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  • Top 5 Customer Segmentation Software in 2024

    12 mars 2024, par Erin

    In marketing, we all know the importance of reaching the right customer with the right message at the right time. That’s how you cut through the noise.

    For that, you need data on your customers — even though gathering the data is not enough. You can have all the data worldwide, but that raises an ethical responsibility and the need to make sense of it.

    Enter customer segmentation software — the answer to delivering personalised customer experiences at scale. 

    This article lists some of the best customer segmentation tools currently in the market. 

    We’ll also go over the benefits of using such tools and how you can choose the best one for your business.

    Let’s get started !

    What is customer segmentation software ?

    Customer segmentation software is a tool that helps businesses analyse customer data and group them based on common characteristics like age, income, and buying habits.

    The main goal of customer segmentation is to gain deeper insights into customer behaviours and preferences. This helps create targeted marketing and product strategies that fit each group and makes it easier to predict how customers will behave in the future.

    Different customer groups

    Benefits of a customer segmentation software

    Understanding your customers is the cornerstone of effective marketing, and customer segmentation software plays a pivotal role in this endeavour. 

    You can deliver more targeted and relevant marketing campaigns by dividing your audience into distinct groups based on shared characteristics. 

    Specifically, here are the main benefits of using customer segmentation tools :

    • Understand your audience better : The software helps businesses group customers with common traits to better understand their preferences and behaviour.
    • Make data-driven decisions : Base your business and marketing decisions on data analytics.
    • Aid product development : Insights from segmentation analytics can guide the creation of products that meet specific customer group needs.
    • Allocate your resources efficiently : Focusing on the customer segments that generate the most revenue leads to more effective and strategic use of your marketing resources.

    Best customer segmentation software in 2024 

    In this section, we go over the top customer segmentation tools in 2024. 

    We’ll look at these tools’ key features and pros and cons.

    1. Matomo

    Matomo dashboard

    Matomo is a comprehensive web analytics tool that merges traditional web analytics, such as tracking pageviews and visitor bounce rates, with more advanced web analytics features for tracking user behaviour. 

    With robust segmentation features, users can filter website traffic based on criteria such as location and device type, enabling them to analyse specific visitor groups and their behaviour. Users can create custom segments to analyse specific groups of visitors and their behaviour.

    Presenting as the ethical alternative to Google Analytics, Matomo emphasises transparency, 100% accurate data, and compliance with privacy laws.

    Key features

    • Heatmaps and Session Recordings : Matomo provides tools that allow businesses to understand website user interactions visually. This insight is crucial for optimising user experience and increasing conversions.
    • Form Analytics : This feature in Matomo tracks how users interact with website forms, helping businesses understand user behaviour in detail and improve form design and functionality.
    • User Flow Analysis : The tool tracks the journey of a website’s visitors, highlighting the paths taken and where users drop off. This is key for optimising website structure for better user experience and more conversions.
    • A/B Testing : Businesses can use Matomo to test different versions of web pages, determining which is more effective in driving conversions.
    • Conversion Funnels : This feature allows businesses to visualise and optimise the steps customers take toward conversion, identifying areas for improvement.

    Pros 

    • Affordability : With plans starting at $19 per month, Matomo is a cost-effective solution for CRO.
    • Free support : Matomo provides free email support to all Matomo Cloud users.
    • Open-source benefits : Being open-source, Matomo offers enhanced security, privacy, customisation options, and a supportive community.
    • Hosting options : Matomo is available either as a self-hosted solution or cloud-hosted.

    Cons

    • Cost for advanced features : Access to advanced features may incur additional costs for Matomo On-Premise users, although the On-Premise solution itself is free.
    • Technical knowledge required : The self-hosted version of Matomo requires technical knowledge for effective management.

    Try Matomo for Free

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

    No credit card required

    2. Google Analytics 

    GA dashboard

    Google Analytics 4 (GA4) comprehensively understands website and app performance. It focuses on event-based data collection, allowing businesses to understand user interactions across platforms. 

    Similarly to Matomo, GA4 provides features that allow businesses to segment their audience based on various criteria such as demographics, behaviours, events, and more.

