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• Top 5 Web Analytics Tools for Your Site

  11 août 2023, par Erin — Analytics Tips

  At the start of July 2023, Universal Analytics (UA) users had to say goodbye to their preferred web analytics tool as Google discontinued it. While some find Google Analytics 4 (GA4) can do what they need, many GA4 users are starting to realise GA4 doesn’t meet all the needs UA once fulfilled. Consequently, they are actively seeking another web analytics tool to complement GA4 and address those unmet requirements effectively.

  In this article, we’ll break down five of the top web analytics tools on the market. You’ll find details about their core capabilities, pricing structures and some noteworthy pros and cons to help you decide which tool is the right fit for you. We’ve also included some key features a good web analytics tool should have to give you a baseline for comparison.

  Whether you’re a marketing manager focused on ROI of campaigns, a web analyst focused on conversions or simply interested in learning more about web analytics, there’s something for you on this list.

  What is a web analytics tool ?

  Web analytics tools collect and analyse information about your website’s visitors, their behaviour and the technical performance of your site. A web analytics tool compiles, measures and analyses website data to give you the information you need to improve site performance, boost conversions and increase your ROI.

  What makes a web analytics tool good ?

  Before we get into tool specifics, let’s go over some of the core features you can expect from a web analytics tool.

  For a web analytics tool to be worth your time (and money), it needs to cover the basics. For example :

  • Visitor reports : The number of visitors, whether they were unique or repeat visitors, the source of traffic (where they found your website), device information (if they’re using a desktop or mobile device) and demographic information like geographic location

  • Behaviour reports : What your visitors did while on your site, conversion rates (e.g., if they signed up for or purchased something), the pages they entered and exited from, average session duration, total time spent on a page and bounce rates (if they left without interacting with anything)

  • Technical information : Page loading speed and event tracking — where users are clicking, what they’re downloading or sharing from your site, if they’re engaging with the media on it and how far down the page they’re scrolling

  • Marketing campaign information : Breakdowns of ad campaigns by provider, showing if ads resulted in traffic to your site and lead to an eventual sale or conversion

  • Search Engine Optimisation (SEO) information : Which keywords on which pages are driving traffic to your site, and what search engines are they coming from

  • Real-time data tracking : Visitor, behaviour and technical information available in real-time, or close to it — allowing you to address to issues as they occur

  • Data visualisation : Charts and graphs illustrating the above information in an easily-readable format — helping identify opportunities and providing valuable insights you can leverage to improve site performance, conversion rates and the amount of time visitors spend on a page

  • Custom reporting : Create custom reports detailing the desired metrics and time frame you’re interested in

  • Security : User access controls and management tools to limit who can see and interact with user data

  • Resources : Official user guides, technical documentation, troubleshooting materials, customer support and community forums

  

  Pros and Cons of Google Analytics 4

  Despite many users’ dissatisfaction, GA4 isn’t going away anytime soon. It’s still a powerful tool with all the standard features you’d expect. It’s the most popular choice for web analytics for a few other reasons, too, including :

  • It’s free to use
  • It’s easy to set up
  • It has a convenient mobile app
  • It has a wealth of user documentation and technical resources online
  • Its machine-learning capabilities help predict user behaviour and offer insights on how to grow your site
  • It integrates easily with other Google tools, like Google Search Console, Google Ads and Google Cloud

  That said, it comes with some serious drawbacks. Many users accustomed to UA have reported being unhappy with the differences between it and GA4. Their reasons range from changes to the user interface and bounce rate calculations, as well as Google’s switch from pageview-focused metrics to event-based ones. 

  Let’s take a look at some of the other cons :

  • Lack of privacy, as Google uses data from Google Analytics for advertising purposes.
  • Cookie consent banners can frustrate visitors, and with 40-60% of web visitors rejecting consent, relying on them can lead to inaccurate data and an incomplete view of your web traffic and campaign outcomes.
  • Can’t import data from UA to GA4 
  • Missing features like heatmaps and session recording
  • Google Analytics 360, the GA for enterprises, costs $150,000/year

  Now that you know GA4’s strengths and weaknesses, it’s time to explore other tools that can help fill in GA4’s gaps.

  Top 5 web analytics tools (that aren’t Google)

  Below is a list of popular web analytics tools that, unless otherwise stated, have all the features a good tool should have.

  Adobe Analytics

  

  Adobe is a trusted name in software, with tools that have shaped the technological landscape for decades, like Photoshop and Illustrator. With web design and UX tools Dreamweaver and XD, it makes sense that they’d offer a web analytics platform as well.

