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  • MediaSPIP version 0.1 Beta

    16 avril 2011, par

    MediaSPIP 0.1 beta est la première version de MediaSPIP décrétée comme "utilisable".
    Le fichier zip ici présent contient uniquement les sources de MediaSPIP en version standalone.
    Pour avoir une installation fonctionnelle, il est nécessaire d’installer manuellement l’ensemble des dépendances logicielles sur le serveur.
    Si vous souhaitez utiliser cette archive pour une installation en mode ferme, il vous faudra également procéder à d’autres modifications (...)

  • MediaSPIP 0.1 Beta version

    25 avril 2011, par

    MediaSPIP 0.1 beta is the first version of MediaSPIP proclaimed as "usable".
    The zip file provided here only contains the sources of MediaSPIP in its standalone version.
    To get a working installation, you must manually install all-software dependencies on the server.
    If you want to use this archive for an installation in "farm mode", you will also need to proceed to other manual (...)

  • Amélioration de la version de base

    13 septembre 2013

    Jolie sélection multiple
    Le plugin Chosen permet d’améliorer l’ergonomie des champs de sélection multiple. Voir les deux images suivantes pour comparer.
    Il suffit pour cela d’activer le plugin Chosen (Configuration générale du site > Gestion des plugins), puis de configurer le plugin (Les squelettes > Chosen) en activant l’utilisation de Chosen dans le site public et en spécifiant les éléments de formulaires à améliorer, par exemple select[multiple] pour les listes à sélection multiple (...)

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  • Privacy-friendly analytics : The benefits of an ethical, GDPR-compliant platform

    13 juin, par Joe

    Your visitors shouldn’t feel like you’re spying on them — even if you’re just trying to improve the user experience or track your marketing efforts. 

    While many analytics platforms make customers feel that way thanks to intrusive cookie consent banners and highly personalised ads, there is a growing movement towards ethical, privacy-friendly analytics.

    In this article, you’ll learn what privacy-friendly analytics is, why it matters, what to look for in a solution and which of the leading providers is right for you. 

    What is privacy-friendly analytics ? 

    Privacy-friendly analytics is a form of website analytics that collects and analyses data in a way that respects the user’s privacy. It’s a type of ethical web analytics.

    Privacy-friendly platforms limit personal data collection and anonymise individual user data while being transparent about collection and tracking methods. They help companies adhere to data protection laws (like GDPR, CCPA, and HIPAA) and new privacy laws (like OCPA, FDBR, and TDPSA) without configuring custom settings. 

    Why use privacy-friendly analytics ? 

    Millions of businesses choose privacy-friendly analytics platforms like Matomo. Here are a few reasons why : 

    Build trust with customers

    Research shows that the vast majority of consumers don’t trust companies with their data, believing that they prioritise profits over data protection. 

    Privacy-friendly analytics can help businesses prove they aren’t out to profit from consumer data and regain customer trust. This can ultimately boost revenue. According to Cisco’s Data Privacy Benchmark Study, organisations gain $180 for every $100 spent on privacy. 

    Comply with privacy regulations

    Data privacy regulations, such as GDPR, protect consumer privacy and establish strict rules governing how businesses can collect and use personal data.

    The cost of non-compliance is high. Under GDPR, fines can be up to €20 million, or 4% of worldwide annual revenue.

    Thanks to features like data anonymisation and the default use of first-party cookies, privacy-friendly analytics platforms can support and strengthen compliance efforts. 

    In fact, the French Data Protection Authority (CNIL) approved Matomo as one of the only web analytics tools to collect data without tracking consent.

    Minimise the impact of a breach

    According to IBM’s Cost of a Data Breach report, the average cost of a data breach is nearly $4.5 million. The more personally identifiable information (PII) is involved, the higher the fines and penalties. 

    A privacy-friendly analytics tool can reduce the potential impact of a breach by minimising the amount of personal information you hold. 

    Is Google Analytics privacy-friendly ?

    Google may be the best-known analytics platform, but it’s not the best choice for businesses that want to collect data responsibly and ethically. 

    Here are just a few of Google Analytics’s privacy issues :

    • It uses analytics data to run its advertising business.
    • It may train large language models like Gemini with analytics data.
    • It requires a specific setup to be GDPR compliant that isn’t available out of the box.

