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• How to Conduct a Customer Journey Analysis (Step-by-Step)

  9 mai 2024, par Erin

  Your customers are everything.

  Treat them right, and you can generate recurring revenue for years. Treat them wrong ; you’ll be spinning your wheels and dealing with churn.

  How do you give your customers the best experience possible so they want to stick around ?

  Improve their customer experience.

  How ?

  By conducting a customer journey analysis.

  When you know how your customers experience your business, you can improve it to meet and exceed customer expectations.

  In this guide, we’ll break down how the customer journey works and give you a step-by-step guide to conduct a thorough customer journey analysis so you can grow your brand.

  What is a customer journey analysis ?

  Every customer you’ve ever served went on a journey to find you.

  From the moment they first heard of you, to the point that they became a customer. 

  Everything in between is the customer journey.

  A customer journey analysis is how you track and analyse how your customers use different channels to interact with your brand.

  

  Analysing your customer journey involves identifying the customer’s different touchpoints with your business so you can understand how it impacts their experience. 

  This means looking at every moment they interacted with your brand before, during and after a sale to help you gain actionable insights into their experience and improve it to reach your business objectives.

  Your customers go through specific customer touchpoints you can track. By analysing this customer journey from a bird’s eye view, you can get a clear picture of the entire customer experience.

  4 benefits of customer journey analysis

  Before we dive into the different steps involved in a customer journey analysis, let’s talk about why it’s vital to analyse the customer journey.

  By regularly analysing your customer journey, you’ll be able to improve the entire customer experience with practical insights, allowing you to :

  Understand your customers better

  What’s one key trait all successful businesses have ?

  They understand their customers.

  By analysing your customer journey regularly, you’ll gain new insights into their wants, needs, desires and behaviours, allowing you to serve them better. These insights will show you what led them to buy a product (or not).

  For example, through conducting a customer journey analysis, a company might find out that customers who come from LinkedIn are more likely to buy than those coming from Facebook.

  Find flaws in your customer journey

  Nobody wants to hear they have flaws. But the reality is your customer journey likely has a few flaws you could improve.

  By conducting customer journey analysis consistently, you’ll be able to pinpoint precisely where you’re losing prospects along the way. 

  For example, you may discover you’re losing customers through Facebook Ads. Or you may find your email strategy isn’t as good as it used to be.

  But it’s not just about the channel. It could be a transition between two channels. For example, you may have great engagement on Instagram but are not converting them into email subscribers. The issue may be that your transition between the two channels has a leak.

  Or you may find that prospects using certain devices (i.e., mobile, tablet, desktop) have lower conversions. This might be due to design and formatting issues across different devices.

  By looking closely at your customer journey and the different customer touchpoints, you’ll see issues preventing prospects from turning into leads or customers from returning to buy again as loyal customers.

  Gain insights into how you can improve your brand

  Your customer journey analysis won’t leave you with a list of problems. Instead, you’ll have a list of opportunities.

  Since you’ll be able to better understand your customers and where they’re falling off the sales funnel, you’ll have new insights into how you can improve the experience and grow your brand.

  For example, maybe you notice that your visitors are getting stuck at one stage of the customer journey and you’re trying to find out why.

  So, you leverage Matomo’s heatmaps, sessions recordings and scroll depth to find out more.

  In the case below, we can see that Matomo’s scroll map is showing that only 65% of the visitors are reaching the main call to action (to write a review). 

  

  To try to push for higher conversions and get more reviews, we could consider moving that button higher up on the page, ideally above the fold.

  Rather than guessing what’s preventing conversions, you can use user behaviour analytics to “step in our user’s shoes” so you can optimise faster and with confidence.

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  Grow your revenue

  By taking charge of your customer journey, you can implement different strategies that will help you increase your reach, gain more prospects, convert more prospects into customers and turn regulars into loyal customers.

  Using customer journey analysis will help you optimise those different touchpoints to maximise the ROI of your channels and get the most out of each marketing activity you implement.

  7 steps to conduct a customer journey analysis

  Now that you know the importance of conducting a customer journey analysis regularly, let’s dive into how to implement an analysis.