    Key features

    • Event-based tracking : GA4’s shift to an event-based model allows for a flexible and predictive analysis of user behaviour. This includes a detailed view of user interactions on websites and apps.
    • Machine Learning and Smarter Insights : GA4 uses machine learning to automatically detect trends, estimate purchase probabilities and provide marketing insights.
    • Google Ads integration : The integration with Google Ads in GA4 enables tracking customer interactions from first ad engagement, providing a holistic view of the customer experience across various platforms.
    • Customer-centric measurements : GA4 collects data as events, covering a wide range of user interactions and offering a comprehensive view of customer behaviour.
    • Pathing reports : GA4 introduces new pathing reports, allowing detailed user flow analysis through websites and apps.
    • Audiences and filters : GA4 allows the creation of audiences based on specific criteria and the application of filters to segment and refine data analysis.

    Pros 

    • Integration with various platforms, including Google Ads, enhances cross-platform user journey analysis.
    • GA4 has a clean reporting interface, making it easier for marketers to identify key trends and data irregularities.
    • Google Analytics has an active community with an abundance of educational resources available for users.

    Cons

    • Complexity for beginners : The wide range of features and new event-based model might overwhelm users new to analytics tools.
    • Dependence on machine learning : Reliance on machine learning for insights and predictions may require trust in the tool’s data processing and large volumes of traffic for accuracy.
    • Transition from UA to GA4 : Users familiar with Universal Analytics (UA) might find the transition to GA4 challenging due to differences in features and data models.

    3. HubSpot

    Hubspot dashboard

    HubSpot is a marketing and sales software that helps businesses attract visitors and turn them into paying customers. 

    It supports various business processes, from social media posts to email marketing, sales, and customer service. HubSpot organises and tracks user interactions across different channels, providing a unified and efficient approach to customer relationship management (CRM) and customer segmentation.

    Businesses can leverage HubSpot’s customer segmentation through lists, workflows, and smart content.

    Key features

    • Integration capabilities : HubSpot offers over 1,000 integrations in its ecosystem, ensuring seamless connectivity across various marketing, sales, and service tools, which helps maintain data consistency and reduces manual efforts.
    • Segmentation and personalisation : HubSpot allows businesses to deliver personalised content and interactions based on customer behaviour and preferences, using its robust CRM features and advanced automation capabilities.

    Pros 

    • Comprehensive support : HubSpot offers a range of support options, including a knowledge base, real-time chat, and more.
    • User-friendly interface : The platform is designed for ease of use, ensuring a smooth experience even for less tech-savvy users.
    • Personalisation capabilities : HubSpot provides personalised marketing, sales and service experiences, leveraging customer data effectively.

    Cons

    • High price point : HubSpot can be expensive, especially as you scale up and require more advanced features.
    • Steep learning curve : For businesses new to such comprehensive platforms, there might be an initial learning curve to utilise its features effectively.

    4. Klaviyo

    Klaviyo dashboard

    Klaviyo is a marketing automation software primarily focused on email and SMS messaging for e-commerce businesses. It’s designed to personalise and optimise customer communication. 

    Klaviyo integrates with e-commerce platforms like Shopify, making it a go-to solution for online stores. Its strength lies in its ability to use customer data to deliver targeted and effective marketing campaigns.

    Key features

    • Email marketing automation : Klaviyo allows users to send automated and personalised emails based on customer behaviour and preferences. This feature is crucial for e-commerce businesses in nurturing leads and maintaining customer engagement.
    • SMS marketing : It includes SMS messaging capabilities, enabling businesses to engage customers directly through text messages.
    • Segmentation and personalisation : Klaviyo offers advanced segmentation tools that enable businesses to categorise customers based on their behaviour, preferences and purchase history, facilitating highly targeted marketing efforts.
    • Integration with e-commerce platforms : Klaviyo integrates with popular e-commerce platforms like Shopify, Magento, and WooCommerce, allowing easy data synchronisation and campaign management.

    Pros 

    • Enhanced e-commerce integration : Klaviyo’s deep integration with e-commerce platforms greatly benefits online retailers regarding ease of use and campaign effectiveness.
    • Advanced segmentation and personalisation : The platform’s strong segmentation capabilities enable businesses to tailor their marketing messages more effectively.
    • Robust automation features : Klaviyo’s automation tools are powerful and user-friendly, saving time and improving marketing efficiency.

    Cons

    • Cost : Klaviyo can be more expensive than other options in this list, particularly as you scale up and add more contacts.
    • Complexity for beginners : The platform’s wide range of features and advanced capabilities might overwhelm beginners or small businesses with simpler needs.

