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  • CRO Program : Best Practices and KPIs to Track [2024]

    8 mai 2024, par Erin

    Driving traffic to your website is only one part of the equation ; the second part is getting those visitors to convert by completing a desired action — creating an account, signing up for a newsletter or completing a purchase. 

    But if you fail to optimise your website for conversions, you’ll have a hard time guiding visitors further down the funnel and turning them into customers.

    That’s where a CRO program (or conversion rate optimisation) can help. 

    This article will cover conversion rate optimisation best practices and outline key metrics and KPIs to start tracking to see an improvement in your conversion rates.

    What is a CRO program ? 

    In the simplest terms, a CRO program — also called a CRO plan — is a digital marketing strategy. It focuses on implementing different tactics that can lead to an increase in conversion rate and maximising revenue. 

    CRO concept with marketing icons

    One thing to remember is that the definition of “conversion” varies from business to business. The most obvious type of conversion would be a financial transaction or a completed form — but it comes down to what you consider a valuable action. 

    Many different actions can count as conversions, depending on your marketing goals. 

    Besides making a purchase, other common examples of key conversion moments include creating a new account, signing up for a free trial, booking a demo and subscribing to an email newsletter. 

    Another thing worth noting is that while the average conversion rate on e-commerce websites is 3.76%, it might fluctuate across different industries and device types. Case in point — desktop devices have higher conversion rates than mobile devices, clocking in at 4.79% and 3.32%, respectively. 

    So, in addition to defining your key conversion moments, you should also go over conversion insights relevant to your specific industry. 

    The importance of conversion rate optimisation 

    You’d be right to assume that the ultimate goal of a conversion rate optimisation process is to drive revenue through higher conversion rates — but don’t focus solely on the numbers. The core principle of a CRO program is improving the customer experience. Once you’ve achieved that, the increase in conversion rate will follow. 

    Illustration of conversion funnel optimisation

    According to a recent report, global conversion rate optimisation (CRO) software sales are expected to reach $3.7 billion by 2032 — up from $1.1 billion in 2021. 

    This growth indicates the increasing interest in strategies and tools that can help optimise the conversion funnel. Businesses are looking for ways to keep potential customers engaged and improve the average conversion rate — without necessarily increasing their spending. 

    Here are a few reasons why a CRO program deserves a spot in your broader digital marketing strategies : 

    • It can lower your cost per acquisition (CPA) : A CRO program is about optimising your conversion funnel by leveraging existing assets and website traffic rather than increasing your spending — which lowers the costs of acquiring new customers and, in turn, drives ROI. 
    • It can maximise customer lifetime value (CLV) : If you can turn one-time buyers into repeat customers, you’ll be one step closer to building a loyal user base and increasing your CLV. 
    • It can lead to increased sales and boost your revenue : Higher conversion rates typically mean higher revenue ; that’s arguably the most obvious benefit of implementing a CRO program
    • It improves the overall user experience : The goal is to make your site more accessible, easier to navigate and more engaging. Delivering the experience people want — and expect — when navigating your website is one of the core principles of a CRO program.
    • It helps you to get to know your customers better : You can’t meet your customers’ needs without taking the time to know them, create user personas and understand their preferences, pain points and conversion barriers they may be facing. 

    Conversion optimisation gives you a competitive edge in revenue and brand reputation. 

    5 CRO best practices 

    Illustration of different CRO elements

    Here are five conversion rate optimisation strategies and best practices that can make a real difference in the customer experience — and drive potential conversions. 

    Create a CRO roadmap in advance 

    First and foremost, you’ll need a well-defined “game plan” that aligns with and reflects your conversion goals. 

    A CRO roadmap is a detailed manual that outlines how to implement different elements of your CRO-related efforts. Marketing teams can refer to this step-by-step framework for test planning, prioritisation and resource allocation while optimising their marketing strategy. 