  Here are the seven steps you can take to analyse the customer journey to improve your customer experience :

  

  1. Map out your customer journey

  Your first step to conducting an effective customer journey analysis is to map your entire customer journey.

  Customer journey mapping means looking at several factors :

  • Buying process
  • Customer actions
  • Buying emotions
  • Buying pain points
  • Solutions

  Once you have an overview of your customer journey maps, you’ll gain insights into your customers, their interests and how they interact with your brand. 

  After this, it’s time to dive into the touchpoints.

  2. Identify all the customer touchpoints 

  To improve your customer journey, you need to know every touchpoint a customer can (and does) make with your brand.

  This means taking note of every single channel and medium they use to communicate with your brand :

  • Website
  • Social media
  • Search engines (SEO)
  • Email marketing
  • Paid advertising
  • And more

  Essentially, anywhere you communicate and interact with your customers is fair game to analyse.

  If you want to analyse your entire sales funnel, you can try Matomo, a privacy-friendly web analytics tool. 

  You should make sure to split up your touchpoints into different customer journey stages :

  • Awareness
  • Consideration
  • Conversion
  • Advocacy

  Then, it’s time to move on to how customers interact on these channels.

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  3. Measure how customers interact on each channel

  To understand the customer journey, you can’t just know where your customers interact with you. You end up learning how they’re interacting.

  This is only possible by measuring customer interactions.

  How ?

  By using a web analytics tool like Matomo.

  With Matomo, you can track every customer action on your website.

  This means anytime they :

  • Visit your website
  • View a web page
  • Click a link
  • Fill out a form
  • Purchase a product
  • View different media
  • And more

  You should analyse your engagement on your website, apps and other channels, like email and social media.

  4. Implement marketing attribution

  Now that you know where your customers are and how they interact, it’s time to analyse the effectiveness of each channel based on your conversion rates.

  Implementing marketing attribution (or multi-touch attribution) is a great way to do this.

  Attribution is how you determine which channels led to a conversion.

  While single-touch attribution models credit one channel for a conversion, marketing attribution gives credit to a few channels.

  For example, let’s say Bob is looking for a new bank. He sees an Instagram post and finds himself on HSBC’s website. After looking at a few web pages, he attends a webinar hosted by HSBC on financial planning and investment strategies. One week later, he gets an email from HSBC following up on the webinar. Then, he decides to sign up for HSBC’s online banking.

  Single touch attribution would attribute 100% of the conversion to email, which doesn’t show the whole picture. Marketing attribution would credit all channels : social media, website content, webinars and email.

  Matomo offers multiple attribution models. These models leverage different weighting factors, like time decay or linear, so that you can allocate credit to each touchpoint based on its impact.

  Matomo’s multi-touch attribution reports give you in-depth insights into how revenue is distributed across different channels. These detailed reports help you analyse each channel’s contribution to revenue generation so you can optimise the customer journey and improve business outcomes.

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  5. Use a funnels report to find where visitors are leaving

  Once you set up your marketing attribution, it’s time to analyse where visitors are falling off.

  You can leverage Matomo funnels to find out the conversion rate at each step of the journey on your website. Funnel reports can help you see exactly where visitors are falling through the cracks so you can increase conversions.

  6. Analyse why visitors aren’t converting

  Once you can see where visitors are leaving, you can start to understand why.

  For example, let’s say you analyse your funnels report in Matomo and see your landing page is experiencing the highest level of drop-offs.

  

  You can also use form analytics to find out why users aren’t converting on your landing pages – a crucial part of the customer journey.

  7. A/B test to improve the customer journey

  The final step to improve your customer journey is to conduct A/B tests. These are tests where you test one version of a landing page to see which one converts better, drives more traffic, or generates more revenue.

  For example, you could create two versions of a header on your website and drive 50% of your traffic to each version. Then, once you’ve got your winner, you can keep that as your new landing page.

  

  Using the data from your A/B tests, you can optimise your customer journey to help convert more prospects into customers.

  Use Matomo to improve your customer journey analysis

  Now that you understand why it’s important to conduct customer journey analysis regularly and how it works, it’s time to put this into practice.

  To improve the customer journey, you need to understand what’s happening at each stage of your funnel. 

  Matomo gives you insights into your customer journey so you can improve website performance and convert more visitors into customers.

