colour scheme and other visual elements that can be optimised to improve conversions.

  Here are a few tips to keep in mind when optimising your website design :

  • Use a colour scheme that’s pleasant rather than too distracting or extreme.
  • Ensure your design doesn’t remove the text’s clarity but makes it easier to read.
  • When in doubt, start with black text on a white background (the opposite rarely works).
  • Keep plenty of whitespace in between design elements.
  • When in doubt about font size, start by testing a larger size.
  • Design mobile-first rather than desktop-first.

  Finally, it’s critical to ensure your website is easy to navigate. Good design is all about the user experience. Is it easy to find what they’re looking for ? Simplify steps to reduce the need to click, and your conversions will increase.

  Start optimising your website for conversions

  If you’re looking to get the most out of the traffic on your site by converting more visitors into leads or customers, following this 5-step CRO checklist will help you take steps in the right direction.

  Just remember conversion rate optimisation is an ongoing process. It’s not a one-time deal. To succeed, you need to test quickly, analyse the impact and do more of what’s working and less of what’s not.

  To optimise your website for better conversion rates, you need the right tools that provide accurate data and insights to effectively increase conversions. With Matomo, you gain access to web analytics and CRO features like Form Analytics and Media Analytics, designed to enhance your conversion rate optimisation efforts. 

  Try Matomo free for 21 days and take your conversion rate to the next level. No credit card required.

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