  Adobe Analytics provides not just web analytics but marketing analytics that tell you about customer acquisition and retention, ROI and ad campaign performance metrics. Its machine learning (ML) and AI-powered analytics predict future customer behaviour based on previously collected data.

  Key features : 

  • Multichannel data collection that covers computers, mobile devices and IoT devices
  • Adobe Sensei (AI/ML) for marketing attribution and anomaly detection
  • Tag management through Adobe Experience Platform Launch simplifies the tag creation and maintenance process to help you track how users interact with your site

  Pros :

  • User-friendly and simple to learn with a drag-and-drop interface
  • When integrated with other Adobe software, it becomes a powerful solution for enterprises
  • Saves your team a lot of time with the recommendations and insights automatically generated by Adobe’s AI/ML

  Cons :

  • No free version
  • Adobe Sensei and tag manager limited to premium version
  • Expensive, especially when combined with the company’s other software
  • Steep learning curve for both setup and use

  Mobile app : Yes

  Integrations : Integrates with Adobe Experience Manager Sites, the company’s CMS. Adobe Target, a CRO tool and part of the Adobe Marketing Cloud subscription, integrates with Analytics.

  Pricing : Available upon request

  Matomo

  

  Matomo is the leading open-source web analytics solution designed to help you make more informed decisions and enhance your customer experience while ensuring GDPR compliance and user privacy. With Matomo Cloud, your data is stored in Europe, while Matomo On-Premise allows you to host your data on your own servers.

  Matomo is used on over 1 million websites, in over 190 countries, and in over 50 languages. Additionally, Matomo is an all-in-one solution, with traditional web analytics (visits, acquisition, etc.) alongside behavioural analytics (heatmaps, session recordings and more), plus a tag manager. No more inefficiently jumping back and forth between tabs in a huge tech stack. It’s all in Matomo, for one consistent, seamless and efficient experience. 

  Key features : 

  • Heatmaps and session recording to display what users are clicking on and how individual users interacted with your site 
  • A/B testing to compare different versions of the same content and see which gets better results
  • Robust API that lets you get insights by connecting your data to other platforms, like data visualisation or business intelligence tools

  Pros : 

  • Open-source, reviewed by experts to ensure that it’s secure
  • Offers On-Premise or Cloud-hosted options
  • Fully compliant with GDPR, so you can be data-driven without worrying. 
  • Option to run without cookies, meaning in most countries you can use Matomo without annoying cookie consent banners and while getting more accurate data
  • You retain complete ownership of your data, with no third parties using it for advertising or unspecified “own purposes”

  Cons : 

  • On-Premise is free, but that means an additional cost for advanced features (A/B testing, heatmaps, etc.) that are included by default on Matomo Cloud
  • Matomo On-Premise requires servers and technical expertise to setup and manage

  Mobile app : Matomo offers a free mobile app (iOS and Android) so you can access your analytics on the go. 

  Integrations : Matomo integrates easily with many other tools and platforms, including WordPress, Looker Studio, Magento, Jira, Drupal, Joomla and Cloudflare.

  Pricing : 

  • Varies based on monthly hits
  • Matomo On-Premise : free
  • Matomo Cloud : starting at €19/month

  Mixpanel

  

  Mixpanel’s features are heavily geared toward e-commerce companies. From the moment a visitor lands on your website to the moment they enter their payment details and complete a transaction, Mixpanel tracks these events.

  Similar to GA4, Mixpanel is an event-focused analytics platform. While you can still track pageviews with Mixpanel, its main focus is on the specific actions users take that lead them to purchases. Putting your attention on this information allows you to find out which events on your site are going through the sales funnel.

  They’re currently developing a Warehouse Events feature to simplify the process of importing data lakes and data warehouses.

  Key features :

  • Custom alerts and anomaly detection
  • Boards, which allow you to share multiple reports and insights with your team in a range of visual styles 
  • Detailed segmentation reporting that lets you break down your data to the individual user, specific event or geographic level

  Pros :

  • Boards allow for emojis, gifs, images and videos to make collaboration fun
  • Powerful mobile analytics for iOS and Android apps
  • Free promotional credits for eligible startups 

  Cons :

  • Limited features in free plan
  • Best features limited to the Enterprise-tier subscription
  • Complicated set up
  • Steep learning curve

  Mobile app : No

  Integrations : Mixpanel has a load of integrations, including Figma, Google Cloud, Slack, HappyFox, Snowflake, Microsoft Azure, Optimizely, Mailchimp and Tenjin. They also have a WordPress plugin.