    While conversion rate optimisation can be a complex process — especially when you don’t know what to tackle first — we’ve found that there are three things you need to consider when setting the foundations of a successful CRO program : 

    • The “why” behind your website traffic : You’re likely using different online marketing strategies — from SEO to pay-per-click (PPC). So, it’s best to start by gathering channel-specific conversion insights through marketing attribution. Then identify which of these efforts have the biggest impact on your target audience. 
    • The so-called “conversion blockers” that tell you where and why visitors tend to leave without completing a desired action : Funnel analysis might reveal problematic pages — drop-off points where you tend to lose most of your visitors. 
    • Your “hooks” : User feedback can be of great help here ; you can learn a lot by simply asking your customers to fill out a quick online survey and tell you what motivated them to take action.

    Before working on that “game plan,” perform a pre-test analysis. 

    Matomo combines web analytics and user behaviour analytics with features like Heatmaps, Session Recordings, Form Analytics, Funnel Analytics, A/B Testing and User Flow. It can give you those initial benchmarks for measuring progress and a potential increase in conversion rate. 

    Validate your ideas with A/B and multivariate testing 

    Conversion rate optimisation is an iterative process. So, it shouldn’t come as a surprise that A/B testing variants of page layouts, CTAs, headlines, copy and other elements is a big part of it.

    Multivariate and A/B testing allows you to test a wide range of elements across your site and identify what works — and, more importantly, what doesn’t — in terms of driving conversions.

    On that note, Matomo’s A/B Testing feature can support your conversion rate optimisation process by identifying variants that perform better based on statistical significance. 

    Try Matomo for Free

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

    No credit card required

    Get to know your website visitors 

    Driving conversions comes down to understanding potential customer’s pain points and needs — and delivering an experience that positions you as the solution and gets them to take action. 

    Here are a few things that can help you understand your website visitors better : 

    • Collecting customer feedback through surveys and using it to identify main areas for improvement 
    • Creating detailed customer personas and optimising your website design and messaging based on your target audience’s pain points, needs and wants 
    • Using heatmaps — colour-coded data visualisation tools that illustrate user interactions — and scroll maps to get a comprehensive overview of online sessions and identify the most engaging elements and those that stand out as potential conversion barriers 

    Matomo’s Heatmaps can help you identify the most-clicked elements on the page and show how far users scroll — providing powerful user insights you can use to optimise these pages.

    Try Matomo for Free

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

    No credit card required

    Remove friction points 

    As we previously discussed, identifying friction points and barriers to conversion — issues that prevent visitors from converting — is one of the crucial aspects of developing a CRO plan. 

    Many different “conversion blockers” are worth looking into, including : 

    • Lengthy or otherwise complex checkout processes 
    • No guest checkout feature 
    • Device type, browser and OS compatibility issues 
    • Slow site speed and other technical issues
    • Lack of free shipping and limited payment methods 
    • Absence of social proof (customer reviews and testimonials) and trust badges

    Once you’ve identified what’s slowing down or completely discouraging users from reaching key conversion moments, take the time to address it. 

    Switch to text-based CTAs 

    Calls-to-action (CTAs) play a crucial role in guiding customers from interest to action. However, sometimes they fail to do their job — encouraging website visitors to proceed to the next step — effectively. 

    The most obvious reason is that your CTAs aren’t visually engaging or clear enough. In that case, you can try using action-oriented language and stronger visual elements and aligning the CTA copy with the context of the page. 

    But more often than not, the issue comes down to a phenomenon called “banner blindness” — the tendency of website visitors to ignore (either intentionally or unintentionally) elements on a page that resemble banner ads. 

    And if that’s what’s preventing visitors from converting, consider switching to text-based CTAs. 

    Conversion rate optimisation metrics and KPIs 

    At this point, you should know the outcomes you hope to achieve. Your next step should be to figure out how you’re going to measure and analyse results — and identify the changes that made the most impact on your conversion funnel. 

    After all, your CRO action plan should be based on data — assumptions and “gut feelings” will rarely lead to a notable increase in conversion rates

    Illustration of the conversion funnel

    That brings us to key performance indicators (KPIs) : 

    Tracking CRO metrics and website KPIs can help you understand the customer’s journey and path to purchase, identify opportunities for improving the user experience (UX) and determine how to optimise conversions.