    Google Analytics’s ongoing issues with privacy laws like GDPR also raise doubt. The French and Austrian Data Protection Authorities have banned Google Analytics in the past, and there is no guarantee they won’t do so again. 

    What to look for in privacy-friendly analytics ?

    Several privacy-friendly analytics tools are available. To find the right one for your brand, look for the following features.

    Data ownership

    Choose a provider that gives you as much control over your users’ data as possible. Ideally, this will be via an on-site solution where you store data on your servers. For cloud-based options, ensure your analytics provider can’t access, use or sell it.

    With 100% data ownership, you have the power to protect your users’ privacy. You know where your customer data is stored and what’s happening to it without external influence.

    Open source

    The only genuinely privacy-friendly software is open-source software. Open-source software means anyone can review the code to ensure it does what it promises — in this case, maximising privacy. 

    Matomo is an open-source software company. Our source code is on GitHub, where everyone can see precisely how our platform tracks and stores user data. A community of developers also regularly examines and reviews our code to further strengthen security. 

    Data anonymisation 

    Privacy-friendly analytics should allow marketers to completely anonymise the data they collect. They achieve this through several techniques like IP anonymisation and pseudonymised user IDs that modify or remove personally identifiable data so it can’t be linked to individuals.

    Data anonymisation settings Matomo

    Matomo’s data anonymisation settings 

    In Matomo, for example, you can anonymise the following things in the platform’s Privacy settings :

    • IP address
    • Location
    • User ID

    IP address anonymisation is enabled by default in Matomo.

    No data sampling 

    Data sampling involves extrapolating analytics reports from an incomplete data set. Google Analytics uses this practice and relies on estimates, leading to incomplete and potentially inaccurate results.

    Privacy-friendly analytics should provide 100% accurate insights without making assumptions about your users’ data.

    GDPR compliance

    Privacy-friendly web analytics platforms adhere to even the strictest privacy laws, including GDPR, HIPAA and CCPA, thanks to the following features :

    • Data anonymisation
    • Cookieless tracking
    • EU data storage
    • First-party cookies by default
    Data subject access request setting Matomo

    Matomo data subject access request settings
    (Image Source)

    Privacy-first platforms also make it easy for companies to fulfil data subject access requests. In Matomo, for example, a dedicated feature lets you find, download and delete all of the data you hold about specific individuals. 

    Cookieless tracking

    Cookieless tracking is a form of visitor tracking that uses methods other than cookies to identify individual users. It is more privacy-friendly because no personal data is collected, and users can withhold consent from cookie banners.

    Matomo uses the most privacy-friendly industry-leading cookieless tracking method, config_id, to anonymously track visitors without fingerprinting them. 

    Top 3 privacy-friendly analytics platforms

    We’ve shortlisted three of the leading privacy-friendly analytics platforms. Learn what they offer, what makes them different and how much they cost.

    Matomo

    Matomo is an open-source web analytics tool and privacy-focused Google Analytics alternative trusted by over one million sites in over 190 countries and over 50 languages. 

    Matomo dashboard

    Matomo dashboard

    Matomo prioritises privacy and keeping businesses compliant with global privacy regulations like GDPR, CCPA and HIPAA. The data you collect is 100% accurate and yours alone. We don’t share it or use it for other purposes. 

    Benefits

    • Matomo’s all-in-one solution offers traditional web and behavioural analytics, such as heatmaps and session recordings. It also includes a free, open-source tag manager
    • Matomo gives you the choice of where to store your user’s data. With Matomo Cloud, that’s in our European servers. With Matomo On-Premise, that’s on your servers.
    • Matomo is open-source. Hundreds of independent developers have reviewed our code, and you can view it yourself on GitHub.

    Pricing 

    Hosting Matomo On-Premise is free, while Matomo Cloud costs $26 per month. 

    Fathom

    Fathom Analytics is a simple, easy-to-use alternative to Google Analytics that puts a premium on privacy. 

    Fathom dashboard

    Fathom dashboard
    (Image Source)

    Fathom has made its platform as easy to use as possible. You can install Fathom on any website or CMS using a single line of code. It also means the platform won’t massively impact your site’s speed or SEO performance. 