    5. UserGuiding

    UserGuiding dashboard

    UserGuiding is a no-code product adoption tool that lets businesses create in-app user walkthroughs, guides, and checklists to onboard, engage, and retain users.

    UserGuiding facilitates customer segmentation by enabling businesses to create segmented onboarding flows, analyse behavioural insights, deliver personalised guidance, and collect feedback tailored to different user segments.

    Key features

    • In-app walkthroughs, guides and checklists : UserGuiding has multiple features that can promote product adoption early in the user journey.
    • In-app messaging : UserGuiding offers in-app messaging to help users learn more about the product and various ways to get value.
    • User feedback : UserGuiding allows businesses to gather qualitative feedback to streamline the adoption journey for users.

    Pros 

    • User-friendly interface
    • Customisable onboarding checklists
    • Retention analytics

    Cons

    • Need for technical expertise to maximise all features
    • Limited customisation options for less tech-savvy users

    What to look for in a customer segmentation software 

    When choosing a customer segmentation software, choosing the right one for your specific business needs is important. 

    Here are a few factors to consider when choosing your customer segmentation tool :

    1. Ease of use : Select a tool with an intuitive interface that simplifies navigation. This enhances the user experience, making complex tasks more manageable. Additionally, responsive customer support is crucial. It ensures that issues are promptly resolved, contributing to a smoother operation.
    2. Scalability and flexibility : Your chosen tool should adjust to your needs. A flexible tool like Matomo can adjust to your growing requirements, offering capabilities that evolve as your business expands.
    3. Integration capabilities : The software should seamlessly integrate with your existing systems, such as CRM, marketing, and automation platforms. 
    4. Advanced analytics and reporting : Assess the software’s capability to analyse and interpret complex data sets, without relying on machine learning to fill data gaps. A robust tool should provide accurate insights and detailed reports, enabling you to make informed decisions based on real data.
    5. Privacy and security considerations : Data security is paramount in today’s digital landscape. Look for features like data encryption, security storage, and adherence to privacy standards like GDPR and CCPA compliance
    6. Reviews and recommendations : Before making a decision, consider the reputation of the software providers. Look for reviews and recommendations from other users, especially those in similar industries. This can provide real-world insights into the software’s performance and reliability.
    List of factors to consider in a customer segmentation tool

    Leverage Matomo’s segmentation capabilities to deliver personalised experiences

    Segmentation is the best place to start if you want to deliver personalised customer experiences. There are several customer segmentation software in the market. But they’re not all the same.

    In this article, we reviewed the top segmentation tools — based on factors like their user base, features, and ethical data privacy considerations.

    Ideally, you want a tool to support your evolving business and segmentation needs. Not to mention one that cares about your customers’ privacy and ensures you stay compliant. 

    Enter Matomo at the top of the list. You can leverage Matomo’s accurate insights and comprehensive segmentation capabilities without compromising on privacy. Try it free for 21-days. No credit card required.

  • 7 Best Marketing Attribution Software in 2024

    22 février 2024, par Erin

    It can be hard to accurately track the impact of your marketing efforts across marketing channels and campaigns. That’s where marketing attribution software comes in. 

    It goes beyond basic web analytics solutions that just look at the final click. Instead, it shows how different channels, content, and ads are performing at every step of the buyer’s journey, which gives a more accurate picture than just focusing on the last click.

    In this guide, we’ll cover the basics of marketing attribution, list the top marketing attribution software and explain how the issue of privacy is transforming the web analytics industry.

    What is marketing attribution ?

    Marketing attribution is the process of assigning credit to each touchpoint in a buyer’s journey that leads to a desired action (such as a conversion or sale) in order to understand the effectiveness of various marketing channels and campaigns in influencing the customer’s decision-making process.

    Marketers use software tools like website analytics to to track and analyse customer interactions across different touchpoints, allowing them to attribute conversions or sales to specific marketing efforts and optimise their strategies and budgets accordingly.

    Why is marketing attribution so important ?

    If you don’t track your campaigns correctly, it’s easy to spend thousands (or even millions) in an ineffective way. A 2022 survey by Australian marketing agency Next&Co revealed their clients wasted AU$5.46 billion in ineffective ad spend.

