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• My journey to Coviu

  27 octobre 2015, par silvia

  My new startup just released our MVP – this is the story of what got me here.

  I love creating new applications that let people do their work better or in a manner that wasn’t possible before.

  My first such passion was as a student intern when I built a system for a building and loan association’s monthly customer magazine. The group I worked with was managing their advertiser contacts through a set of paper cards and I wrote a dBase based system (yes, that long ago) that would manage their customer relationships. They loved it – until it got replaced by an SAP system that cost 100 times what I cost them, had really poor UX, and only gave them half the functionality. It was a corporate system with ongoing support, which made all the difference to them.

  The story repeated itself with a CRM for my Uncle’s construction company, and with a resume and quotation management system for Accenture right after Uni, both of which I left behind when I decided to go into research.

  Even as a PhD student, I never lost sight of challenges that people were facing and wanted to develop technology to overcome problems. The aim of my PhD thesis was to prepare for the oncoming onslaught of audio and video on the Internet (yes, this was 1994 !) by developing algorithms to automatically extract and locate information in such files, which would enable users to structure, index and search such content.

  Many of the use cases that we explored are now part of products or continue to be challenges : finding music that matches your preferences, identifying music or video pieces e.g. to count ads on the radio or to mark copyright infringement, or the automated creation of video summaries such as trailers.

  

  This continued when I joined the CSIRO in Australia – I was working on segmenting speech into words or talk spurts since that would simplify captioning & subtitling, and on MPEG-7 which was a (slightly over-engineered) standard to structure metadata about audio and video.

  In 2001 I had the idea of replicating the Web for videos : i.e. creating hyperlinked and searchable video-only experiences. We called it “Annodex” for annotated and indexed video and it needed full-screen hyperlinked video in browsers – man were we ahead of our time ! It was my first step into standards, got several IETF RFCs to my name, and started my involvement with open codecs through Xiph.

  Around the time that YouTube was founded in 2006, I founded Vquence – originally a video search company for the Web, but pivoted to a video metadata mining company. Vquence still exists and continues to sell its data to channel partners, but it lacks the user impact that has always driven my work.

  As the video element started being developed for HTML5, I had to get involved. I contributed many use cases to the W3C, became a co-editor of the HTML5 spec and focused on video captioning with WebVTT while contracting to Mozilla and later to Google. We made huge progress and today the technology exists to publish video on the Web with captions, making the Web more inclusive for everybody. I contributed code to YouTube and Google Chrome, but was keen to make a bigger impact again.

  The opportunity came when a couple of former CSIRO colleagues who now worked for NICTA approached me to get me interested in addressing new use cases for video conferencing in the context of WebRTC. We worked on a kiosk-style solution to service delivery for large service organisations, particularly targeting government. The emerging WebRTC standard posed many technical challenges that we addressed by building rtc.io , by contributing to the standards, and registering bugs on the browsers.

  Fast-forward through the development of a few further custom solutions for customers in health and education and we are starting to see patterns of need emerge. The core learning that we’ve come away with is that to get things done, you have to go beyond “talking heads” in a video call. It’s not just about seeing the other person, but much more about having a shared view of the things that need to be worked on and a shared way of interacting with them. Also, we learnt that the things that are being worked on are quite varied and may include multiple input cameras, digital documents, Web pages, applications, device data, controls, forms.

  So we set out to build a solution that would enable productive remote collaboration to take place. It would need to provide an excellent user experience, it would need to be simple to work with, provide for the standard use cases out of the box, yet be architected to be extensible for specialised data sharing needs that we knew some of our customers had. It would need to be usable directly on Coviu.com, but also able to integrate with specialised applications that some of our customers were already using, such as the applications that they spend most of their time in (CRMs, practice management systems, learning management systems, team chat systems). It would need to require our customers to sign up, yet their clients to join a call without sign-up.

  Collaboration is a big problem. People are continuing to get more comfortable with technology and are less and less inclined to travel distances just to get a service done. In a country as large as Australia, where 12% of the population lives in rural and remote areas, people may not even be able to travel distances, particularly to receive or provide recurring or specialised services, or to achieve work/life balance. To make the world a global village, we need to be able to work together better remotely.

  The need for collaboration is being recognised by specialised Web applications already, such as the LiveShare feature of Invision for Designers, Codassium for pair programming, or the recently announced Dropbox Paper. Few go all the way to video – WebRTC is still regarded as a complicated feature to support.