    Benefits

    • Fathom complies with all major privacy regulations, including GDPR and CCPA.
    • Fathom doesn’t sample data. It also blocks bots and scrapers, so you only see human visitors.
    • Fathom anonymises IP addresses, so you don’t have to show cookie banners.

    Drawbacks

    • Fathom doesn’t offer many of Matomo’s advanced features like e-commerce tracking, heatmaps, and session recordings.
    • The premium version of Fathom is not open-source. 

    Pricing 

    From $15 per month.

    Plausible

    Plausible Analytics is an open-source, privacy-friendly analytics tool built and hosted in the EU.

    Plausible dashboard

    Plausible dashboard
    (Image Source)

    The platform launched in 2019 as a lightweight, easy-to-use alternative to Google Analytics. Its simplicity is a big selling point. Instead of dozens of menus, it presents the information you need on a single page.

    Benefits

    • Plausible boasts an ultra-lightweight script, which means it has a minimal impact on page loading times. 
    • Plausible is GDPR and CCPA-compliant by design, so there’s no need for cookie banners.
    • Plausible is an open-source software with the source code available on GitHub.

    Drawbacks

    • Plausible lacks advanced privacy controls like a GDPR manager.
    • It has none of Matomo’s advanced features like A/B testing, session recordings or heatmaps. 

    Pricing 

    From $9 per month

    Try Matomo for free

    Ready to try a privacy-friendly analytics solution ? Making the switch is easy with Matomo, as it’s one of the only platforms to import historical Google Analytics data. You can also try Matomo for free for 21 days — no credit card required. 

  • What Is Incrementality & Why Is It Important in Marketing ?

    26 mars 2024, par Erin

    Imagine this : you just launched your latest campaign and it was a major success.

    You blew last month’s results out of the water.

    You combined a variety of tactics, channels and ad creatives to make it work.

    Now, it’s time to build the next campaign.

    The only issue ?

    You don’t know what made it successful or how much your recent efforts impacted the results.

    You’ve been building your brand for years. You’ve built up a variety of marketing pillars that are working for you. So, how do you know how much of your campaign is from years of effort or a new tactic you just implemented ?

    The key is incrementality.

    This is a way to properly attribute the right weight to your marketing tactics.

    In this article, we break down what incrementality is in marketing, how it differs from traditional attribution and how you can calculate and track it to grow your business.

    What is incrementality in marketing ?

    Incrementality in marketing is growth that can be directly credited to a marketing effort above and beyond the success of the branding.

    It looks at how much a specific tactic positively impacted a campaign on top of overall branding and marketing strategies.

    What is incrementally in marketing?

    For example, this could be how much a specific tactic, campaign or channel helped increase conversions, email sign-ups or organic traffic.

    The primary purpose of incrementally in marketing is to more accurately determine the impact a single marketing variable had on the success of a project.

    It removes every other factor and isolates the specific method to help marketers double down on that strategy or move on to new tactics.

    With Matomo, you can track conversions simply. With our last non-direct channel attribution system, you’ll be able to quickly see what channels are converting (and which aren’t) so you can gain insights into incrementality. 

    See why over 1 million websites choose Matomo today.

    Try Matomo for Free

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

    No credit card required

    How incrementality differs from attribution

    In marketing and advertising, it’s crucial to understand what tactics and activities drive growth.

    Incrementality and attribution help marketers and business owners understand what efforts impact their results.

    But they’re not the same.

    Here’s how they differ :

    Incrementality vs. attribution

    Incrementality explained

    Incrementality measures how much a specific marketing campaign or activity drives additional sales or growth.

    Simply put, it’s analysing the difference between having never implemented the campaign (or tactic or channel) in the first place versus the impact of the activity.

    In other words, how much revenue would you have generated this month without campaign A ?

    And how much additional revenue did you generate directly due to campaign A ?

    The reality is that dozens of factors impact revenue and growth.

    You aren’t just pouring your marketing into one specific channel or campaign at a time.

    Chances are, you’ve got your hands on several marketing initiatives like SEO, PPC, organic social media, paid search, email marketing and more.

    Beyond that, you’ve built a brand with a not-so-tangible impact on your recurring revenue.

    So, the question is, if you took away your new campaign, would you still be generating the same amount of revenue ?

    And, if you add in that campaign, how much additional revenue and growth did it directly create ?