    That said, you shouldn’t try to track every metric in the book ; think about your ultimate goal and identify the metrics and KPIs most relevant to your business. 

    We’ll assume that you’re already tracking macro- and micro-conversions. However, we’ve outlined a few additional key conversion rate optimisation metrics you should keep an eye on to make sure that your CRO program is performing as intended : 

    • Cost-per-conversion : By measuring how much you spend on each successful conversion — again, completed forms, sign-ups and sales all count as key conversion moments — you’ll be in a better position to assess the cost-effectiveness of your online marketing strategies.
    • Starter rate : This metric tells you the number of people who start filling out the form, after seeing it. This metric is particularly important for companies that rely on getting leads from forms. 
    • Average order value (AOV) : This metric is important for e-commerce sites to understand the value of their transactions. AOV calculates the average monetary value of each order.

    That’s not all ; you can also use a web analytics tool like Matomo to gain granular insights into visitors : 

    • Unique, new and returning visitors : Tracking the number of new and returning visitors your website gets within a given timeframe will help you understand your user base and determine if your content resonates with them. While you want a constant stream of new traffic, don’t overlook the importance of returning visitors ; they’re the foundation of a loyal customer base.
    • User flows : By analysing the user flows, you’ll have a visual representation of how visitors use your website, which will help you understand their journey and the specific path they take. 
    • Bounce rate : This metric tells you how many users viewed a single page on your site and ended up leaving before they took any kind of action. As such, it’s a clear indicator of how good your content, CTAs and website layout are at keeping users engaged.
    • Exit rate : Another key metric to track is the exit rate — the percentage of users who drop off at a specific page. High-exit pages usually lack important information and CTAs, cause frustration or otherwise fail to meet users’ expectations. Keep in mind that there’s a difference between bounce rate and exit rate — the latter involves users who viewed at least one other page. 

    There are many other user engagement metrics you should keep an eye on in addition to the ones mentioned above — including time on-page, actions per visit, scroll depth and traffic source. You’ll find all this information — and more — in Matomo’s Page Analytics Report

    Conclusion 

    Implementing a CRO program can be a time-consuming and iterative process. However, it’s vital for guiding your marketing efforts and making data-driven decisions that’ll ultimately help you drive growth and reach your business goals. 

    It’s best to start by identifying where your website visitors come from and what contributes to — or prevents them from — taking further action. But that’s easier said than done. You’ll need to leverage web analytics tools like Matomo to gather powerful user insights and monitor your website’s performance. 

    As an all-in-one, privacy-friendly web analytics solution, Matomo combines traditional web analytics and advanced behavioural analytics — delivering a consistent experience based on 100% accurate, unsampled data.

    Join the 1 million websites that have chosen Matomo as their web analytics platform. Start your 21-day free trial today — and see how Matomo can help you improve your website’s conversion rates. No credit card required.

  • 10 Key Google Analytics Limitations You Should Be Aware Of

    9 mai 2022, par Erin

    Google Analytics (GA) is the biggest player in the web analytics space. But is it as “universal” as its brand name suggests ?

    Over the years users have pointed out a number of major Google Analytics limitations. Many of these are even more visible in Google Analytics 4. 

    Introduced in 2020, Google Analytics 4 (GA4) has been sceptically received. As the sunset date of 1st, July 2023 for the current version, Google Universal Analytics (UA), approaches, the dismay grows stronger.

    To the point where people are pleading with others to intervene : 

    GA4 Elon Musk Tweet
    Source : Chris Tweten via Twitter

    Main limitations of Google Analytics

    Google Analytics 4 is advertised as a more privacy-centred, comprehensive and “intelligent” web analytics platform. 

    According to Google, the newest version touts : 

    • Machine learning at its core provides better segmentation and fast-track access to granular insights 
    • Privacy-by-design controls, addressing restrictions on cookies and new regulatory demands 
    • More complete understanding of customer journeys across channels and devices 

    Some of these claims hold true. Others crumble upon a deeper investigation. Newly advertised Google Analytics capabilities such as ‘custom events’, ‘predictive insights’ and ‘privacy consent mode’ only have marginal improvements. 