    Illustrated statistic showing how much ad spend was wasted in 2022

    That’s 41% of all the ad spend tracked by Next&Co in 2022. A wasted marketing spend percentage this high isn’t exactly a recipe for a high marketing return on investment (ROI). And yet, it’s the average.

    Why is that ? 

    Most companies don’t actively track the results of their marketing campaigns actively enough.

    By improving your marketing attribution, you can determine which channels, ads, and campaigns work and which don’t. Then, you can move the budget from ineffective channels to effective ones.

    Even if you can only identify half of your wastage, this could be 20% or more of your total spend. Just imagine what your bottom line would look like if your marketing budget were 20% more effective.

    That’s the power that marketing attribution, when done right, brings to the table. It’s the road to a higher marketing ROI.

    Common marketing attribution models and how they’re different 

    The default model for attributing completed goals in most analytics tools is either the last interaction or the last non-direct interaction.

    However, some multi-touch models can help you get a more holistic view of the impact of your marketing efforts.

    Pros and cons of different marketing attribution models.
    • Last interaction model : attributes the conversion to the final interaction or referring source (campaign or ad).
    • Last non-direct interaction model : attributes the conversion to the final touchpoint that was not a direct visit to your website. (For example, if a search ad took them to a product page, the user bookmarked it and returned directly the next day to finish the purchase. The credit would go to the search ad as it’s the last non-direct touchpoint.)
    • First interaction model : attributes the conversion to the first referring event alone.
    • Linear model : gives equal value to every touchpoint throughout the customer journey. 
    • Time decay model : gives more value to touchpoints the closer they were to the actual sale.
    • Position-based model : gives more value to the first and last touchpoints — often 40% each, while splitting 20% among the rest.

    You can read our guide dedicated to marketing attribution models for more details on these models.

    Types of marketing attribution software and the impact of privacy regulations

    Until recently, digital advertising was the “scientific” advertisers’ utopia. Everything could be measured, with cookies from giants like Google and Facebook stalking every user across the web.

    But with the advent of regulations like GDPR and the CCPA, you can no longer blindly trust Google Analytics or the Meta Pixel without consequences.

    Multi-channel attribution tools with third-party cookies and GDPR

    Google, Meta, and other companies used to track and combine user data from their own platforms and websites across the web that installed their tags. These third-party cookies have long been under fire and have caused several GDPR fines.

    Illustration of the privacy issues with some multi-channel attribution tools

    The alternative : analytics platforms with first-party cookies

    In a post-GDPR digital marketing landscape, a compliant-by-default web analytics platform like Matomo is a more reliable and accurate alternative.

    Plus, with a platform like Matomo, you don’t need to rely on data from digital advertising platforms like Facebook Ads and Google Ads. You can accurately track referral sources using our campaign tracking parameters.

    7 best marketing attribution software in 2024

    Below is the list of our favourite marketing attribution tools in 2024. If you find and use one that suits your needs correctly, you can quickly boost your marketing performance.

    1. Matomo — Accurate and easiest to set up for marketing attribution

    Matomo is a privacy-friendly web analytics suite that empowers you to accurately attribute marketing efforts and gain valuable insights while prioritising user privacy and compliance.

    Matomo integrates with e-commerce platforms like WooCommerce and Magenta. That makes it easy for B2C marketing teams to track the revenue impact of their campaigns.

    Multi-channel conversion attribution report in Matomo analytics

    You can also compare a variety of attribution models against each other. B2B teams can use our API to integrate Matomo with their CRM.

    Pros :

    • Relies on first-party cookies for tracking, ensuring accurate data collection and attribution of user actions
    • Includes additional features like Heatmaps, Session Recordings, Form Analytics, A/B Testing, and more
    • Easy to set up and use
    • Features most common multi-touch attribution models

    Cons :

    • Limited to owned channels (website and e-commerce store) due to first-party cookies and data (but you can integrate other data sources through a CRM)

    Pricing

    The self-hosted version is free. The cloud hosted version starts at $19 per month and includes a 21-day free trial. No credit card requierd. 

    Try Matomo for Free

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

    No credit card required

    2. WhatConverts — Great option for leads-based businesses with high ad spend

    WhatConverts is a marketing attribution tool with a focus on lead tracking. With most web analytics setups, it adds call and text tracking to the typical form-only tracking.