  Used by over 1 million websites, Matomo is the leading privacy-friendly web analytics solution in the world. 

  Matomo provides you with accurate, unsampled data so you understand exactly what’s going on with your website performance.

  The best part ?

  It’s easy to use and is compliant with the strictest privacy regulations.

  Try Matomo free for 21-days and start Improving your customer journey. No credit card required.

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  21 day free trial. No credit card required.

  
  

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• Linear Attribution Model : What Is It and How Does It Work ?

  16 février 2024, par Erin

  Want a more in-depth way to understand the effectiveness of your marketing campaigns ? Then, the linear attribution model could be the answer.

  Although you can choose from several different attribution models, a linear model is ideal for giving value to every touchpoint along the customer journey. It can help you identify your most effective marketing channels and optimise your campaigns. 

  So, without further ado, let’s explore what a linear attribution model is, when you should use it and how you can get started. 

  What is a linear attribution model ?

  A linear attribution model is a multi-touch method of marketing attribution where equal credit is given to each touchpoint. Every marketing channel used across the entire customer journey gets credit, and each is considered equally important. 

  So, if a potential customer has four interactions before converting, each channel gets 25% of the credit.

  

  Let’s look at how linear attribution works in practice using a hypothetical example of a marketing manager, Sally, who is looking for an alternative to Google Analytics. 

  Sally starts her conversion path by reading a Matomo article comparing Matomo to Google Analytics she finds when searching on Google. A few days later she signs up for a webinar she saw on Matomo’s LinkedIn page. Two weeks later, Sally gets a sign-off from her boss and decides to go ahead with Matomo. She visits the website and starts a free trial by clicking on one of the paid Google Ads. 

  Using a linear attribution model, we credit each of the channels Sally uses (organic traffic, organic social, and paid ads), ensuring no channel is overlooked in our marketing analysis. 

  Are there other types of attribution models ?

  Absolutely. There are several common types of attribution models marketing managers can use to measure the impact of channels in different ways. 

  

  • First interaction : Also called a first-touch attribution model, this method gives all the credit to the first channel in the customer journey. This model is great for optimising the top of your sales funnel.
  • Last interaction : Also called a last-touch attribution model, this approach gives all the credit to the last channel the customer interacts with. It’s a great model for optimising the bottom of your marketing funnel. 
  • Last non-direct interaction : This attribution model excludes direct traffic and credits the previous touchpoint. This is a fantastic alternative to a last-touch attribution model, especially if most customers visit your website before converting. 
  • Time decay attribution model : This model adjusts credit according to the order of the touchpoints. Those nearest the conversion get weighted the highest. 
  • Position-based attribution model : This model allocates 40% of the credit to the first and last touchpoints and splits the remaining 20% evenly between every other interaction.

  Why use a linear attribution model ?

  Marketing attribution is vital if you want to understand which parts of your marketing strategy are working. All of the attribution models described above can help you achieve this to some degree, but there are several reasons to choose a linear attribution model in particular. 

  It uses multi-touch attribution

  Unlike single-touch attribution models like first and last interaction, linear attribution is a multi-touch attribution model that considers every touchpoint. This is vital to get a complete picture of the modern customer journey, where customers interact with companies between 20 and 500 times. 

  Single-touch attribution models can be misleading by giving conversion credit to a single channel, especially if it was the customer’s last use. In our example above, Sally’s last interaction with our brand was through a paid ad, but it was hardly the most important. 

  It’s easy to understand

  Attribution models can be complicated, but linear attribution is easy to understand. Every touchpoint gets the same credit, allowing you to see how your entire marketing function works. This simplicity also makes it easy for marketers to take action. 

  It’s great for identifying effective marketing channels

  Because linear attribution is one of the few models that provides a complete view of the customer journey, it’s easy to identify your most common and influential touchpoints. 

  It accounts for the top and bottom of your funnel, so you can also categorise your marketing channels more effectively and make more informed decisions. For example, PPC ads may be a more common bottom-of-the-full touchpoint and should, therefore, not be used to target broad, top-of-funnel search terms.

  Are there any reasons not to use linear attribution ?

  Linear attribution isn’t perfect. Like all attribution models, it has its weaknesses. Specifically, linear attribution can be too simple, dilute conversion credit and unsuitable for long sales cycles.

