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• Making Your First-Party Data Work for You and Your Customers

  11 mars, par Alex Carmona

  At last count, 162 countries had enacted data privacy policies of one kind or another. These laws or regulations, without exception, intend to eliminate the use of third-party data. That puts marketing under pressure because third-party data has been the foundation of online marketing efforts since the dawn of the Internet.

  Marketers need to future-proof their operations by switching to first-party data. This will require considerable adjustment to systems and processes, but the reward will be effective marketing campaigns that satisfy privacy compliance requirements and bring the business closer to its customers.

  To do that, you’ll need a coherent first-party data strategy. That’s what this article is all about. We’ll explain the different types of personal data and discuss how to use them in marketing without compromising or breaching data privacy regulations. We’ll also discuss how to build that strategy in your business. 

  So, let’s dive in.

  The different data types

  There are four distinct types of personal data used in marketing, each subject to different data privacy regulations.

  Before getting into the different types, it’s essential to understand that all four may comprise one or more of the following :

  Identifying data	Name, email address, phone number, etc.
  Behavioural data	Website activity, app usage, wishlist content, purchase history, etc.
  Transactional data	Orders, payments, subscription details, etc.
  Account data	Communication preferences, product interests, wish lists, etc.
  Demographic data	Age, gender, income level, education, etc.
  Geographic Data	Location-based information, such as zip codes or regional preferences.
  Psychographic Data	Interests, hobbies and lifestyle preferences.

  First-party data

  When businesses communicate directly with customers, any data they exchange is first-party. It doesn’t matter how the interaction occurs : on the telephone, a website, a chat session, or even in person.

  Of course, the parties involved aren’t necessarily individuals. They may be companies, but people within those businesses will probably share at least some of the data with colleagues. That’s fine, so long as the data : 

  • Remains confidential between the original two parties involved, and 
  • It is handled and stored following applicable data privacy regulations.

  The core characteristic of first-party data is that it’s collected directly from customer interactions. This makes it reliable, accurate and inherently compliant with privacy regulations — assuming the collecting party complies with data privacy laws.

  A great example of first-party data use is in banking. Data collected from customer interactions is used to provide personalised services, detect fraud, assess credit risk and improve customer retention.

  Zero-party data

  There’s also a subset of first-party data, sometimes called zero-party data. It’s what users intentionally and proactively share with a business. It can be preferences, intentions, personal information, survey responses, support tickets, etc.

  What makes it different is that the collection of this data depends heavily on the user’s trust. Transparency is a critical factor, too ; visitors expect to be informed about how you’ll use their data. Consumers also have the right to withdraw permission to use all or some of their information at any time.

  

  Second-party data

  This data is acquired from a separate organisation that collects it firsthand. Second-party data is someone else’s first-party data that’s later shared with or sold to other businesses. The key here is that whoever owns that data must give explicit consent and be informed of who businesses share their data with.

  A good example is the cooperation between hotel chains, car rental companies, and airlines. They share joint customers’ flight data, hotel reservations, and car rental bookings, much like travel agents did before the internet undermined that business model.

  Third-party data

  This type of data is the arch-enemy of lawmakers and regulators trying to protect the personal data of citizens and residents in their country. It’s information collected by entities that have no direct relationship with the individuals whose data it is.

  Third-party data is usually gathered, aggregated, and sold by data brokers or companies, often by using third-party cookies on popular websites. It’s an entire business model — these third-party brokers sell data for marketing, analytics, or research purposes. 

  Most of the time, third-party data subjects are unaware that their data has been gathered and sold. Hence the need for strong data privacy regulations.

  Benefits of a first-party data strategy

  First-party data is reliable, accurate, and ethically sourced. It’s an essential part of any modern digital marketing strategy.

  More personalised experiences

  The most important application of first-party data is customising and personalising customers’ interactions based on real behaviours and preferences. Personalised experiences aren’t restricted to websites and can extend to all customer communication.