    Screenshot of the WhatConverts homepage

    Pros :

    • Reliable call and text tracking
    • Revenue attribution to specific leads (and, by extension, campaigns and ads)

    Cons :

    • Focused exclusively on leads — little utility for e-commerce companies 

    Pricing

    The cheapest plan starts at $30/month but does not include analytics integrations or form tracking. To access this and advanced flow tracking and attribution features, you need the Elite plan, which starts at $160/month.

    3. HubSpot Marketing Hub — Ideal CRM for larger B2B companies

    HubSpot is a marketing CRM with attribution features for tracking and analysis.

    Screenshot of the HubSpot homepage

    The platform is very broad — encompassing CRM, email automation and other tools — which makes it challenging to use effectively. The price tag is also quite steep for smaller companies and marketing teams.

    Pros :

    • Concretely tracks revenue to multiple different touchpoints and marketing channels
    • Includes several different multi-touch attribution models
    • Allows offline conversion tracking

    Cons :

    • The price point is too high for smaller teams
    • Cam be difficult to set up effectively

    Pricing

    Since marketing attribution is only included in HubSpot Marketing Hub’s Professional and Enterprise plans, pricing starts at $800/month (paid annually). If you commit for a year but pay monthly, the price is $890/month for the professional plan. This goes up with additional add-ons and as your contacts increase as well. 

    4. ActiveCampaign — Good CRM option for small B2B companies

    ActiveCampaign is a CRM and marketing automation platform that can help you trace leads and revenue back to their source.

    Screenshot of the ActiveCampaign homepage

    Although it has a similar scope of features to HubSpot, it is more affordable and slightly easier to use for beginners.

    Pros :

    • Tracks sales revenue back to specific marketing touchpoints
    • Powerful marketing automation features

    Cons :

    • B2B companies may need to purchase two plans, one ActiveCampaign marketing and one CRM.

    Pricing

    Unlike HubSpot, ActiveCampaign offers a much more affordable plan, starting at $29/month billed annually (for up to 1,000 contacts). The marketing and sales CRM bundle starts at $93/month with up to five users.

    5. Salesforce Data Cloud for Marketing — Ideal CRM for enterprises

    Salesforce is a robust and feature-rich CRM that many enterprises rely on for their sales teams.

    Screenshot of the Salesforce homepage

    That makes Salesforce’s marketing attribution platform a logical choice for existing Salesforce users.

    Pros :

    • Uses prospect and sales data from CRM to attribute revenue
    • Revenue prediction analytics
    • Lead scoring to help your sales team focus on high-value leads

    Cons :

    • Difficult to set up and use
    • Clunky and aged user interface
    • Relatively high price point

    Pricing

    The limited Marketing Cloud Account Engagement Growth plan starts at $1,250/month, billed annually. To access advanced cross-channel journeys, you need the Pro plan, which starts at $2,750 monthly.

    6. Terminus — Great for account-based marketing

    If your marketing team uses an account-based marketing (ABM) approach, Terminus might be the right option for you.

    Screenshot of the Terminus homepage

    It offers ABM tools like target account event tracking and revenue attribution tools for your marketing campaigns.

    Pros :

    • Advanced multi-channel revenue attribution tools with a wide range of reports
    • Track intent touchpoints back to target accounts
    • Reliable revenue predictions help you focus your marketing activities

    Cons :

    • Complex and difficult to set up, understand and use effectively
    • Lacks native integrations with many common advertising platforms and analytics tools

    Pricing

    Terminus offers no standard pricing plans. You must contact their sales team for a custom quote based on your needs.

    7. Adobe Analytics — An analytics for enterprises

    Adobe Analytics is part of the Adobe Experience Cloud, with plenty of big data analysis tools for enterprises. Although the platform is quite powerful, it is equally complex and difficult to use. The price point is also prohibitive for many smaller companies.

    Screenshot of the Adobe Analytics homepage

    Pros :

    • Very extensive reporting tools
    • Predictive analytics give you solid leading indicator for future campaign performance
    • Track multiple digital touchpoints across the entire customer journey

    Cons :

    • Like Google Analytics, Adobe Analytics aggregates your visitor data by default, making compliant “consent-free tracking” — tracking user actions without asking for consent — impossible according to GDPR. (See more differences in Matomo’s comparison against Adobe Analytics and Google Analytics.)
    • Prohibitively expensive for most smaller companies
    • Very steep learning curve for setting up and using it correctly

    Pricing

    Adobe Analytics uses usage-based pricing — which means they adjust the pricing based on the traffic volume to your website. Still, their lower price points aren’t exactly SMB-friendly — multiple sources put Adobe’s lowest starting price point at $2,000–2,500 per month.