  

  With Coviu, we’d like to offer a collaboration feature to every Web app. We now have a Web app that provides a modern and beautifully designed collaboration interface. To enable other Web apps to integrate it, we are now developing an API. Integration may entail customisation of the data sharing part of Coviu – something Coviu has been designed for. How to replicate the data and keep it consistent when people collaborate remotely – that is where Coviu makes a difference.

  We have started our journey and have just launched free signup to the Coviu base product, which allows individuals to own their own “room” (i.e. a fixed URL) in which to collaborate with others. A huge shout out goes to everyone in the Coviu team – a pretty amazing group of people – who have turned the app from an idea to reality. You are all awesome !

  With Coviu you can share and annotate :

  • images (show your mum photos of your last holidays, or get feedback on an architecture diagram from a customer),
  • pdf files (give a presentation remotely, or walk a customer through a contract),
  • whiteboards (brainstorm with a colleague), and
  • share an application window (watch a YouTube video together, or work through your task list with your colleagues).

  All of these are regarded as “shared documents” in Coviu and thus have zooming and annotations features and are listed in a document tray for ease of navigation.

  This is just the beginning of how we want to make working together online more productive. Give it a go and let us know what you think.

  http://coviu.com/

  The post My journey to Coviu first appeared on ginger’s thoughts.

• How to Track Website Visitors : Benefits, Tools and FAQs

  31 août 2023, par Erin — Analytics Tips, Marketing

  Businesses spend a ton of time, money and effort into creating websites that are not only helpful and captivating, but also highly effective at converting visitors. They’ll create content, revise designs, add new pages and change forms, all in the hope of getting visitors to stay on the site and convert into leads or customers.

  When you track website visitors, you can see which of your efforts are moving the needle. While many people are familiar with pageviews as a metric, website visitor tracking can be much more in-depth and insightful.

  In this article, we’ll cover how website visitor tracking works, what you can track, and how this information can improve sales and marketing results. We’ll also explain global privacy concerns and how businesses can choose the right tracking software. 

  What is website visitor tracking ? 

  Website visitor tracking uses software and applications to track and analyse how visitors interact with your website. It’s a vital tool to help businesses understand whether their website design and content are having the desired effect.

  

  Website visitor tracking includes very broad, non-specific data, like how many times visitors have come to your site. But it can also get very specific, with personal information about the user and even recordings of their visit to your site. Site visits, which may include visiting several different pages of the same site, are often referred to as “sessions.”

  Although Google Analytics is the most widely used website visitor tracking software, it isn’t the most comprehensive or powerful. Companies that want a more in-depth understanding of their website may need to consider running a more precise tool alongside Google Analytics, like Matomo.

  As we’ll cover later, website tracking has many important business applications, but it also poses privacy and security concerns, causing some states and countries to impose strict regulations. Privacy laws and your company’s values should also impact what web analytics tool you choose.

  How website tracking works

  Website tracking starts with the collection of data as users interact with the website. Tracking technologies like cookies, JavaScript and pixels are embedded into web pages. These technologies then gather data about user behaviour, session details and user actions, such as pageviews, clicks, form submissions and more.

  More advanced tracking systems assign unique identifiers (such as cookies or visitor IDs) to individual users. This enables tracking of user journeys across multiple sessions and pages. These detailed journeys can often tell a different story and provide different insights than aggregated numbers do. 

  All this collected data is transmitted from the user’s browser to a centralised tracking system, which can be a third-party web analytics tool or a self-hosted solution. The collected data is stored in databases and processed to generate meaningful insights. This process involves organising the data, aggregating metrics, and creating reports.

  Analytics tools process the collected data to generate reports and visualisations that provide insights into user behaviour. Metrics such as pageviews, bounce rates, conversion rates and user paths are analysed. Good web analytics tools are able to present these insights in a user-friendly way. Analysts and marketing professionals then use this knowledge to make informed decisions to improve the user experience (UX).

  Advanced tracking systems allow data segmentation and filtering based on various criteria, such as user demographics, traffic sources, devices and more. This enables deeper analysis of specific user groups. For example, you might find that your conversion rate is much lower when your website is viewed on a mobile device. You can then dig deeper into that segment of data to find out why and experiment with changes that might increase mobile conversions.