    That is incrementality. It’s how much a campaign went above and beyond to add new revenue that wouldn’t have been there otherwise.

    So, how does attribution play into all of this ?

    Attribution explained

    Attribution is simply the process of assigning credit for a conversion to a particular marketing touchpoint.

    While incrementality is about narrowing down the overall revenue impact from a particular campaign, attribution seeks to point to a specific channel to attribute a sale.

    For example, in any given marketing campaign, you have a few marketing tactics.

    Let’s say you’re launching a limited-time product.

    You might have :

    • Paid ads via Facebook and Instagram
    • A blog post sharing how the product works
    • Organic social media posts on Instagram and TikTok
    • Email waitlist campaign building excitement around the upcoming product
    • SMS campaigns to share a limited-time discount

    So, when the time comes for the sale launch, and you generate $30,000 in revenue, what channel gets the credit ?

    Do you give credit to the paid ads on Facebook ? What about Instagram ? They got people to follow you and got them on the email waitlist.

    Do you give credit to email for reminding people of the upcoming sale ? What about your social media posts that reminded people there ?

    Or do you credit your SMS campaign that shared a limited-time discount ?

    Which channel is responsible for the sale ?

    This is what attribution is all about.

    It’s about giving credit where credit is due.

    The reason you want to attribute credit ? So you know what’s working and can double down your efforts on the high-impact marketing activities and channels.

    Leveraging incrementality and attribution together

    Incrementality and attribution aren’t competing methods of analysing what’s working.

    They’re complementary to one another and go hand in hand.

    You can (and should) use attribution and incrementality in your marketing to help understand what activities, campaigns and channels are making the biggest incremental impact on your business growth.

    Why it’s important to measure incrementality

    Incrementality is crucial to measure if you want to pour your time, money and effort into the right marketing channels and tactics.

    Here are a few reasons why you need to measure incrementality if you want to be successful with your marketing and grow your business :

    1. Accurate data

    If you want to be an effective marketer, you need to be accurate.

    You can’t blindly start marketing campaigns in hopes that you will sell many products or services.

    That’s not how it works.

    Sure, you’ll probably make some sales here and there. But to truly be effective with your work, you must measure your activities and channels correctly.

    Incrementality helps you see how each channel, tactic or campaign made a difference in your marketing.

    Matomo gives you 100% accurate data on your website activities. Unlike Google Analytics, we don’t use data sampling which limits how much data is analysed.

    Screenshot example of the Matomo dashboard

    2. Helps you to best determine the right tactics for success

    How can you plan your marketing strategy if you don’t know what’s working ?

    Think about it.

    You’ll be blindly sailing the seas without a compass telling you where to go.

    Measuring incrementality in your marketing tactics and channels helps you understand the best tactics.

    It shows you what’s moving the needle (and what’s not).

    Once you can see the most impactful tactics and channels, you can forge future campaigns that you know will work.

    3. Allows you to get the most out of your marketing budget

    Since incrementality sheds light on what’s moving your business forward, you can confidently implement your efforts on the right tactics and channels.

    Guess what happens when you start doubling down on the most impactful activities ?

    You start increasing revenue, decreasing ad spend and getting a higher return on investment.

    The result is that you will get more out of your marketing budget.

    Not only will you boost revenue, but you’ll also be able to boost profit margins since you’re not wasting money on ineffective tactics.

    4. Increase traffic

    When you see what’s truly working in your business, you can figure out what channels and tactics you should be working.

    Incrementality helps you understand not only what your best revenue tactics are but also what channels and campaigns are bringing in the most traffic.

    When you can increase traffic, you can increase your overall marketing impact.

    5. Increase revenue

    Finally, with increased traffic, the inevitable result is more conversions.

    More conversions mean more revenue.

    Incrementality gives you a vision of the tactics and channels that are converting the best.

    If you can see that your SMS campaigns are driving the best ROI, then you know that you’ll grow your revenue by pouring more into acquiring SMS leads.

    By calculating incrementality regularly, you can rest assured that you’re only investing time and money into the most impactful activities in terms of revenue generation.

    How to calculate and test incrementality in marketing

    Now that you understand how incrementality works and why it’s important to calculate, the question is : 

    How do you calculate and conduct incrementality tests ?

    Given the ever-changing marketing landscape, it’s crucial to understand how to calculate and test incrementally in your business.