  The result is company communications and marketing messages are far more relevant to customers. It allows businesses to engage more meaningfully with them, building trust and strengthening customer relationships. Inevitably, this also results in stronger customer loyalty and better customer retention.

  Greater understanding of customers

  Because first-party data is more accurate and reliable, it can be used to derive valuable insights into customer needs and wants. When all the disparate first-party data points are centralised and organised, it’s possible to uncover trends and patterns in customer behaviour that might not be apparent using other data.

  This helps businesses predict and respond to customer needs. It also allows marketing teams to be more deliberate when segmenting customers and prospects into like-minded groups. The data can also be used to create more precise personas for future campaigns or reveal how likely a customer would be to purchase in response to a campaign.

  Build trust with customers

  First-party data is unique to a business and originates from interactions with customers. It’s also data collected with consent and is “owned” by the company — if you can ever own someone else’s data. If treated like the precious resource, it can help businesses build trust with customers.

  However, developing that trust requires a transparent, step-by-step approach. This gradually strengthens relationships to the point where customers are more comfortable sharing the information they’re asked for.

  However, while building trust is a long and sometimes arduous process, it can be lost in an instant. That’s why first-party data must be protected like the Crown Jewels.

  

  Components of a first-party data strategy

  Security is essential to any first-party data strategy, and for good reason. As Gartner puts it, a business must find the optimal balance between business outcomes and data risk mitigation. Once security is baked in, attention can turn to the different aspects of the strategy.

  Data collection

  There are many ways to collect first-party data ethically, within the law and while complying with data privacy regulations, such as Europe’s General Data Protection Regulation (GDPR). Potential sources include :

  Website activity	forms and surveys, behavioural tracking, cookies, tracking pixels and chatbots
  Mobile app interactions	in-app analytics, push notifications and in-app forms
  Email marketing	newsletter sign-ups, email engagement tracking, promotions, polls and surveys
  Events	registrations, post-event surveys and virtual event analytics
  Social media interaction	polls and surveys, direct messages and social media analytics
  Previous transactions	purchase history, loyalty programmes and e-receipts
  Customer service	call centre data, live chat, chatbots and feedback forms
  In-person interactions	in-store purchases, customer feedback and Wi-Fi sign-ins
  Gated content	whitepapers, ebooks, podcasts, webinars and video downloads
  Interactive content	quizzes, assessments, calculators and free tools
  CRM platforms	customer profiles and sales data
  Consent management	privacy policies, consent forms, preference setting

  Consent management

  It may be the final item on the list above, but it’s also a key requirement of many data privacy laws and regulations. For example, the GDPR is very clear about consent : “Processing personal data is generally prohibited, unless it is expressly allowed by law, or the data subject has consented to the processing.”

  For that reason, your first-party data strategy must incorporate various transparent consent mechanisms, such as cookie banners and opt-in forms. Crucially, you must provide customers with a mechanism to manage their preferences and revoke that consent easily if they wish to.

  Data management

  Effective first-party data management, mainly its security and storage, is critical. Most data privacy regimes restrict the transfer of personal data to other jurisdictions and even prohibit it in some instances. Many even specify where residents’ data must be stored.

  Consider this cautionary tale : The single biggest fine levied for data privacy infringement so far was €1.2 billion. The Irish Data Protection Commission imposed a massive fine on Meta for transferring EU users’ data to the US without adequate data protection mechanisms.

  Data security is critical. If first-party data is compromised, it becomes third-party data, and any customer trust developed with the business will evaporate. To add insult to injury, data regulators could come knocking. That’s why the trend is to use encryption and anonymisation techniques alongside standard access controls.

  Once security is assured, the focus is on data management. Many businesses use a Customer Data Platform. This software gathers, combines and manages data from many sources to create a complete and central customer profile. Modern CRM systems can also do that job. AI tools could help find patterns and study them. But the most important thing is to keep databases clean and well-organised to make it easier to use and avoid data silos.

  Data activation

  Once first-party data has been collected and analysed, it needs to be activated, which means a business needs to use it for the intended purpose. This is the implementation phase where a well-constructed first-party strategy pays off. 