  3 types of website tracking and their benefits

  There are three main categories of website tracking, and they each provide different information that can be used by sales, marketing, engineering and others. Here, we cover those three types and how businesses use them to understand customers and create better experiences.

  Website analytics 

  Website analytics is all about understanding the traffic your website receives. This type of tracking allows you to learn how the website performs based on pageviews, real-time traffic, bounce rate and conversions. 

  For example, you would use website analytics to determine how effectively your homepage drives people toward a product or pricing page. You can use pageviews and previous page statistics to learn how many people who land on your homepage read your blog posts. From there, you could use web analytics to determine the conversion rate of the call to action at the end of each article.

  

  User behaviour

  While website analytics focuses on the website’s performance, user behaviour tracking is about monitoring and quantifying user behaviour. One of the most obvious aspects of user behaviour is what they click on, but there are many other actions you can track. 

  The time a user spends on a page can help you determine whether the content on the page is engaging. Some tracking tools can also measure how far down the page a user scrolls, which reveals whether some content is even being seen. 

  Session recordings are another popular tool for analysing user behaviour. They not only show concrete actions, like clicks, but can also show how the user moves throughout the page. Where do they stop ? What do they scroll right past ? This is one example of how user behaviour data can be quantitative or qualitative.

  Visitor information

  Tracking can also include gathering or uncovering information about visitors to your site. This might include demographic information, such as language and location, or details like what device a website visitor is using and on which browser they view your website. 

  This type of data helps your web and marketing teams make better decisions about how to design and format the site. If you know, for example, that the website for your business-to-business (B2B) software is overwhelmingly viewed on desktop computers, that will affect how you structure your pages and choose images. 

  Similarly, if visitor information tells you that you have a significant audience in France, your marketing team might develop new content to appeal to those potential customers.

  Use website visitor tracking to improve marketing, sales and UX 

  Website visitor tracking has various applications for different parts of your business, from marketing to sales and much more. When you understand the impact tracking has on different teams, you can better evaluate your company’s needs and build buy-in among stakeholders.

  Marketing

  At many companies, the marketing team owns and determines what kind of content is on your website. From landing pages to blog posts to the navigation bar, you want to create an experience that drives people toward making a purchase. When marketers can track website visitors, they can get a real look at how visitors respond to and engage with their marketing efforts. Pageviews, conversion rates and time spent on pages help them better understand what your customers care about and what messaging resonates.

  But web analytics can even help marketing teams better understand how their external marketing campaigns are performing. Tracking tools like Matomo reveal your most important traffic sources. The term “traffic source” refers to the content or web property from which someone arrives at your site. 

  For instance, you might notice that an older page got a big boost in traffic this month. You can then check the traffic sources, where you find that an influential LinkedIn user posted a link to the page. This presents an opportunity to adjust the influencer or social media aspects of your marketing strategy.

  

  Beyond traffic sources, Matomo can provide a visual user journey (also known as User Flow), showing which pages visitors tend to view in a session and even in what order they progress. This gives you a bird’s-eye view of the customer journey.

  Sales

  Just like your marketing team, your sales team can benefit from tracking and analysing website visitor information. Data about user behaviour and visitor demographics helps sales representatives better understand the people they’re talking to. Segmented visitor tracking data can even provide clues as to how to appeal to different buyer personas.

  Sales leadership can use web analytics to gauge interest over time, tie visitors to revenue and develop more accurate sales forecasts and goals. 

  

  And it’s not just aggregated website tracking data that your sales team can use to better serve customers. They can also use insights about an individual visitor to tailor their approach. Matomo’s Visits Log report and Visitor Profiles allow you to see which pages a prospect has viewed. This tells your sales team which products and features the prospect is most interested in, leading to more relevant interactions and more effective sales efforts.

  User experience and web development

  The way users interact with and experience your website has a big impact on their impression of your brand and, ultimately, whether they become customers. While marketing often controls much of a website’s content, the backend and technical operation of the site usually falls to a web development or engineering team. Website analytics and tracking inform their work, too.

  Along with data about website traffic and conversion rates, web development teams often monitor bounce rates (the percentage of people who leave your website entirely after landing on a page) and page load time (the time it takes for an individual web page to load for a user). Besides the fact that slow loading times inconvenience visitors, they can also negatively affect your search engine optimization (SEO).