  

  It can be too simple

  Linear attribution lacks nuance. It only considers touchpoints while ignoring other factors like brand image and your competitors. This is true for most attribution models, but it’s still important to point it out. 

  It can dilute conversion credit

  In reality, not every touchpoint impacts conversions to the same extent. In the example above, the social media post promoting the webinar may have been the most effective touchpoint, but we have no way of measuring this. 

  The risk with using a linear model is that credit can be underestimated and overestimated — especially if you have a long sales cycle. 

  It’s unsuitable for very long sales cycles

  Speaking of long sales cycles, linear attribution models won’t add much value if your customer journey contains dozens of different touchpoints. Credit will get diluted to the point where analysis becomes impossible, and the model will also struggle to measure the precise ways certain touchpoints impact conversions. 

  Should you use a linear attribution model ?

  A linear attribution model is a great choice for any company with shorter sales cycles or a reasonably straightforward customer journey that uses multiple marketing channels. In these cases, it helps you understand the contribution of each touchpoint and find your best channels. 

  It’s also a practical choice for small businesses and startups that don’t have a team of data scientists on staff or the budget to hire outside help. Because it’s so easy to set up and understand, anyone can start generating insights using this model. 

  How to set up a linear attribution model

  Are you sold on the idea of using a linear attribution model ? Then follow the steps below to get started :

  

  Choose a marketing attribution tool

  Given the market is worth $3.1 billion, you won’t be surprised to learn there are plenty of tools to choose from. But choose carefully. The tool you pick can significantly impact your success with attribution modelling. 

  Take Google Analytics, for instance. While GA4 offers several marketing attribution models for free, including linear attribution, it lacks accuracy due to cookie consent rejection and data sampling. 

  Accurate marketing attribution is included as a feature in Matomo Cloud and is available as a plugin for Matomo On-Premise users. We support a full range of attribution models that use 100% accurate data because we don’t use data sampling, and cookie consent isn’t an issue (with the exception of Germany and the UK). That means you can trust our insights.

  Matomo’s marketing attribution is available out of the box, and we also provide access to raw data, allowing you to develop your custom attribution model. 

  Collect data

  The quality of your marketing attribution also depends on the quality and quantity of your data. It’s why you need to avoid a platform that uses data sampling. 

  This should include :

  • General data from your analytics platform, like pages visited and forms filled
  • Goals and conversions, which we’ll discuss in more detail in the next step
  • Campaign tracking data so you can monitor the behaviour of traffic from different referral channels
  • Behavioural data from features like Heatmaps or Session Recordings

  Set up goals and conversions

  You can’t assign conversion values to customer journey touchpoints if you don’t have conversion goals in place. That’s why the next step of the process is to set up conversion tracking in your web analytics platform. 

  Depending on your type of business and the product you sell, conversions could take one of the following forms :

  • A product purchase
  • Signing up for a webinar
  • Downloading an ebook
  • Filling in a form
  • Starting a free trial

  Setting up these kinds of goals is easy if you use Matomo. 

  Just head to the Goals section of the dashboard, click Manage Goals and then click the green Add A New Goal button. 

  Fill in the screen below, and add a Goal Revenue at the bottom of the page. Doing so will mean Matomo can automatically calculate the value of each touchpoint when using your attribution model. 

  

  If your analytics platform allows it, make sure you also set up Event Tracking, which will allow you to analyse how many users start to take a desired action (like filling in a form) but never complete the task. 

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  Test and validate

  As we’ve explained, linear attribution is a great model in some scenarios, but it can fall short if you have a long or complex sales funnel. Even if you’re sure it’s the right model for your company, testing and validating is important. 

  Ideally, your chosen attribution tool should make this process pretty straightforward. For example, Matomo’s Marketing Attribution feature makes comparing and contrasting three different attribution models easy. 

  Here we compare the performance of three attribution models—linear, first-touch, and last-non-direct—in Matomo’s Marketing Attribution dashboard, providing straightforward analysis.

  

  If you think linear attribution accurately reflects the value of your channels, you can start to analyse the insights it generates. If not, then consider using another attribution model.