  The activation stage is where businesses use the intelligence they gather to :

  • Personalise website and app experiences
  • Adapt marketing campaigns
  • Improve conversion rates
  • Match stated preferences
  • Cater to observed behaviours
  • Customise recommendations based on purchase history
  • Create segmented email campaigns
  • Improve retargeting efforts
  • Develop more impactful content

  Measurement and optimisation

  Because first-party data is collected directly from customers or prospects, it’s far more relevant, reliable, and specific. Your analytics and campaign tracking will be more accurate. This gives you direct and actionable insights into your audience’s behaviour, empowering you to optimise your strategies and achieve better results.

  The same goes for your collection and activation efforts. An advanced web analytics platform like Matomo lets you identify key user behaviour and optimise your tracking. Heatmaps, marketing attribution tools, user behaviour analytics and custom reports allow you to segment audiences for better traction (and collect even more first-party data).

  

  How to build a first-party data strategy

  There are five important and sequential steps to building a first-party data strategy. But this isn’t a one-time process. It must be revisited regularly as operating and regulatory environments change. There are five steps : 

  1. Audit existing data

  Chances are that customers already freely provide a lot of first-party data in the normal course of business. The first step is to locate this data, and the easiest way to do that is by mapping the customer journey. This identifies all the touchpoints where first-party data might be found.

  2. Define objectives

  Then, it’s time to step back and figure out the goals of the first-party data strategy. Consider what you’re trying to achieve. For example :

  • Reduce churn 
  • Expand an existing loyalty programme
  • Unload excess inventory
  • Improve customer experiences

  Whatever the objectives are, they should be clear and measurable.

  3. Implement tools and technology

  The first two steps point to data gaps. Now, the focus turns to ethical web analytics with a tool like Matomo. 

  To further comply with data privacy regulations, it may also be appropriate to implement a Consent Management Platform (CMP) to help manage preferences and consent choices.

  4. Build trust with transparency

  With the tools in place, it’s time to engage customers. To build trust, keep them informed about how their data is used and remind them of their right to withdraw their consent. 

  Transparency is crucial in such engagement, as outlined in the 7 GDPR principles.

  5. Continuously improve

  Rinse and repeat. The one constant in business and life is change. As things change, they expose weaknesses or flaws in the logic behind systems and processes. That’s why a first-party data strategy needs to be continually reviewed, updated, and revised. It must adapt to changing trends, markets, regulations, etc. 

  Tools that can help

  Looking back at the different types of data, it’s clear that some are harder and more bothersome to get than others. But capturing behaviours and interactions can be easy — especially if you use tools that follow data privacy rules.

  But here’s a tip. Google Analytics 4 isn’t compliant by default, especially not with Europe’s GDPR. It may also struggle to comply with some of the newer data privacy regulations planned by different US states and other countries.

  Matomo Analytics is compliant with the GDPR and many other data privacy regulations worldwide. Because it’s open source, it can be integrated with any consent manager.

  Get started today by trying Matomo for free for 21 days,
  no credit card required.

  Try Matomo for free

• CCPA vs GDPR : Understanding Their Impact on Data Analytics

  19 mars, par Alex Carmona

  With over 400 million internet users in Europe and 331 million in the US (11% of which reside in California alone), understanding the nuances of privacy laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) is crucial for compliant and ethical consumer data collection.

  Navigating this compliance landscape can be challenging for businesses serving European and Californian markets.

  This guide explores the key differences between CCPA and GDPR, their impact on data analytics, and how to ensure your business meets these essential privacy requirements.

  What is the California Consumer Privacy Act (CCPA) ?

  The California Consumer Privacy Act (CCPA) is a data privacy law that gives California consumers control over their personal information. It applies to for-profit businesses operating in California that meet specific criteria related to revenue, data collection and sales.

  Origins and purpose

  The CCPA addresses growing concerns about data privacy and how businesses use personal information in California. The act passed in 2018 and went into effect on 1 January 2020.