    If you’re not sure how incrementality testing works, then follow these simple steps :

    How to test and analyze incrementality in marketing?

    Your first step to get an incrementality measurement is to conduct what’s referred to as a “holdout test.”

    It’s not a robust test, but it’s an easy way to get the ball rolling with incrementality.

    Here’s how it works :

    1. Choose your target audience.

    With Matomo’s segmentation feature, you can get pretty specific with your target audience, such as :

      • Visitors from the UK
      • Returning visitors
      • Mobile users
      • Visitors who clicked on a specific ad
    1. Split your audience into two groups :
      • Control group (60% of the segment)
      • Test group (40% of the segment)
    1. Target the control group with your marketing tactic (the simpler the tactic, the better).
    1. Target the test group with a different marketing tactic.
    1. Analyse the results. The difference between the control and test groups is the incremental lift in results. The new marketing tactic is either more effective or not.
    1. Repeat the test with a new control group (with an updated tactic) and a new test group (with a new tactic).

    Matomo can help you analyse the results of your campaigns in our Goals feature. Set up business objectives so you can easily track different goals like conversions.

    Try Matomo for Free

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

    No credit card required

    Here’s an example of how this incrementality testing could look in real life.

    Imagine a fitness retailer wants to start showing Facebook ads in their marketing mix.

    The marketing manager decided to conduct a holdout test. If we match our example below with the steps above, this is how the holdout test might look.

    1. They choose people who’ve purchased free weights in the past as their target audience (see how that segmentation works ?).
    2. They split this segment into a control group and a test group.
    3. For this test, they direct their regular marketing campaign to the control group (60% of the segment). The campaign includes promoting a 20% off sale on organic social media posts, email marketing, and SMS.
    4. They direct their regular marketing campaign plus Facebook ads to the test group (40% of the segment).
    5. They ran the campaign for three weeks with the goal for sale conversions and noticed :
      • The control group had a 1.5% conversion rate.
      • The test group (with Facebook ads) had a 2.1% conversion rate.
      • In this scenario, they could see the group who saw the Facebook ads convert better.
      • They created the following formula to measure the incremental lift of the Facebook ads :
    Calculation: Incrementality in marketing.
      • Here’s how the calculation works out : (2.1% – 1.5%) / 1.5% = 40%

    The Facebook ads had a positive 40% incremental lift in conversions during the sale.

    Incrementality testing isn’t a one-and-done process, though.

    While this first test is a great sign for the marketing manager, it doesn’t mean they should immediately throw all their money into Facebook ads.

    They should continue conducting tests to verify the initial test.

    Use Matomo to track incrementality today

    Incrementality can give you insights into exactly what’s working in your marketing (and what’s not) so you can design proven strategies to grow your business.

    If you want more help tracking your marketing efforts, try Matomo today.

    Our web analytics and behaviour analytics platform gives you firsthand data on your website visitors you can use to craft effective marketing strategies.

    Matomo provides 100% accurate data. Unlike other major web analytics platforms, we don’t do data sampling. What you see is what’s really going on in your website. That way, you can make more informed decisions for better results.

    At Matomo, we take privacy very seriously and include several advanced privacy protections to ensure you are in full control.

    As a fully compliant web analytics solution, we’re fully compliant with some of the world’s strictest privacy regulations like GDPR. With Matomo, you get peace of mind knowing you can make data-driven decisions while also being compliant. 

    If you’re ready to launch a data-driven marketing strategy today and grow your business, get started with our 21-day free trial now. No credit card required.

  • A Beginner’s Guide to Omnichannel Analytics

    14 avril 2024, par Erin

    Linear customer journeys are as obsolete as dial-up internet and floppy disks. As a marketing manager, you know better than anyone that customers interact with your brand hundreds of times across dozens of channels before purchasing. That can make tracking them a nightmare unless you build an omnichannel analytics solution. 

    Alas, if only it were that simple. 

    Unfortunately, it’s not enough to collect data on your customers’ complex journeys just by buying an omnichannel platform. You need to generate actionable insights by using marketing attribution to tie channels to conversions. 

    This article will explain how to build a useful omnichannel analytics solution that lets you understand and improve the customer journey.

    What is omnichannel analytics ?