    Complex setup, poor UI and lack of support with migration also leave many other users frustrated with GA4. 

    Let’s unpack all the current (and legacy) limitations of Google Analytics you should account for. 

    1. No Historical Data Imports 

    Google rushed users to migrate from Universal Analytics to Google Analytics 4. But they overlooked one important precondition — backwards compatibility. 

    You have no way to import data from Google Universal Analytics to Google Analytics 4. 

    Historical records are essential for analysing growth trends and creating benchmarks for new marketing campaigns. Effectively, you are cut short from past insights — and forced to start strategising from scratch. 

    At present, Google offers two feeble solutions : 

    • Run data collection in parallel and have separate reporting for GA4 and UA until the latter is shut down. Then your UA records are gone. 
    • For Ecommerce data, manually duplicate events from UA at a new GA4 property while trying to figure out the new event names and parameters. 

    Google’s new data collection model is the reason for migration difficulties. 

    In Google Analytics 4, all analytics hits types — page hits, social hits, app/screen view, etc. — are recorded as events. Respectively, the “‘event’ parameter in GA4 is different from one in Google Universal Analytics as the company explains : 

    GA4 vs Universal Analytics event parameters
    Source : Google

    This change makes migration tedious — and Google offers little assistance with proper events and custom dimensions set up. 

    2. Data Collection Limits 

    If you’ve wrapped your head around new GA4 events, congrats ! You did a great job, but the hassle isn’t over. 

    You still need to pay attention to new Google Analytics limits on data collection for event parameters and user properties. 

    GA4 Event limits
    Source : Google

    These apply to :

    • Automatically collected events
    • Enhanced measurement events
    • Recommended events 
    • Custom events 

    When it comes to custom events, GA4 also has a limit of 25 custom parameters per event. Even though it seems a lot, it may not be enough for bigger websites. 

    You can get higher limits by upgrading to Google Analytics 360, but the costs are steep. 

    3. Limited GDPR Compliance 

    Google Analytics has a complex history with European GDPR compliance

    A 2020 ruling by the Court of Justice of the European Union (CJEU) invalidated the Privacy Shield framework Google leaned upon. This framework allowed the company to regulate EU-US data transfers of sensitive user data. 

    But after this loophole was closed, Google faced a heavy series of privacy-related fines :

    • French data protection authority, CNIL, ruled that  “the transfers to the US of personal data collected through Google Analytics are illegal” — and proceeded to fine Google for a record-setting €150 million at the beginning of 2022. 
    • Austrian regulators also deemed Google in breach of GDPR requirements and also branded the analytics as illegal. 

    Other EU-member states might soon proceed with similar rulings. These, in turn, can directly affect Google Analytics users, whose businesses could face brand damage and regulatory fines for non-compliance. In fact, companies cannot select where the collected analytics data will be stored — on European servers or abroad — nor can they obtain this information from Google.

    Getting a web analytics platform that allows you to keep data on your own servers or select specific Cloud locations is a great alternative. 

    Google also has been lax with its cookie consent policy and doesn’t properly inform consumers about data collection, storage or subsequent usage. Google Analytics 4 addresses this issue to an extent. 

    By default, GA4 relies on first-party cookies, instead of third-party ones — which is a step forward. But the user privacy controls are hard to configure without losing most of the GA4 functionality. Implementing user consent mode to different types of data collection also requires a heavy setup. 

    4. Strong Reliance on Sampled Data 

    To compensate for ditching third-party cookies, GA4 more heavily leans on sampled data and machine learning to fill the gaps in reporting. 

    In GA4 sampling automatically applies when you :

    • Perform advanced analysis such as cohort analysis, exploration, segment overlap or funnel analysis with not enough data 
    • Have over 10,000,000 data rows and generate any type of non-default report 

    Google also notes that data sampling can occur at lower thresholds when you are trying to get granular insights. If there’s not enough data or because Google thinks it’s too complex to retrieve. 

    In their words :

    Source : Google

    Data sampling adds “guesswork” to your reports, meaning you can’t be 100% sure of data accuracy. The divergence from actual data depends on the size and quality of sampled data. Again, this isn’t something you can control. 