  Key features

  • Grants consumers the right to know what personal information is collected
  • Provides the right to delete personal information
  • Allows consumers to opt out of the sale of their personal information
  • Prohibits discrimination against consumers who exercise their CCPA rights

  Key definitions under the CCPA framework

  • Business : A for-profit entity doing business in California and meeting one or more of these conditions :
    • Has annual gross revenues over $25 million ;
    • Buys, receives, sells or shares 50,000 or more consumers’ personal information ; or
    • Derives 50% or more of its annual revenues from selling consumers’ personal information
  • Consumer : A natural person who is a California resident
  • Personal Information : Information that could be linked to, related to or used to identify a consumer or household, such as online identifiers, IP addresses, email addresses, social security numbers, cookie identifiers and more

  What is the General Data Protection Regulation (GDPR) ?

  The General Data Protection Regulation (GDPR) is a data privacy and protection law passed by the European Union (EU). It’s one of the strongest and most influential data privacy laws worldwide and applies to all organisations that process the personal data of individuals in the EU.

  Origins and purpose

  The GDPR was passed in 2016 and went into effect on 25 May 2018. It aims to harmonise data privacy laws in Europe and give people in the European Economic Area (EEA) privacy rights and control over their data.

  Key features

  • Applies to all organisations that process the personal data of individuals in the EEA
  • Grants individuals a wide range of privacy rights over their data
  • Requires organisations to obtain explicit and informed consent for most data processing
  • Mandates appropriate security measures to protect personal data
  • Imposes significant fines and penalties for non-compliance

  Key definitions under the GDPR framework

  • Data Subject : An identified or identifiable person
  • Personal Data : Any information relating to a data subject
  • Data Controller : The entity or organisation that determines how personal data is processed and what for
  • Data Processor : The entity or organisation that processes the data on behalf of the controller

  CCPA vs. GDPR : Key similarities

  The CCPA and GDPR enhance consumer privacy rights and give individuals greater control over their data.

  Dimension	CCPA	GDPR
  Purpose	Protect consumer privacy	Protect individual data rights
  Key Rights	Right to access, delete and opt out of sale	Right to access, rectify, erase and restrict processing
  Transparency	Requires transparency around data collection and use	Requires transparency about data collection, processing and use

  CCPA vs. GDPR : Key differences

  While they have similar purposes, the CCPA and GDPR differ significantly in their scope, approach and specific requirements.

  Dimension	CCPA	GDPR
  Scope	For-profit businesses only	All organisations processing EU consumer data
  Territorial Reach	California-based natural persons	All data subjects within the EEA
  Consent	Opt-out system	Opt-in system
  Penalties	Per violation based on its intentional or negligent nature	Case-by-case based on comprehensive assessment
  Individual Rights	Narrower (relative to GDPR)	Broader (relative to CCPA)

  CCPA vs. GDPR : A multi-dimensional comparison

  The previous sections gave a broad overview of the similarities and differences between CCPA and GDPR. Let’s now examine nine key dimensions where these regulations converge or diverge and discuss their impact on data analytics.

  

  #1. Scope and territorial reach

  The GDPR has a much broader scope than the CCPA. It applies to all organisations that process the personal data of individuals in the EEA, regardless of their business model, purpose or physical location.

  The CCPA applies to medium and large for-profit businesses that derive a substantial portion of their earnings from selling Californian consumers’ personal information. It doesn’t apply to non-profits, government agencies or smaller for-profit companies.

  Impact on data analytics

  The difference in scope significantly impacts data analytics practices. Smaller businesses may not need to comply with either regulation, some may only need to follow the CCPA, while most global businesses must comply with both. This often requires different methods for collecting and processing data in California, Europe, and elsewhere.

  #2. Penalties and fines for non-compliance

  Both the CCPA and GDPR impose penalties for non-compliance, but the severity of fines differs significantly :

  CCPA	Maximum penalty
  	$2,500 per unintentional violation $7,500 per intentional violation

  “Per violation” means per violation per impacted consumer. For example, three intentional CCPA violations affecting 1,000 consumers would result in 3,000 total violations and a $22.5 million maximum penalty (3,000 × $7,500).