    Get accurate marketing attribution with Matomo (without privacy concerns)

    Matomo allows you to do marketing attribution effectively and accurately without compromising your users’ privacy. By default, we only use first-party cookies and offer consent-free tracking – meaning no more annoying cookie consent banners (excluding in Germany and the UK).

    If you want to boost your marketing performance without disregarding your users’ privacy, get started with our 21-day free trial. No credit card required. It’s time to make more informed decisions about your marketing campaigns.

  • Unveiling GA4 Issues : 8 Questions from a Marketer That GA4 Can’t Answer

    8 janvier 2024, par Alex

    It’s hard to believe, but Universal Analytics had a lifespan of 11 years, from its announcement in March 2012. Despite occasional criticism, this service established standards for the entire web analytics industry. Many metrics and reports became benchmarks for a whole generation of marketers. It truly was an era.

    For instance, a lot of marketers got used to starting each workday by inspecting dashboards and standard traffic reports in the Universal Analytics web interface. There were so, so many of those days. They became so accustomed to Universal Analytics that they would enter reports, manipulate numbers, and play with metrics almost on autopilot, without much thought.

    However, six months have passed since the sunset of Universal Analytics – precisely on July 1, 2023, when Google stopped processing requests for resources using the previous version of Google Analytics. The time when data about visitors and their interactions with the website were more clearly structured within the UA paradigm is now in the past. GA4 has brought a plethora of opportunities to marketers, but along with those opportunities came a series of complexities.

    GA4 issues

    Since its initial announcement in 2020, GA4 has been plagued with errors and inconsistencies. It still has poor and sometimes illogical documentation, numerous restrictions, and peculiar interface solutions. But more importantly, the barrier to entry into web analytics has significantly increased.

    If you diligently follow GA4 updates, read the documentation, and possess skills in working with data (SQL and basic statistics), you probably won’t feel any problems – you know how to set up a convenient and efficient environment for your product and marketing data. But what if you’re not that proficient ? That’s when issues arise.

    In this article, we try to address a series of straightforward questions that less experienced users – marketers, project managers, SEO specialists, and others – want answers to. They have no time to delve into the intricacies of GA4 but seek access to the fundamentals crucial for their functionality.

    Previously, in Universal Analytics, they could quickly and conveniently address their issues. Now, the situation has become, to put it mildly, more complex. We’ve identified 8 such questions for which the current version of GA4 either fails to provide answers or implies that answers would require significant enhancements. So, let’s dive into them one by one.

    Question 1 : What are the most popular traffic sources on my website ?

    Seemingly a straightforward question. What does GA4 tell us ? It responds with a question : “Which traffic source parameter are you interested in ?”

    GA4 traffic source

    Wait, what ?

    People just want to know which resources bring them the most traffic. Is that really an issue ?

    Unfortunately, yes. In GA4, there are not one, not two, but three traffic source parameters :

    1. Session source.
    2. First User Source – the source of the first session for each user.
    3. Just the source – determined at the event or conversion level.

    If you wanted to open a report and draw conclusions quickly, we have bad news for you. Before you start ranking your traffic sources by popularity, you need to do some mental work on which parameter and in what context you will look. And even when you decide, you’ll need to make a choice in the selection of standard reports : work with the User Acquisition Report or Traffic Acquisition.

    Yes, there is a difference between them : the first uses the First User Source parameter, and the second uses the session source. And you need to figure that out too.

    Question 2 : What is my conversion rate ?

    This question concerns everyone, and it should be simple, implying a straightforward answer. But no.

    GA4 conversion rate

    In GA4, there are three conversion metrics (yes, three) :

    1. Session conversion – the percentage of sessions with a conversion.
    2. User conversion – the percentage of users who completed a conversion.
    3. First-time Purchaser Conversion – the share of active users who made their first purchase.

    If the last metric doesn’t interest us much, GA4 users can still choose something from the remaining two. But what’s next ? Which parameters to use for comparison ? Session source or user source ? What if you want to see the conversion rate for a specific event ? And how do you do this in analyses rather than in standard reports ?