  Don’t forget to take action from your marketing efforts, either. Linear attribution helps you spot the channels that contribute most to conversions, so allocate more resources to those channels and see if you can improve your conversion rate or boost your ROI. 

  Make the most of marketing attribution with Matomo

  A linear attribution model lets you measure every touchpoint in your customer journey. It’s an easy attribution model to start with and lets you identify and optimise your most effective marketing channels. 

  However, accurate data is essential if you want to benefit the most from marketing attribution data. If your web analytics solution doesn’t play nicely with cookies or uses sampled data, then your linear model isn’t going to tell you the whole story. 

  That’s why over 1 million sites trust Matomo’s privacy-focused web analytics, ensuring accurate data for a comprehensive understanding of customer journeys.

  Now you know what linear attribution modelling is, start employing the model today by signing up for a free 21-day trial, no credit card required. 

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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• Benefits and Shortcomings of Multi-Touch Attribution

  13 mars 2023, par Erin — Analytics Tips

  Few sales happen instantly. Consumers take their time to discover, evaluate and become convinced to go with your offer. 

  Multi-channel attribution (also known as multi-touch attribution or MTA) helps businesses better understand which marketing tactics impact consumers’ decisions at different stages of their buying journey. Then double down on what’s working to secure more sales. 

  Unlike standard analytics, multi-channel modelling combines data from various channels to determine their cumulative and independent impact on your conversion rates. 

  The main benefit of multi-touch attribution is obvious : See top-performing channels, as well as those involved in assisted conversions. The drawback of multi-touch attribution : It comes with a more complex setup process. 

  If you’re on the fence about getting started with multi-touch attribution, here’s a summary of the main arguments for and against it. 

  What Are the Benefits of Multi-Touch Attribution ?

  Remember an old parable of blind men and an elephant ?

  Each one touched the elephant and drew conclusions about how it might look. The group ended up with different perceptions of the animal and thought the others were lying…until they decided to work together on establishing the truth.

  Multi-channel analytics works in a similar way : It reconciles data from various channels and campaign types into one complete picture. So that you can get aligned on the efficacy of different campaign types and gain some other benefits too. 

  Better Understanding of Customer Journeys 

  On average, it takes 8 interactions with a prospect to generate a conversion. These interactions happen in three stages : 

  • Awareness : You need to introduce your company to the target buyers and pique their interest in your solution (top-of-the-funnel). 
  • Consideration : The next step is to channel this casual interest into deliberate research and evaluation of your offer (middle-of-the-funnel). 
  • Decision : Finally, you need to get the buyer to commit to your offer and close the deal (bottom-of-the-funnel). 

  You can analyse funnels using various attribution models — last-click, fist-click, position-based attribution, etc. Each model, however, will spotlight the different element(s) of your sales funnel. 

  For example, a single-touch attribution model like last-click zooms in on the bottom-of-the-funnel stage. You can evaluate which channels (or on-site elements) sealed the deal for the prospect. For example, a site visitor arrived from an affiliate link and started a free trial. In this case, the affiliate (referral traffic) gets 100% credit for the conversion. 

  This measurement tactic, however, doesn’t show which channels brought the customer to the very bottom of your funnel. For instance, they may have interacted with a social media post, your landing pages or a banner ad before that. 

  Multi-touch attribution modelling takes funnel analysis a notch further. In this case, you map more steps in the customer journey — actions, events, and pages that triggered a visitor’s decision to convert — in your website analytics tool.

  

  Then, select a multi-touch attribution model, which provides more backward visibility aka allows you to track more than one channel, preceding the conversion. 

  For example, a Position Based attribution model reports back on all interactions a site visitor had between their first visit and conversion. 

  A prospect first lands at your website via search results (Search traffic), which gets a 40% credit in this model. Two days later, the same person discovers a mention of your website on another blog and visits again (Referral traffic). This time, they save the page as a bookmark and revisit it again in two more days (Direct traffic). Each of these channels will get a 10% credit. A week later, the prospect lands again on your site via Twitter (Social) and makes a request for a demo. Social would then receive a 40% credit for this conversion. Last-click would have only credited social media and first-click — search engines. 