  

  The largest CCPA fine to date was Zoom’s $85 million settlement in 2021.

  

  In contrast, the GDPR has resulted in 2,248 fines totalling almost €6.6 billion since 2018 — €2.4 billion of which were for non-compliance.

  GDPR	Maximum penalty
  	€20 million or 4% of all revenue earned the previous year

  So far, the biggest fine imposed under the GDPR was Meta’s €1.2 billion fine in May 2023 — 15 times more than Zoom had to pay California.

  Impact on data analytics

  The significant difference in potential fines demonstrates the importance of regulatory compliance for data analytics professionals. Non-compliance can have severe financial consequences, directly affecting budget allocation and business operations.

  Businesses must ensure their data collection, storage and processing practices comply with regulations in both Europe and California.

  Choosing privacy-first, compliance-ready analytics platforms like Matomo is instrumental for mitigating non-compliance risks.

  #3. Data subject rights and consumer rights

  The CCPA and GDPR give people similar rights over their data, but their limitations and details differ.

  Rights common to the CCPA and GDPR

  • Right to Access/Know : People can access their personal information and learn what data is collected, its source, its purpose and how it’s shared
  • Right to Delete/Erasure : People can request the deletion of their personal information, with some exceptions
  • Right to Non-Discrimination : Businesses can’t discriminate against people who exercise their privacy rights

  Consumer rights unique to the CCPA

  • Right to Opt Out of Sale : Consumers can prohibit the sale of their personal information
  • Right to Notice : Businesses must inform consumers about data collection practices
  • Right to Disclosure : Consumers can request specific information collected about them

  Data subject rights unique to the GDPR

  • Right to be Informed : Broader transparency requirements encompass data retention, automated decision-making and international transfers
  • Right to Rectification : Data subjects may request the correction of inaccurate data
  • Right to Restrict Processing : Consumers may limit data use in certain situations
  • Right to Data Portability : Businesses must provide individual consumer data in a secure, portable format when requested
  • Right to Withdraw Consent : Consumers may withdraw previously granted consent to data processing

  	CCPA	GDPR
  Right to Access or Know	✓	✓
  Right to Delete or Erase	✓	✓
  Right to Non-Discrimination	✓	✓
  Right to Opt-Out	✓
  Right to Notice	✓
  Right to Disclosure	✓
  Right to be Informed		✓
  Right to Rectification		✓
  Right to Restrict Processing		✓
  Right to Data Portability		✓
  Right to Withdraw Consent		✓

  Impact on data analytics

  Data analysts must understand these rights and ensure compliance with both regulations, which could potentially require separate data handling processes for EU and California consumers.

  #4. Opt-out vs. opt-in

  The CCPA generally follows an opt-out model, while the GDPR requires explicit consent from individuals before processing their data.

  Impact on data analytics

  For CCPA compliance, businesses can collect data by default if they provide opt-out mechanisms. Failing to process opt-out requests can result in severe penalties, like Sephora’s $1.2 million fine.

  Under GDPR, organisations must obtain explicit consent before collecting any data, which can limit the amount of data available for analysis.

  #5. Parental consent

  The CCPA and GDPR have provisions regarding parental consent for processing children’s data. The CCPA requires parental consent for children under 13, while the GDPR sets the age at 16, though member states can lower it to 13.

  Impact on data analytics

  This requirement significantly impacts businesses targeting younger audiences. In Europe and the US, companies must implement different methods to verify users’ ages and obtain parental consent when necessary.

  The California Attorney General’s Office recently fined Tilting Point Media LLC $500,000 for sharing children’s data without parental consent.

  #6. Data security requirements

  Both regulations require businesses to implement adequate security measures to protect personal data. However, the GDPR has more prescriptive requirements, outlining specific security measures and emphasising a risk-based approach.

  Impact on data analytics

  Data analytics professionals must ensure that data is processed and stored securely to avoid breaches and potential fines.