  

  Along with session recordings, user experience teams and web developers may use heatmaps to find out what parts of a page draw a visitor’s attention and where they are most likely to convert or take some other action. They can then use these insights to make a web page more intuitive and useful.

  Visitor tracking and privacy regulations 

  There are different data privacy standards in other parts of the world, which are designed to ensure that businesses collect and use consumer data ethically. The most-discussed of these privacy standards is the General Data Protection Regulation (GDPR), which was instituted by the European Union (EU) but affects businesses worldwide. However, it’s important to note that individual countries or states can have different privacy laws.

  Many privacy laws govern how websites can use cookies to track visitors. With a user’s consent, cookies can help websites identify and remember visitors. However, many web visitors will reject cookie consent banners. When this happens, analysts and marketers can’t collect information from these visitors and have to work with incomplete tracking data. Incomplete data leads to poor decision-making. What’s more, cookie consent banners can create a poor user experience and often annoy web visitors.

  With Matomo’s industry-leading measures to protect user privacy, France’s data protection agency (CNIL) has confirmed that Matomo is exempt from tracking consent in France. Matomo users have peace of mind knowing they can uphold the GDPR and collect data without needing to collect and track cookie consent. Only in Germany and the UK are cookie consent banners still required.

  Choosing user tracking software

  The benefits and value of tracking website visitors are enormous, but not all tracking software is equal. Different tools have different core functionalities. For instance, some focus on user behaviour over traditional web analytics. Others offer detailed website performance data but offer little in the way of visitor information. It’s a good idea to start by identifying your company’s most important tracking goals.

  Along with core features, look for useful tools to experiment with and optimise your website with. For example, Matomo enables A/B testing while many other tools do not.

  

  Along with users of your website, you also need to think about the employees who will be using the tracking software. The interface can have a big impact on the value you get from a tool. Matomo’s session recording functionality, for example, not only provides you with video but with a colour-coded timeline identifying important user actions.

  

  Privacy standards and compliance should also be a part of the conversation. Different tools use different tracking methods, impacting accuracy and security and can even cause legal trouble. You should consider which data privacy laws you are subject to, as well as the privacy expectations of your users.

  

  Some industries have especially high data security standards. Government and healthcare organisations, for example, may require visitor tracking software that is hosted on their premises. While there are many purely cloud-based software-as-a-service (SaaS) tracking tools, Matomo is available both On-Premise (also known as self-hosted) and in the Cloud.

  Frequently asked questions

  Here are answers to some of people’s most common questions about tracking website visitors.

  Can you track who visited your website ?

  In most cases, tracking your website’s traffic is possible. Still, the extent of the tracking depends on the visitor-tracking technology you use and the privacy settings and precautions the visitor uses. For example, some technologies can pinpoint users by IP address. In other cases, you may only have access to anonymized data.

  Is it legal to track someone’s IP address ?

  It is legal for websites and businesses to track someone’s IP address in the sense that they can identify that someone from the same IP address is visiting a page repeatedly. Under the General Data Protection Regulation (GDPR), IP addresses are considered personally identifiable information (PII). The GDPR mandates that websites only log and store a user’s IP address with the user’s consent.

  How do you find where visitors are clicking the most ?

  Heatmap tools are among the most common tools for learning where visitors click the most on your website. Heatmaps use colour-coding to show what parts of a web page users either click on or hover over the most.

  Unique tracking URLs are another way to determine what part of your website gets the most clicks. For example, if you have three links on a page that all go to the same destination, you can use tracking links to determine how many clicks each link generates.

  Matomo also offers a Tag Manager within the platform that lets you manage and unify all your tracking and marketing tags to find out where visitors are clicking.

  What is the best tool for website visitor tracking ?

  Like most tools, the best website visitor tracking tool depends on your needs. Each tool offers different functionalities, user interfaces and different levels of accuracy and privacy. Matomo is a good choice for companies that value privacy, compliance and accuracy.

  Tracking for powerful insights and better performance

  Tracking website visitors is now a well-ingrained part of business operations. From sales reps seeking to understand their leads to marketers honing their ad spend, tracking helps teams do their jobs better.

  Take the time to consider what you want to learn from website tracking and let those priorities guide your choice of visitor tracking software. Whatever your industry or needs, user privacy and compliance must be a priority.