  Pricing : 

  • Starter : free plan available
  • Growth : $20/month
  • Enterprise $833/month

  HubSpot Marketing

  

  HubSpot is a customer relationship management (CRM) platform with marketing, sales, customer service, content management system (CMS) and operations tools. This greater ecosystem of HubSpot software allows you to practically run your entire business in one place.

  Even though HubSpot Marketing isn’t a dedicated web analytics tool, it provides comparable standard metrics as the other tools on this list, albeit without the more advanced analytical metrics they offer. If you’re already using HubSpot to host your website, it’s definitely worth consideration.

  Key features :

  • Customer Journey Analytics presents the steps your customers went through in the sales process, step-by-step, in a visual way
  • Dashboards for your reports, including both fully customisable options for power users and pre-made templates for new users

  Pros :

  • Integration with other HubSpot tools, like HubSpot CRM’s free live chat widget 
  • User-friendly interface with many features being drag-and-drop, like the report dashboard
  • 24/7 customer support

  Cons :

  • Can get expensive with upgrades and other HubSpot tool add ons
  • Not a dedicated web analytics tool, so it’s missing some of the features other tools have, like heatmaps
  • Not really worth it as a standalone tool
  • Some users report customer support is unhelpful

  Mobile app : Yes

  Integrations : The larger HubSpot CRM platform can connect with nearly 1,500 other apps through the HubSpot App Marketplace. These include Slack, Microsoft Teams, Salesforce, Make, WordPress, SurveyMonkey, Shopify, monday.com, Stripe, WooCommerce and hundreds of others.

  Pricing : 

  • Starter : $20/month ($18/month with annual plan) 
  • Professional : $890/month ($800/month with annual plan) 
  • Enterprise : $3,600/month ($43,200 billed annually)

  Kissmetrics

  

  Kissmetrics is a web analytics tool that is marketed toward SaaS and ecommerce companies. They label themselves as “person-based” because they combine event-based tracking with detailed user profiles of the visitors to your site, which allows you to gain insights into customer behaviour. 

  With user profiles, you can drill down to see how many times someone has visited your site, if they’ve purchased from you and the steps they took before completing a sale. This allows you to cater more to these users and drive growth.

  Key features : 

  • Person Profiles that give granular information about individual users and their activities on your site
  • Campaigns, an engagement messenger application, allows you to set up email automations that are triggered by specific events
  • Detailed reporting tools 

  Pros : 

  • No third-party cookies
  • No data sampling
  • APIs for Ruby on Rails, JavaScript, Python and PHP

  Cons : 

  • Difficult installation
  • Strongest reporting features only available in the most expensive plan
  • Reports can be slow to generate
  • Requires custom JavaScript code to tack single-page applications
  • Doesn’t track demographic data, bounce rate, exits, session length or time on page

  Mobile app : No

  Integrations : Kissmetrics integrates with HubSpot, Appcues, Slack, Mailchimp, Shopify, WooCommerce, Recurly and a dozen others. There is also a Kissmetrics WordPress plugin.

  Pricing : 

  • Silver : $299/month (small businesses)
  • Gold : $499/month (medium) 
  • Platinum : custom pricing (enterprises)

  Conclusion

  In this article, you learned about popular tools for web analytics to better inform you of your options. Despite all of GA4’s shortcomings, by complementing it with another web analytics tool, teams can gain a more comprehensive understanding of their website traffic and enhance their overall analytics capabilities.

  If you want an option that delivers powerful insights while keeping privacy, security and compliance at the forefront, you should try Matomo. 

  Try Matomo alongside Google Analytics now to see how it compares.

  Start your 21-day free trial now – no credit card required.

• Meta Receives a Record GDPR Fine from The Irish Data Protection Commission

  29 mai 2023, par Erin — GDPR

  The Irish Data Protection Commission (the DPC) issued a €1.2 billion fine to Meta on May, 22nd 2023 for violating the General Data Protection Regulation (GDPR). 

  The regulator ruled that Meta was unlawfully transferring European users’ data to its US-based servers and taking no sufficient measures for ensuring users’ privacy. 

  Meta must now suspend data transfer within five months and delete EU/EEA users’ personal data that was illegally transferred across the border. Or they risk facing another round of repercussions. 

  Meta continued to transfer personal user data to the USA following an earlier ruling of The Court of Justice of the European Union (CJEU), which already address problematic EU-U.S. data flows. Meta continued those transfers on the basis of the updated Standard Contractual Clauses (“SCCs”), adopted by the European Commission in 2021. 