  #7. International data transfers

  Both the CCPA and GDPR address international data transfers. Under the CCPA, businesses must only inform consumers about international transfers. The GDPR has stricter requirements, including ensuring adequate data protection safeguards for transfers outside the EEA.

  

  Other rules, like the Payment Services Directive 2 (PSD2), also affect international data transfers, especially in the financial industry.

  PSD2 requires strong customer authentication and secure communication channels for payment services. This adds complexity to cross-border data flows.

  Impact on data analytics

  The primary impact is on businesses serving European residents from outside Europe. Processing data within the European Union is typically advisable. Meta’s record-breaking €1.2 billion fine was specifically for transferring data from the EEA to the US without sufficient safeguards.

  Choosing the right analytics platform helps avoid these issues.

  For example, Matomo offers a free, open-source, self-hosted analytics platform you can deploy anywhere. You can also choose a managed, GDPR-compliant cloud analytics solution with all data storage and processing servers within the EU (in Germany), ensuring your data never leaves the EEA.

  #8. Enforcement mechanisms

  The California Attorney General is responsible for enforcing CCPA requirements, while in Europe, the Data Protection Authority (DPA) in each EU member state enforces GDPR requirements.

  Impact on data analytics

  Data analytics professionals should be familiar with their respective enforcement bodies and their powers to support compliance efforts and minimise the risk of fines and penalties.

  #9. Legal basis for personal data processing

  The GDPR outlines six legal grounds for processing personal data :

  • Consent
  • Contract
  • Legal obligation
  • Vital interests
  • Public task
  • Legitimate interests

  The CCPA doesn’t explicitly define lawful bases but focuses on consumer rights and transparency in general.

  Impact on data analytics

  Businesses subject to the GDPR must identify and document a valid lawful basis for each processing activity.

  Compliance rules under CCPA and GDPR

  Complying with the CCPA and GDPR requires a comprehensive approach to data privacy. Here’s a summary of the essential compliance rules for each framework :

  

  CCPA compliance rules

  • Create clear and concise privacy policies outlining data collection and use practices
  • Give consumers the right to opt-out
  • Respond to consumer requests to access, delete and correct their personal information
  • Implement reasonable security measures for consumers’ personal data protection
  • Never discriminate against consumers who exercise their CCPA rights

  GDPR compliance rules

  • Obtain explicit and informed consent for data processing activities
  • Implement technical and organisational controls to safeguard personal data
  • Designate a Data Protection Officer (DPO) if necessary
  • Perform data protection impact assessments (DPIAs) for high-risk processing activities
  • Maintain records of processing activities
  • Promptly report data breaches to supervisory authorities

  Navigating the CCPA and GDPR with confidence

  Understanding the nuances of the CCPA and GDPR is crucial for businesses operating in the US and Europe. These regulations significantly impact data collection and analytics practices.

  Implementing robust data security practices and prioritising privacy and compliance are essential to avoid severe penalties and build trust with today’s privacy-conscious consumers.

  Privacy-centric analytics platforms like Matomo enable businesses to collect, analyse and use data responsibly and transparently, extracting valuable insights while maintaining compliance with both CCPA and GDPR requirements.

  Start your 21-day free trial today !

  no credit card required

• How to analyse 404 pages

  1er juillet 2019, par Matomo Core Team — Development, Plugins

  How to analyse “not found” pages (404) in digital analytics

  Have you ever sent out a newsletter and one link wasn’t active yet ? Would you like to know how many users get affected when this happens ? Would you like to know if your visitors are encountering 404 pages ? 

  In this article we’re describing an easy way to analyse “not found” pages on your website with Matomo to increase your visitors’ user experience, user acquisition, and SEO (search engine optimization).

  How to know the number of 404s on my website ?

  There are different ways to get this information. Depending on how your website is built, you may or may not collect this data.

  The easiest way to answer this question is to fire a 404 page on your website, you do this by accessing a wrong url :

  

  As you can see here, in our case, the page title starts with “Page non trouvée” which stands for “Page not found” when translated in English (as the website we are considering here is in French) :

  

  In this example 19 page views have been fired and it generated a bounce rate of 67%. As a result ⅔ of the visits ended here.