  Find out how much detail and insight Matomo can give you with our free 21-day trial — no credit card required.

• How to Choose the Optimal Multi-Touch Attribution Model for Your Organisation

  13 mars 2023, par Erin — Analytics Tips

  If you struggle to connect the dots on your customer journeys, you are researching the correct solution. 

  Multi-channel attribution models allow you to better understand the users’ paths to conversion and identify key channels and marketing assets that assist them.

  That said, each attribution model has inherent limitations, which make the selection process even harder.

  This guide explains how to choose the optimal multi-touch attribution model. We cover the pros and cons of popular attribution models, main evaluation criteria and how-to instructions for model implementation. 

  Pros and Cons of Different Attribution Models 

  

  First Interaction 

  First Interaction attribution model (also known as first touch) assigns full credit to the conversion to the first channel, which brought in a lead. However, it doesn’t report other interactions the visitor had before converting.

  Marketers, who are primarily focused on demand generation and user acquisition, find the first touch attribution model useful to evaluate and optimise top-of-the-funnel (ToFU). 

  Pros 

  • Reflects the start of the customer journey
  • Shows channels that bring in the best-qualified leads 
  • Helps track brand awareness campaigns

  Cons 

  • Ignores the impact of later interactions at the middle and bottom of the funnel 
  • Doesn’t provide a full picture of users’ decision-making process 

  Last Interaction 

  Last Interaction attribution model (also known as last touch) shifts the entire credit allocation to the last channel before conversion. But it doesn’t account for the contribution of all other channels. 

  If your focus is conversion optimization, the last-touch model helps you determine which channels, assets or campaigns seal the deal for the prospect. 

  Pros 

  • Reports bottom-of-the-funnel events
  • Requires minimal data and configurations 
  • Helps estimate cost-per-lead or cost-per-acquisition

  Cons 

  • No visibility into assisted conversions and prior visitor interactions 
  • Overemphasise the importance of the last channel (which can often be direct traffic) 

  Last Non-Direct Interaction 

  Last Non-Direct attribution excludes direct traffic from the calculation and assigns the full conversion credit to the preceding channel. For example, a paid ad will receive 100% of credit for conversion if a visitor goes directly to your website to buy a product. 

  Last Non-Direct attribution provides greater clarity into the bottom-of-the-funnel (BoFU). events. Yet, it still under-reports the role other channels played in conversion. 

  Pros 

  • Improved channel visibility, compared to Last-Touch 
  • Avoids over-valuing direct visits
  • Reports on lead-generation efforts

  Cons 

  • Doesn’t work for account-based marketing (ABM) 
  • Devalues the quality over quantity of leads 

  Linear Model

  Linear attribution model assigns equal credit for a conversion to all tracked touchpoints, regardless of their impact on the visitor’s decision to convert.

  It helps you understand the full conversion path. But this model doesn’t distinguish between the importance of lead generation activities versus nurturing touches.

  Pros 

  • Focuses on all touch points associated with a conversion 
  • Reflects more steps in the customer journey 
  • Helps analyse longer sales cycles

  Cons 

  • Doesn’t accurately reflect the varying roles of each touchpoint 
  • Can dilute the credit if too many touchpoints are involved 

  Time Decay Model 

  Time decay models assumes that the closer a touchpoint is to the conversion, the greater its influence. Pre-conversion touchpoints get the highest credit, while the first ones are ranked lower (5%-5%-10%-15%-25%-30%).

  This model better reflects real-life customer journeys. However, it devalues the impact of brand awareness and demand-generation campaigns. 

  Pros 

  • Helps track longer sales cycles and reports on each touchpoint involved 
  • Allows customising the half-life of decay to improve reporting 
  • Promotes conversion optimization at BoFu stages

  Cons 

  • Can prompt marketers to curtail ToFU spending, which would translate to fewer qualified leads at lower stages
  • Doesn’t reflect highly-influential events at earlier stages (e.g., a product demo request or free account registration, which didn’t immediately lead to conversion)

  Position-Based Model 

  Position-Based attribution model (also known as the U-shaped model) allocates the biggest credit to the first and the last interaction (40% each). Then distributes the remaining 20% across other touches. 

  For many marketers, that’s the preferred multi-touch attribution model as it allows optimising both ToFU and BoFU channels. 