    Omnichannel analytics collects and analyses customer data from every touchpoint and device. The goal is to collect all this omnichannel data in one place, creating a single, real-time, unified view of your customer’s journey.

    What is omnichannel analytics

    Unfortunately, most businesses haven’t achieved this yet. As Karen Lellouche Tordjman and Marco Bertini say :

    “Despite all the buzz around the concept of omnichannel, most companies still view customer journeys as a linear sequence of standardised touchpoints within a given channel. But the future of customer engagement transforms touchpoints from nodes along a predefined distribution path to full-blown portals that can serve as points of sale or pathways to many other digital and virtual interactions. They link to chatbots, kiosks, robo-advisors, and other tools that customers — especially younger ones — want to engage with.”

    However, doing so is more important than ever — especially when consumers have over 300 digital touchpoints, and the average number of touchpoints in the B2B buyer journey is 27.

    Not only that, but customers expect personalised experiences across every platform — that’s the kind you can only create when you have access to omnichannel data.

    A diagram showing how complex customer journeys are

    What might omnichannel analytics look like in practice for an e-commerce store ?

    An online store would integrate data from channels like its website, mobile app, social media accounts, Google Ads and customer service records. This would show how customers find its brand, how they use each channel to interact with it and which channels convert the most customers. 

    This would allow the e-commerce store to tailor marketing channels to customers’ needs. For instance, they could focus social media use on product discovery and customer support. Google Ads campaigns could target the best-converting products. While all this is happening, the store could also ensure every channel looks the same and delivers the same experience. 

    What are the benefits of omnichannel analytics ?

    Why go to all the trouble of creating a comprehensive view of the customer’s experience ? Because you stand to gain some pretty significant benefits when implementing omnichannel analytics.

    What are the benefits of omnichannel analytics?

    Understand the customer journey

    You want to understand how your customers behave, right ? No other method will allow you to fully understand your customer journey the way omnichannel analytics does. 

    It doesn’t matter how customers engage with your brand — whether that’s your website, app, social media profiles or physical stores — omnichannel analytics capture every interaction.

    With this 360-degree view of your customers, it’s easy to understand how they move between channels, where they encounter issues and what bottlenecks prevent them from converting. 

    Deliver better personalisation

    We don’t have to tell you that personalisation matters. But do you know just how important it is ? Since 56% of customers will become repeat buyers after a personalised experience, delivering them as often as possible is critical. 

    Omnichannel analytics helps in your quest for personalisation by highlighting the individual preferences of customer segments. For example, e-commerce stores can use omnichannel analytics to understand how shoppers behave across different devices and tailor their offers accordingly. 

    Upgrade the customer experience

    Omnichannel analytics gives you the insights to improve every aspect of the customer experience. 

    For starters, you can ensure a consistent brand experience across all your top channels by making sure they look and behave the same.

    Then, you can use omnichannel insights to tailor each channel to your customers’ requirements. For example, most people interacting with your brand on social media may seek support. Knowing that you can create dedicated support accounts to assist users. 

    Improve marketing campaigns

    Which marketing campaigns or traffic sources convert the most customers ? How can you improve these campaigns ? Omnichannel analytics has the answers. 

    When you implement omnichannel analytics you automatically track the performance of every marketing channel by attributing each conversion to one or more traffic sources. This lets you see whether Google Ads bring in more customers than your SEO efforts. Or whether social media ads are the most profitable acquisition channel. 

    Armed with this information, you can improve your marketing efforts — either by focusing on your profitable channels or rectifying problems that stop less profitable channels from converting.

    What are the challenges of omnichannel analytics ?

    There are three challenges when implementing an omnichannel analytics solution :

    What are the challenges of omnichannel analytics?
    • Complex customer journeys : Customer journeys aren’t linear and can be incredibly difficult to track. 
    • Regulatory and privacy issues : When you start gathering customer data, you quickly come up against consumer privacy laws. 
    • No underlying goal : There has to be a reason to go to all this effort, but brands don’t always have goals in mind before they start. 

    You can’t do anything about the first challenge. 

    After all, your customer journey will almost never be linear. And isn’t the point of implementing an omnichannel solution to understand these complex journeys in the first place ? Once you set up omnichannel analytics, these journeys will be much easier to decipher. 