  In some cases, the information related to a “not found” page can be found either within the title or within the URL, as some websites redirect you to a specific web page when a page can’t be found.

  If you can’t identify “not found” pages via a page title or a page URL, we strongly advise you to use this specific tracking code method on your 404 page : “How to track error pages in Matomo ?”. 

  You can easily set it with Matomo Tag Manager with a custom HTML tag :

  

  where the trigger is the following :

  

  You will however, have to define this trigger as an exclusion for all the other tags which may conflict with it (here below is the new trigger defined for the generic Matomo tags we are inserting on all pages) :

  

  Once this specific tracking is set, you will be able to track the source of the 404 and will gather all the “not found” pages in a specific group within your Page Title report :

  

  Here, for example, you can identify that the homepage of this website had a link pointing to a 404, in our case it was https://www.webassoc.org/pro-du-web.

  Note that this is just one technique. You could also create a custom dimension report and decide to send the 404 there also.

  How to get notified when a 404 page is visited ?

  Trust us, you’re not going to check everyday whether a 404 page has been visited. In order to avoid checking it manually, you can define custom alerts.

  There are three possible scenarios when “not found” pages can be fired :

  • internal 404 : one link within your website is pointing to a wrong url on the same website.
  • external 404 : someone from an external website made a link to yours and the link is not correct.
  • direct access 404 : someone access directly to a not found page on your website.

  You can define all those three within Matomo, but in your case, you will only have to focus on the first two only. In fact, you can’t really fix the third scenario. That’s the reason why we’re not focusing on it. It would result in irrelevant alerts.

  Custom alert for internal 404

  An internal 404 is defined from a 404 where the source is an internal web page. As a result, it will look like the following in your report :

  

  In this example, we’re using this specific custom implementation, the title of the page will contain “From = https://www.webassoc.org/”. So set our custom alert accordingly :

  

  Now every time a 404 page will be fired from an internal page, you’ll be notified by email.

  Note that you can also decide to not receive any email and track the evolution of alerts with the History of triggered alerts feature.

  Custom alert for external 404

  External 404 is almost the same setup. The only thing you need to keep in mind is that we want to exclude the 404 where the source is not indicated. As a result, your configuration will look like the following :

  

  Here your regular expression pattern is the following one :

  404/URL = .*From = (?!https://www.webassoc.org)[^\s]+

  as you’ll want to have any referrer coming from a website which is not Matomo and not a direct 404.

   

  You can now be notified every time that a 404 is fired from any link.

  Note that this configuration may slightly differ from website to website. So always double check your tracking code and the way the values are sent to your reports. Also try to trigger those alerts first before validating them.

  How to follow the evolution of your 404 over time ?

  It may be interesting to know how good or how bad you are performing in terms of 404.

  In order to check this information, you can click on the evolution icon near the 404 title :

  

  But you may be interested in accessing this information more regularly without having to create this report each time.

  So, one way to analyse the evolution of your 404 is to create a segment such as :

  

  and to click after that on evolution icon :

  

  As you can see below the number of “not found” pages is quite low in general, but we can also notice that a period received an increase in terms of 404 not found pages on May 27. It may be interesting to investigate it :

  

  You can start from the overview of referrers :

  

  As you can notice here the main source of 404 is coming from direct entries which is the most difficult channel to analyse as we don’t really know where the visitors are coming from.

  How to perform your analysis even faster ?

  As you can see analysing reports in Matomo in order to detect 404 pages is a time-consuming activity. In order to make it faster, you can already create a report about it within the Email reports feature with the following settings :

  • Segment : 404
  • Email schedule : never.
  • Visits summary and Page titles as selected report.

  You will then end up with a saved report listing all the URLs concerned :

  

  You can also have a look at the “Custom reports” premium feature.

  It will provide you with more flexibility. You will then be able to focus on the most important thing : the cause of 404.

  Good luck and happy analytics !