  Pros 

  • Helps establish the main channels for lead generation and conversion
  • Adds extra layers of visibility, compared to first- and last-touch attribution models 
  • Promotes budget allocation toward the most strategic touchpoints

  Cons 

  • Diminishes the importance of lead nurturing activities as more credit gets assigned to demand-gen and conversion-generation channels
  • Limited flexibility since it always assigns a fixed amount of credit to the first and last touchpoints, and the remaining credit is divided evenly among the other touchpoints

  How to Choose the Right Multi-Touch Attribution Model For Your Business 

  If you’re deciding which attribution model is best for your business, prepare for a heated discussion. Each one has its trade-offs as it emphasises or devalues the role of different channels and marketing activities.

  To reach a consensus, the best strategy is to evaluate each model against three criteria : Your marketing objectives, sales cycle length and data availability. 

  Marketing Objectives 

  Businesses generate revenue in many ways : Through direct sales, subscriptions, referral fees, licensing agreements, one-off or retainer services. Or any combination of these activities. 

  In each case, your marketing strategy will look different. For example, SaaS and direct-to-consumer (DTC) eCommerce brands have to maximise both demand generation and conversion rates. In contrast, a B2B cybersecurity consulting firm is more interested in attracting qualified leads (as opposed to any type of traffic) and progressively nurturing them towards a big-ticket purchase. 

  When selecting a multi-touch attribution model, prioritise your objectives first. Create a simple scoreboard, where your team ranks various channels and campaign types you rely on to close sales. 

  Alternatively, you can survey your customers to learn how they first heard about your company and what eventually triggered their conversion. Having data from both sides can help you cross-validate your assumptions and eliminate some biases. 

  Then consider which model would best reflect the role and importance of different channels in your sales cycle. Speaking of which….

  Sales Cycle Length 

  As shoppers, we spend less time deciding on a new toothpaste brand versus contemplating a new IT system purchase. Factors like industry, business model (B2C, DTC, B2B, B2BC), and deal size determine the average cycle length in your industry. 

  Statistically, low-ticket B2C sales can happen within just several interactions. The average B2B decision-making process can have over 15 steps, spread over several months. 

  That’s why not all multi-touch attribution models work equally well for each business. Time-decay suits better B2B companies, while B2C usually go for position-based or linear attribution. 

  Data Availability 

  Businesses struggle with multi-touch attribution model implementation due to incomplete analytics data. 

  Our web analytics tool captures more data than Google Analytics. That’s because we rely on a privacy-focused tracking mechanism, which allows you to collect analytics without showing a cookie consent banner in markets outside of Germany and the UK. 

  Cookie consent banners are mandatory with Google Analytics. Yet, almost 40% of global consumers reject it. This results in gaps in your analytics and subsequent inconsistencies in multi-touch attribution reports. With Matomo, you can compliantly collect more data for accurate reporting. 

  Some companies also struggle to connect collected insights to individual shoppers. With Matomo, you can cross-attribute users across browning sessions, using our visitors’ tracking feature. 

  When you already know a user’s identifier (e.g., full name or email address), you can track their on-site behaviours over time to better understand how they interact with your content and complete their purchases. Quick disclaimer, though, visitors’ tracking may not be considered compliant with certain data privacy laws. Please consult with a local authority if you have doubts. 

  How to Implement Multi-Touch Attribution

  Multi-touch attribution modelling implementation is like a “seek and find” game. You have to identify all significant touchpoints in your customers’ journeys. And sometimes also brainstorm new ways to uncover the missing parts. Then figure out the best way to track users’ actions at those stages (aka do conversion and events tracking). 

  Here’s a step-by-step walkthrough to help you get started. 

  Select a Multi-Touch Attribution Tool 

  The global marketing attribution software is worth $3.1 billion. Meaning there are plenty of tools, differing in terms of accuracy, sophistication and price.

  To make the right call prioritise five factors :

  • Available models : Look for a solution that offers multiple options and allows you to experiment with different modelling techniques or develop custom models. 
  • Implementation complexity : Some providers offer advanced data modelling tools for creating custom multi-touch attribution models, but offer few out-of-the-box modelling options. 
  • Accuracy : Check if the shortlisted tool collects the type of data you need. Prioritise providers who are less dependent on third-party cookies and allow you to identify repeat users. 
  • Your marketing stack : Some marketing attribution tools come with useful add-ons such as tag manager, heatmaps, form analytics, user session recordings and A/B testing tools. This means you can collect more data for multi-channel modelling with them instead of investing in extra software. 
  • Compliance : Ensure that the selected multi-attribution analytics software wouldn’t put you at risk of GDPR non-compliance when it comes to user privacy and consent to tracking/analysis. 