    Unlike Google Analytics 4, Matomo applies no data sampling. Your reports are always accurate and fully representative of actual user behaviours. 

    5. No Proper Data Anonymization 

    Data anonymization allows you to collect basic analytics about users — visits, clicks, page views — but without personally identifiable information (or PII) such as geo-location, assigns tracking ID or other cookie-based data. 

    This reduced your ability to :

    • Remarket 
    • Identify repeating visitors
    • Do advanced conversion attribution 

    But you still get basic data from users who ignored or declined consent to data collection. 

    By default, Google Analytics 4 anonymizes all user IP addresses — an upgrade from UA. However, it still assigned a unique user ID to each user. These count as personal data under GDPR. 

    For comparison, Matomo provides more advanced privacy controls. You can anonymize :

    • Previously tracked raw data 
    • Visitor IP addresses
    • Geo-location information
    • User IDs 

    This can ensure compliance, especially if you operate in a sensitive industry — and delight privacy-mindful users ! 

    6. No Roll-Up Reporting

    Getting a bird’s-eye view of all your data is helpful when you need hotkey access to main sites — global traffic volume, user count or percentage of returning visitors.

    With Roll-Up Reporting, you can see global-performance metrics for multiple localised properties (.co.nz, .co.uk, .com, etc,) in one screen. Then zoom in on specific localised sites when you need to. 

    7. Report Processing Latency 

    The average data processing latency is 24-48 hours with Google Analytics. 

    Accounts with over 200,000 daily sessions get data refreshes only once a day. So you won’t be seeing the latest data on core metrics. This can be a bummer during one-day promo events like Black Friday or Cyber Monday when real-time information can prove to be game-changing ! 

    Matomo processes data with lower latency even for high-traffic websites. Currently, we have 6-24 hour latency for cloud deployments. On-premises web analytics can be refreshed even faster — within an hour or instantly, depending on the traffic volumes. 

    8. No Native Conversion Optimisation Features

    Google Analytics users have to use third-party tools to get deeper insights like how people are interacting with your webpage or call-to-action.

    You can use the free Google Optimize tool, but it comes with limits : 

    • No segmentation is available 
    • Only 10 simultaneous running experiments allowed 

    There isn’t a native integration between Google Optimize and Google Analytics 4. Instead, you have to manually link an Optimize Container to an analytics account. Also, you can’t select experiment dimensions in Google Analytics reports.

    What’s more, Google Optimize is a basic CRO tool, best suited for split testing (A/B testing) of copy, visuals, URLs and page layouts. If you want to get more advanced data, you need to pay for extra tools. 

    Matomo comes with a native set of built-in conversion optimization features : 

    • Heatmaps 
    • User session recording 
    • Sales funnel analysis 
    • A/B testing 
    • Form submission analytics 
    A/B test hypothesis testing on Matomo
    A/B test hypothesis testing on Matomo

    9. Deprecated Annotations

    Annotations come in handy when you need to provide extra context to other team members. For example, point out unusual traffic spikes or highlight a leak in the sales funnel. 

    This feature was available in Universal Analytics but is now gone in Google Analytics 4. But you can still quickly capture, comment and share knowledge with your team in Matomo. 

    You can add annotations to any graph that shows statistics over time including visitor reports, funnel analysis charts or running A/B tests. 

    10. No White Label Option 

    This might be a minor limitation of Google Analytics, but a tangible one for agency owners. 

    Offering an on-brand, embedded web analytics platform can elevate your customer experience. But white label analytics were never a thing with Google Analytics, unlike Matomo. 

    Wrap Up 

    Google set a high bar for web analytics. But Google Analytics inherent limitations around privacy, reporting and deployment options prompt more users to consider Google Analytics alternatives, like Matomo. 

    With Matomo, you can easily migrate your historical data records and store customer data locally or in a designated cloud location. We operate by a 100% unsampled data principle and provide an array of privacy controls for advanced compliance. 

    Start your 21-day free trial (no credit card required) to see how Matomo compares to Google Analytics ! 

  • 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.