    As for the other two :

    Using the right software that respects user privacy and complies with all major privacy laws will avoid regulatory issues. Take Matomo, for instance. Our software was designed with privacy in mind and is configured to follow the strictest privacy laws, such as GDPR. 

    Tying omnichannel analytics to marketing attribution will solve the final challenge by giving your omnichannel efforts a goal. When you tie omnichannel analytics to your marketing efforts, you aren’t just getting a 360-degree view of your customer journey for the sake of it. You are getting that view to improve your marketing efforts and increase sales.

    Try Matomo for Free

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

    No credit card required

    How to set up an omnichannel analytics solution

    Want to set up a seamless analytical environment that incorporates data from every possible source ? Follow these five steps :

    Choose one or more analytics providers

    You can use several tools to build an omnichannel analytics solution. These include web and app analytics tools, customer data platforms that centralise first-party data and business intelligence tools (typically used for visualisation). 

    Which tools you use will depend on your goals and your budget — the loftier your ambitions and the higher your budget, the more tools you can use. 

    Ideally, you should use as few tools as possible to capture your data. Most teams won’t need business intelligence platforms, for example. However, you may or may not need both an analytics platform and a customer data platform. Your decision will depend on how many channels your customers use and how well your analytics tool tracks everything.

    If it can capture web and app usage while integrating with third-party platforms like your back-end e-commerce platform, then it’s probably enough.

    Collect accurate data at every touchpoint 

    Your omnichannel analytics efforts hinge on the quantity and quality of data you can collect. You want to gather data from every touchpoint possible and store that data in as few places as possible. That’s why choosing as few tools as possible in the step above is so important. 

    So, where should you start ? Common data sources include :

    • Your website
    • Apps (iOS and Android)
    • Social media profiles
    • ERPs
    • PoS systems

    At the same time, make sure you’re tracking all relevant metrics. Revenue, customer engagement and conversion-focused metrics like conversion rate, dwell time, cart abandonment rate and churn rate are particularly important. 

    Set up marketing attribution

    Setting up marketing attribution (also known as multi-touch attribution) is essential to tie omnichannel data to business goals. It’s the only way to know exactly how valuable each marketing channel is and where each customer comes from. 

    You’ll want to use multi-touch attribution, given you have data from across the customer journey.

    Image of six different attribution models

    Multi-touch attribution models can include (but are not limited to) :

    • Linear : where each touchpoint is given equal weighting
    • Time decay : where touchpoints are more valuable the nearer they are to conversion
    • Position-based : where the first and last touch points are more valuable than all the others. 

    You don’t have to use just one of the models above, however. One of the benefits of using a web analytics tool like Matomo is that you can choose between different attribution models and compare them.

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    Create reports that help you visualise data

    Dashboards are your friend here. They’ll let you see KPIs at a glance, allowing you to keep track of day-to-day changes in your customer journey. Ideally, you’ll want a platform that lets you customise dashboard widgets so only relevant KPIs are shown. 

    A custom graph created in Matomo

    Setting up standard and custom reports is also important. Custom reports allow you to choose metrics and dimensions that align with your goals. They will also allow you to present your data most meaningfully to your team, increasing the likelihood they act upon insights. 

    Analyse data and take action

    Now that you have customer journey data at your fingertips, it’s time to analyse it. After all, there’s no point in implementing an omnichannel analytics solution if you aren’t going to take action. 

    If you’re unsure where to start, re-read the benefits we listed at the start of this article. You could use your omnichannel insights to improve your marketing campaigns by doubling down on the channels that bring in the best customers.

    Or you could identify (and fix) bottlenecks in the customer journey so customers are less likely to fall out of your funnel between certain channels. 

    Just make sure you take action based on your data alone.

    Make the most of omnichannel analytics with Matomo

    A comprehensive web and app analytics platform is vital to any omnichannel analytics strategy. 

    But not just any solution will do. When privacy regulations impede an omnichannel analytics solution, you need a platform to capture accurate data without breaking privacy laws or your users’ trust. 

    That’s where Matomo comes in. Our privacy-friendly web analytics platform ensures accurate tracking of web traffic while keeping you compliant with even the strictest regulations. Moreover, our range of APIs and SDKs makes it easy to track interactions from all your digital products (website, apps, e-commerce back-ends, etc.) in one place. 

    Try Matomo for free for 21 days. No credit card required.