  The bottom line : Multi-channel attribution models show how different channels (and marketing tactics) contribute to conversions at different stages of the customer journey. Without it, you get an incomplete picture.

  Improved Budget Allocation 

  Understanding causal relationships between marketing activities and conversion rates can help you optimise your budgets.

  First-click/last-click attribution models emphasise the role of one channel. This can prompt you toward the wrong conclusions. 

  For instance, your Facebook ads campaigns do great according to a first-touch model. So you decide to increase the budget. What you might be missing though is that you could have an even higher conversion rate and revenue if you fix “funnel leaks” — address high drop-off rates during checkout, improve page layout and address other possible reasons for exiting the page.

  

  By knowing when and why people abandon their purchase journey, you can improve your marketing velocity (aka the speed of seeing the campaign results) and your marketing costs (aka the budgets you allocate toward different assets, touchpoints and campaign types). 

  Or as one of the godfathers of marketing technology, Dan McGaw, explained in a webinar :

  “Once you have a multi-touch attribution model, you [can] actually know the return on ad spend on a per-campaign basis. Sometimes, you can get it down to keywords. Sometimes, you can get down to all kinds of other information, but you start to realise, “Oh, this campaign sucks. I should shut this off.” And then really, that’s what it’s about. It’s seeing those campaigns that suck and turning them off and then taking that budget and putting it into the campaigns that are working”.

  More Accurate Measurements 

  The big boon of multi-channel marketing attribution is that you can zoom in on various elements of your funnel and gain granular data on the asset’s performance. 

  In other words : You get more accurate insights into the different elements involved in customer journeys. But for accurate analytics measurements, you must configure accurate tracking. 

  Define your objectives first : How do you want a multi-touch attribution tool to help you ? Multi-channel attribution analysis helps you answer important questions such as :

  • How many touchpoints are involved in the conversions ? 
  • How long does it take for a lead to convert on average ? 
  • When and where do different audience groups convert ? 
  • What is your average win rate for different types of campaigns ?

  Your objectives will dictate which multi-channel modelling approach will work best for your business — as well as the data you’ll need to collect. 

  At the highest level, you need to collect two data points :

  • Conversions : Desired actions from your prospects — a sale, a newsletter subscription, a form submission, etc. Record them as tracked Goals. 
  • Touchpoints : Specific interactions between your brand and targets — specific page visits, referral traffic from a particular marketing channel, etc. Record them as tracked Events. 

  Your attribution modelling software will then establish correlation patterns between actions (conversions) and assets (touchpoints), which triggered them. 

  The accuracy of these measurements, however, will depend on the quality of data and the type of attribution modelling used. 

  Data quality stands for your ability to procure accurate, complete and comprehensive information from various touchpoints. For instance, some data won’t be available if the user rejected a cookie consent banner (unless you’re using a privacy-focused web analytics tool like Matomo). 

  Different attribution modelling techniques come with inherent shortcomings too as they don’t accurately represent the average sales cycle length or track visitor-level data, which allows you to understand which customer segments convert best.

  Learn more about selecting the optimal multi-channel attribution model for your business.

  What Are the Limitations of Multi-Touch Attribution ?

  Overall, multi-touch attribution offers a more comprehensive view of the conversion paths. However, each attribution model (except for custom ones) comes with inherent assumptions about the contribution of different channels (e.g,. 25%-25%-25%-25% in linear attribution or 40%-10%-10%-40% in position-based attribution). These conversion credit allocations may not accurately represent the realities of your industry. 

  Also, most attribution models don’t reflect incremental revenue you gain from existing customers, which aren’t converting through analysed channels. For example, account upgrades to a higher tier, triggered via an in-app offer. Or warranty upsell, made via a marketing email. 

  In addition, you should keep in mind several other limitations of multi-touch attribution software.

  Limited Marketing Mix Analysis 

  Multi-touch attribution tools work in conjunction with your website analytics app (as they draw most data from it). Because of that, such models inherit the same visibility into your marketing mix — a combo of tactics you use to influence consumer decisions.

  Multi-touch attribution tools cannot evaluate the impact of :

  • Dark social channels 
  • Word-of-mouth 
  • Offline promotional events
  • TV or out-of-home ad campaigns 

  If you want to incorporate this data into your multi-attribution reporting, you’ll have to procure extra data from other systems — CRM, ad measurement partners, etc, — and create complex custom analytics models for its evaluation.