    In the end, instead of an answer to a simple question, marketers get a bunch of new questions.

    Question 3. Can I trust user and session metrics ?

    Unfortunately, no. This may boggle the mind of those not well-versed in the mechanics of calculating user and session metrics, but it’s the plain truth : the numbers in GA4 and those in reality may and will differ.

    GA4 confidence levels

    The reason is that GA4 uses the HyperLogLog++ statistical algorithm to count unique values. Without delving into details, it’s a mechanism for approximate estimation of a metric with a certain level of error.

    This error level is quite well-documented. For instance, for the Total Users metric, the error level is 1.63% (for a 95% confidence interval). In simple terms, this means that 100,000 users in the GA4 interface equate to 100,000 1.63% in reality.

    Furthermore – but this is no surprise to anyone – GA4 samples data. This means that with too large a sample size or when using a large number of parameters, the application will assess your metrics based on a partial sample – let’s say 5, 10, or 30% of the entire population.

    It’s a reasonable assumption, but it can (and probably will) surprise marketers – the metrics will deviate from reality. All end-users can do (excluding delving into raw data methodologies) is to take this error level into account in their conclusions.

    Question 4. How do I calculate First Click attribution ?

    You can’t. Unfortunately, as of late, GA4 offers only three attribution models available in the Attribution tab : Last Click, Last Click For Google Ads, and Data Driven. First Click attribution is essential for understanding where and when demand is generated. In the previous version of Google Analytics (and until recently, in the current one), users could quickly apply First Click and other attribution models, compare them, and gain insights. Now, this capability is gone.

    GA4 attribution model

    Certainly, you can look at the conversion distribution considering the First User Source parameter – this will be some proxy for First Click attribution. However, comparing it with others in the Model Comparison tab won’t be possible. In the context of the GA4 interface, it makes sense to forget about non-standard attribution models.

    Question 5. How do I account for intra-session traffic ?

    Intra-session traffic essentially refers to a change in traffic sources within a session. Imagine a scenario where a user comes to your site organically from Google and, within a minute, comes from an email campaign. In the previous version of Google Analytics, a new session with the traffic source “e-mail” would be created in such a case. But now, the situation has changed.

    A session now only ends in the case of a timeout – say, 30 minutes without interaction. This means a session will always have a source from which it started. If a user changes the source within a session (clicks on an ad, from email campaigns, and so on), you won’t know anything about it until they convert. This is a significant blow to intra-session traffic since their contribution to traffic remains virtually unnoticed. 

    Question 6. How can I account for users who have not consented to the use of third-party cookies ?

    You can’t. Google Consent Mode settings imply several options when a user rejects the use of 3rd party cookies. In GA4 and BigQuery, depersonalized cookieless pings will be sent. These pings do not contain specific client_id, session_id, or other custom dimensions. As a result, you won’t be able to consider them as users or link the actions of such users together.

    Question 7. How can I compare data in explorations with the previous year ?

    The maximum data retention period for a free GA4 account is 14 months. This means that if the date range is wider, you can only use standard reports. You won’t be able to compare or view cohorts or funnels for periods more than 14 months ago. This makes the product functionality less rich because various report formats in explorations are very convenient for comparing specific metrics in easily digestible reports.

    GA4 data retention

    Of course, you always have the option to connect BigQuery and store raw data without limitations, but this process usually requires the involvement of an advanced analyst. And precisely this option is unavailable to most marketers in small teams.

    Question 8. Is the data for yesterday accurate ?

    Unknown. Google declares that data processing in GA4 takes up to 48 hours. And although this process is faster, most users still have room for frustration. And they can be understood.

    Data processing time in GA4

    What does “data processing takes 24-48 hours” mean ? When will the data in reports be complete ? For yesterday ? Or the day before yesterday ? Or for all days that were more than two days ago ? Unclear. What should marketers tell their managers when they were asked if all the data is in this report ? Well, probably all of it… or maybe not… Let’s wait for 48 hours…

    Undoubtedly, computational resources and time are needed for data preprocessing and aggregation. It’s okay that data for today will not be up-to-date. And probably not for yesterday either. But people just want to know when they can trust their data. Are they asking for too much : just a note that this report contains all the data sent and processed by Google Analytics ?

    What should you do ?