  Finally, evaluate the adoption costs. Free multi-channel analytics tools come with data quality and consistency trade-offs. Premium attribution tools may have “hidden” licensing costs and bill you for extra data integrations. 

  Look for a tool that offers a good price-to-value ratio (i.e., one that offers extra perks for a transparent price). 

  Set Up Proper Data Collection 

  Multi-touch attribution requires ample user data. To collect the right type of insights you need to set up : 

  • Website analytics : Ensure that you have all tracking codes installed (and working correctly !) to capture pageviews, on-site actions, referral sources and other data points around what users do on page. 
  • Tags : Add tracking parameters to monitor different referral channels (e.g., “facebook”), campaign types (e.g., ”final-sale”), and creative assets (e.g., “banner-1”). Tags help you get a clearer picture of different touchpoints. 
  • Integrations : To better identify on-site users and track their actions, you can also populate your attribution tool with data from your other tools – CRM system, A/B testing app, etc. 

  Finally, think about the ideal lookback window — a bounded time frame you’ll use to calculate conversions. For example, Matomo has a default windows of 7, 30 or 90 days. But you can configure a custom period to better reflect your average sales cycle. For instance, if you’re selling makeup, a shorter window could yield better results. But if you’re selling CRM software for the manufacturing industry, consider extending it.

  Configure Goals and Events 

  Goals indicate your main marketing objectives — more traffic, conversions and sales. In web analytics tools, you can measure these by tracking specific user behaviours. 

  For example : If your goal is lead generation, you can track :

  • Newsletter sign ups 
  • Product demo requests 
  • Gated content downloads 
  • Free trial account registration 
  • Contact form submission 
  • On-site call bookings 

  In each case, you can set up a unique tag to monitor these types of requests. Then analyse conversion rates — the percentage of users who have successfully completed the action. 

  To collect sufficient data for multi-channel attribution modelling, set up Goal Tracking for different types of touchpoints (MoFU & BoFU) and asset types (contact forms, downloadable assets, etc). 

  Your next task is to figure out how users interact with different on-site assets. That’s when Event Tracking comes in handy. 

  Event Tracking reports notify you about specific actions users take on your website. With Matomo Event Tracking, you can monitor where people click on your website, on which pages they click newsletter subscription links, or when they try to interact with static content elements (e.g., a non-clickable banner). 

  Using in-depth user behavioural reports, you can better understand which assets play a key role in the average customer journey. Using this data, you can localise “leaks” in your sales funnel and fix them to increase conversion rates.

  Test and Validated the Selected Model 

  A common challenge of multi-channel attribution modelling is determining the correct correlation and causality between exposure to touchpoints and purchases. 

  For example, a user who bought a discounted product from a Facebook ad would act differently than someone who purchased a full-priced product via a newsletter link. Their rate of pre- and post-sales exposure will also differ a lot — and your attribution model may not always accurately capture that. 

  That’s why you have to continuously test and tweak the selected model type. The best approach for that is lift analysis. 

  Lift analysis means comparing how your key metrics (e.g., revenue or conversion rates) change among users who were exposed to a certain campaign versus a control group. 

  In the case of multi-touch attribution modelling, you have to monitor how your metrics change after you’ve acted on the model recommendations (e.g., invested more in a well-performing referral channel or tried a new brand awareness Twitter ad). Compare the before and after ROI. If you see a positive dynamic, your model works great. 

  The downside of this approach is that you have to invest a lot upfront. But if your goal is to create a trustworthy attribution model, the best way to validate is to act on its suggestions and then test them against past results. 

  Conclusion

  A multi-touch attribution model helps you measure the impact of different channels, campaign types, and marketing assets on metrics that matter — conversion rate, sales volumes and ROI. 

  Using this data, you can invest budgets into the best-performing channels and confidently experiment with new campaign types. 

  As a Matomo user, you also get to do so without breaching customers’ privacy or compromising on analytics accuracy.

  Start using accurate multi-channel attribution in Matomo. Get your free 21-day trial now. No credit card required.