  Time-Based Constraints 

  Most analytics apps provide a maximum 90-day lookback window for attribution. This can be short for companies with longer sales cycles. 

  

  Marketing channels can be overlooked or underappreciated when your attribution window is too short. Because of that, you may curtail spending on brand awareness campaigns, which, in turn, will reduce the number of people entering the later stages of your funnel. 

  At the same time, many businesses would also want to track a look-forward window — the revenue you’ll get from one customer over their lifetime. In this case, not all tools may allow you to capture accurate information on repeat conversions — through re-purchases, account tier updates, add-ons, upsells, etc. 

  Again, to get an accurate picture you’ll need to understand how far into the future you should track conversions. Will you only record your first sales as a revenue number or monitor customer lifetime value (CLV) over 3, 6 or 12 months ? 

  The latter is more challenging to do. But CLV data can add another depth of dimension to your modelling accuracy. With Matomo, you set up this type of tracking by using our visitors’ tracking feature. We can help you track select visitors with known identifiers (e.g. name or email address) to discover their visiting patterns over time. 

  

  Limited Access to Raw Data 

  In web analytics, raw data stands for unprocessed website visitor information, stripped from any filters, segmentation or sampling applied. 

  Data sampling is a practice of analysing data subsets (instead of complete records) to extrapolate findings towards the entire data set. Google Analytics 4 applies data sampling once you hit over 500k sessions at the property level. So instead of accurate, real-life reporting, you receive approximations, generated by machine learning models. Data sampling is one of the main reasons behind Google Analytics’ accuracy issues. 

  In multi-channel attribution modelling, usage of sampled data creates further inconsistencies between the reports and the actual state of affairs. For instance, if your website generates 5 million page views, GA multi-touch analytical reports are based on the 500K sample size aka only 90% of the collected information. This hardly represents the real effect of all marketing channels and can lead to subpar decision-making. 

  With Matomo, the above is never an issue. We don’t apply data sampling to any websites (no matter the volume of traffic) and generate all the reports, including multi-channel attribution ones, based on 100% real user data. 

  AI Application 

  On the other hand, websites with smaller traffic volumes often have limited sampling datasets for building attribution models. Some tracking data may also be not available because the visitor rejected a cookie banner, for instance. On average, less than 50% of users in Australia, France, Germany, Denmark and the US among other countries always consent to all cookies. 

  To compensate for such scenarios, some multi-touch attribution solutions apply AI algorithms to “fill in the blanks”, which impacts the reporting accuracy. Once again, you get approximate data of what probably happened. However, Matomo is legally exempt from showing a cookie consent banner in most EU markets. Meaning you can collect 100% accurate data to make data-driven decisions.

  Difficult Technical Implementation 

  Ever since attribution modelling got traction in digital marketing, more and more tools started to emerge.

  

  Most web analytics apps include multi-touch attribution reports. Then there are standalone multi-channel attribution platforms, offering extra features for conversion rate optimization, offline channel tracking, data-driven custom modelling, etc. 

  Most advanced solutions aren’t available out of the box. Instead, you have to install several applications, configure integrations with requested data sources, and then use the provided interfaces to code together custom data models. Such solutions are great if you have a technical marketer or a data science team. But a steep learning curve and high setup costs make them less attractive for smaller teams. 

  Conclusion 

  Multi-touch attribution modelling lifts the curtain in more steps, involved in various customer journeys. By understanding which touchpoints contribute to conversions, you can better plan your campaign types and budget allocations. 

  That said, to benefit from multi-touch attribution modelling, marketers also need to do the preliminary work : Determine the key goals, set up event and conversion tracking, and then — select the optimal attribution model type and tool. 

  Matomo combines simplicity with sophistication. We provide marketers with familiar, intuitive interfaces for setting up conversion tracking across the funnel. Then generate attribution reports, based on 100% accurate data (without any sampling or “guesstimation” applied). You can also get access to raw analytics data to create custom attribution models or plug it into another tool ! 

  Start using accurate, easy-to-use multi-channel attribution with Matomo. Start your free 21-day trial now. No credit card requried.