  The Irish regulator successfully proved that these arrangements had not sufficiently addressed the “fundamental rights and freedoms” of the European data subjects, outlined in the CJEU ruling. Meta was not doing enough to protect EU users’ data against possible surveillance and unconsented usage by US authorities or other authorised entities.

  Why European Regulators Are After The US Big Tech Firms ? 

  GDPR regulations have been a sore area of compliance for US-based big tech companies. 

  Effectively, they had to adopt a host of new measures for collecting user consent, ensuring compliant data storage and the right to request data removal for a substantial part of their user bases. 

  The wrinkle, however, is that companies like Google and Meta among others, don’t have separate data processing infrastructure for different markets. Instead, all the user data gets commingled on the companies’ servers, which are located in the US. 

  Data storage facilities’ location is an issue. In 2020, the CJEU made a historical ruling, called the invalidation of the Privacy Shield. Originally, international companies were allowed to transfer data between the EU and the US if they adhered to seven data protection principles. This arrangement was called the Privacy Shield. 

  However, the continuous investigation found that the Privacy Shield scheme was not GDPR compliant and therefore companies could no longer use it to justify cross-border data transfers.

  The invalidation of the Privacy Shield gave ground for further investigations of the big tech companies’ compliance statuses. 

  In March 2022, the Irish DPC issued the first €17 million fine to Meta for “insufficient technical and organisational measures to ensure information security of European users”. In September 2022, Meta was again hit with a €405 million fine for Instagram breaching GDPR principles. 

  2023 began with another series of rulings, with the DPC concluding that Meta had breaches of the GDPR relating to its Facebook service (€210 million fine) and breaches related to Instagram (€180 million fine). 

  Clearly, Meta already knew they weren’t doing enough for GDPR compliance and yet they refused to take privacy-focused action. 

  Is Google GDPR Compliant ?

  Google has a similar “track record” as Meta when it comes to ensuring full compliance with the GDPR. Although Google has said to provide users with more controls for managing their data privacy, the proposed solutions are just scratching the surface. 

  In the background, Google continues to leverage its ample reserves of user browsing, behavioural and device data in product development and advertising. 

  In 2022, the Irish Council for Civil Liberties (ICCL) found that Google used web users’ information in its real-time bidding ad system without their knowledge or consent. The French data regulator (CNIL), in turn, fined Google for €150 million because of poor cookie consent banners the same year. 

  Google Analytics GDPR compliance status is, however, the bigger concern.

  Neither Google Univeral Analytics (UA) nor Google Analytics 4 are GDPR compliant, following the Privacy Shield framework invalidation in 2020. 

  Fines from individual regulators in Sweden, France, Austria, Italy, Denmark, Finland and Norway ruled that Google Analytics is non-GDPR compliant and is therefore illegal to use. 

  The regulatory rulings not just affect Google, but also GA users. Because the product is in breach of European privacy laws, people using it are complacent. Privacy groups like noyb, for example, are exercising their right to sue individual websites, using Google Analytics.

  How to Stay GDPR Compliant With Website Analytics 

  To avoid any potential risk exposure, selectively investigate each website analytics provider’s data storage and management practices. 

  Inquire about the company’s data storage locations among the first things. For example, Matomo Cloud keeps all the data in the EU, while Matomo On-Premise edition gives you the option to store data in any country of your choice. 

  Secondly, ask about their process for consent tracking and subsequent data analysis. Our website analytics product is fully GDPR compliant as we have first-party cookies enabled by default, offer a convenient option of tracking out-outs, provide a data removal mechanism and practice safe data storage. In fact, Matomo was approved by the French Data Protection Authority (CNIL) as one of the few web analytics apps that can be used to collect data without tracking consent. 

  Using an in-built GDPR Manager, Matomo users can implement the right set of controls for their market and their industry. For example, you can implement extra data or IP anonymization ; disable visitor logs and profiles. 

  Thanks to our privacy-by-design architecture and native controls, users can make their Matomo analytics compliant even with the strictest privacy laws like HIPAA, CCPA, LGPD and PECR. 

  Learn more about GDPR-friendly website analytics.

  Final Thoughts

  Since the GDPR came into effect in 2018, over 1,400 fines have been given to various companies in breach of the regulations. Meta and Google have been initially lax in response to European regulatory demands. But as new fines follow and the consumer pressure mounts, Big Tech companies are forced to take more proactive measures : add opt-outs for personalised ads and introduce an alternative mechanism to third-party cookies. 

  Companies, using non-GDPR-compliant tools risk finding themselves in the crossfire of consumer angst and regulatory criticism. To operate an ethical, compliant business consider privacy-focused alternatives to Google products, especially in the area of website analytics. 

• 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.