    Credit should be given to the Google team – they have done a lot to enable users to answer these questions in one form or another. For example, you can use data streaming in BigQuery and work with raw data. The entry threshold for this functionality has been significantly lowered. In fact, if you are dissatisfied with the GA4 interface, you can organize your export to BigQuery and create your own reports without (almost) any restrictions.

    Another strong option is the widespread launch of GTM Server Side. This allows you to quite freely modify the event model and essentially enrich each hit with various parameters, doing this in a first-party context. This, of course, reduces the harmful impact of most of the limitations described in this text.

    But this is not a solution.

    The users in question – marketers, managers, developers – they do not want or do not have the time for a deep dive into the issue. And they want simple answers to simple (it seemed) questions. And for now, unfortunately, GA4 is more of a professional tool for analysts than a convenient instrument for generating insights for not very advanced users.

    Why is this such a serious issue ?

    The thing is – and this is crucial – over the past 10 years, Google has managed to create a sort of GA-bubble for marketers. Many of them have become so accustomed to Google Analytics that when faced with another issue, they don’t venture to explore alternative solutions but attempt to solve it on their own. And almost always, this turns out to be expensive and inconvenient.

    However, with the latest updates to GA4, it is becoming increasingly evident that this application is struggling to address even the most basic questions from users. And these questions are not fantastically complex. Much of what was described in this article is not an unsolvable mystery and is successfully addressed by other analytics services.

    Let’s try to answer some of the questions described from the perspective of Matomo.

    Question 1 : What are the most popular traffic sources ? [Solved]

    In the Acquisition panel, you will find at least three easily identifiable reports – for traffic channels (All Channels), sources (Websites), and campaigns (Campaigns). 

    Channel Type Table

    With these, you can quickly and easily answer the question about the most popular traffic sources, and if needed, delve into more detailed information, such as landing pages.

    Question 2 : What is my conversion rate ? [Solved]

    Under Goals in Matomo, you’ll easily find the overall conversion rate for your site. Below that you’ll have access to the conversion rate of each goal you’ve set in your Matomo instance.

    Question 3 : Can I trust user and session metrics ? [Solved]

    Yes. With Matomo, you’re guaranteed 100% accurate data. Matomo does not apply sampling, does not employ specific statistical algorithms, or any analogs of threshold values. Yes, it is possible, and it’s perfectly normal. If you see a metric in the visits or users field, it accurately represents reality by 100%.

    Try Matomo for Free

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

    No credit card required

    Question 4 : How do I calculate First Click attribution ? [Solved]

    You can do this in the same section where the other 5 attribution models, available in Matomo, are calculated – in the Multi Attribution section.

    Multi Attribution feature

    You can choose a specific conversion and, in a few clicks, calculate and compare up to 3 marketing attribution models. This means you don’t have to spend several days digging through documentation trying to understand how a particular model is calculated. Have a question – get an answer.

    Question 5 : How do I account for intra-session traffic ? [Solved]

    Matomo creates a new visit when a user changes a campaign. This means that you will accurately capture all relevant traffic if it is adequately tagged. No campaigns will be lost within a visit, as they will have a new utm_campaign parameter.

    This is a crucial point because when the Referrer changes, a new visit is not created, but the key lies in something else – accounting for all available traffic becomes your responsibility and depends on how you tag it.

    Try Matomo for Free

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

    No credit card required

    Question 6 : How can I account for users who have not consented to the use of third-party cookies ? [Solved]

    Google Analytics requires users to accept a cookie consent banner with “analytics_storage=granted” to track them. If users reject cookie consent banners, however, then Google Analytics can’t track these visitors at all. They simply won’t show up in your traffic reports. 

    Matomo doesn’t require cookie consent banners (apart from in the United Kingdom and Germany) and can therefore continue to track visitors even after they have rejected a cookie consent screen. This is achieved through a config_id variable (the user identifier equivalent which is updating once a day). 

    Matomo doesn't need cookie consent, so you see a complete view of your traffic

    This means that virtually all of your website traffic will be tracked regardless of whether users accept a cookie consent banner or not.

    Question 7 : How can I compare data in explorations with the previous year ? [Solved]

    There is no limitation on data retention for your aggregated reports in Matomo. The essence of Matomo experience lies in the reporting data, and consequently, retaining reports indefinitely is a viable option. So you can compare data for any timeframe. 7

    Date Comparison Selector