Recherche avancée

Médias (0)

Mot : - Tags -/navigation

Aucun média correspondant à vos critères n’est disponible sur le site.

Autres articles (82)

  • 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 (...)

Sur d’autres sites (10781)

  • lavu/mem : move the DECLARE_ALIGNED macro family to mem_internal on next+1 bump

    27 mai 2020, par Anton Khirnov
    lavu/mem : move the DECLARE_ALIGNED macro family to mem_internal on next+1 bump
    

    They are not properly namespaced and not intended for public use.

    • [DH] libavcodec/4xm.c
    • [DH] libavcodec/aac.h
    • [DH] libavcodec/aacenc.h
    • [DH] libavcodec/aacps.h
    • [DH] libavcodec/aacps_fixed_tablegen.h
    • [DH] libavcodec/aacsbrdata.h
    • [DH] libavcodec/aactab.c
    • [DH] libavcodec/aactab.h
    • [DH] libavcodec/ac3dec.h
    • [DH] libavcodec/ac3dsp.c
    • [DH] libavcodec/ac3tab.c
    • [DH] libavcodec/agm.c
    • [DH] libavcodec/aic.c
    • [DH] libavcodec/arm/sbcdsp_init_arm.c
    • [DH] libavcodec/asv.h
    • [DH] libavcodec/atrac1.c
    • [DH] libavcodec/atrac3.c
    • [DH] libavcodec/atrac3plus.h
    • [DH] libavcodec/atrac3plusdec.c
    • [DH] libavcodec/atrac9dec.c
    • [DH] libavcodec/binkaudio.c
    • [DH] libavcodec/cabac.c
    • [DH] libavcodec/cavs.c
    • [DH] libavcodec/cavs.h
    • [DH] libavcodec/clearvideo.c
    • [DH] libavcodec/cook.c
    • [DH] libavcodec/dca_core.h
    • [DH] libavcodec/dca_lbr.h
    • [DH] libavcodec/dca_xll.h
    • [DH] libavcodec/dcadata.c
    • [DH] libavcodec/dirac_vlc.c
    • [DH] libavcodec/diracdec.c
    • [DH] libavcodec/dnxhddec.c
    • [DH] libavcodec/dnxhdenc.h
    • [DH] libavcodec/dolby_e.h
    • [DH] libavcodec/dss_sp.c
    • [DH] libavcodec/dstdec.c
    • [DH] libavcodec/eamad.c
    • [DH] libavcodec/eatgq.c
    • [DH] libavcodec/eatqi.c
    • [DH] libavcodec/fft.h
    • [DH] libavcodec/fic.c
    • [DH] libavcodec/g2meet.c
    • [DH] libavcodec/h264_mvpred.h
    • [DH] libavcodec/h264dec.h
    • [DH] libavcodec/hcadec.c
    • [DH] libavcodec/hevcdec.h
    • [DH] libavcodec/hevcdsp.h
    • [DH] libavcodec/hq_hqa.h
    • [DH] libavcodec/hqx.h
    • [DH] libavcodec/imm4.c
    • [DH] libavcodec/mdct15.h
    • [DH] libavcodec/mdec.c
    • [DH] libavcodec/mimic.c
    • [DH] libavcodec/mips/constants.c
    • [DH] libavcodec/mips/h264dsp_mmi.c
    • [DH] libavcodec/mips/simple_idct_mmi.c
    • [DH] libavcodec/mips/vc1dsp_mmi.c
    • [DH] libavcodec/mips/vp8dsp_mmi.c
    • [DH] libavcodec/mips/xvid_idct_mmi.c
    • [DH] libavcodec/mjpegdec.h
    • [DH] libavcodec/mlpdec.c
    • [DH] libavcodec/mpc.h
    • [DH] libavcodec/mpeg12dec.c
    • [DH] libavcodec/mpegaudiodec_template.c
    • [DH] libavcodec/mpegaudiodsp_template.c
    • [DH] libavcodec/nellymoserdec.c
    • [DH] libavcodec/on2avc.c
    • [DH] libavcodec/opus.h
    • [DH] libavcodec/opus_celt.h
    • [DH] libavcodec/opus_pvq.h
    • [DH] libavcodec/opusenc.c
    • [DH] libavcodec/opusenc_psy.h
    • [DH] libavcodec/opustab.c
    • [DH] libavcodec/ppc/h264chroma_template.c
    • [DH] libavcodec/ppc/h264dsp.c
    • [DH] libavcodec/ppc/h264qpel.c
    • [DH] libavcodec/ppc/mpegvideo_altivec.c
    • [DH] libavcodec/ppc/mpegvideodsp.c
    • [DH] libavcodec/ppc/vp8dsp_altivec.c
    • [DH] libavcodec/proresenc_kostya.c
    • [DH] libavcodec/qdm2.c
    • [DH] libavcodec/ra144.h
    • [DH] libavcodec/ra288.h
    • [DH] libavcodec/rtjpeg.h
    • [DH] libavcodec/rv34.h
    • [DH] libavcodec/sbc.h
    • [DH] libavcodec/sbcdec.c
    • [DH] libavcodec/sbcdsp.h
    • [DH] libavcodec/sbcdsp_data.c
    • [DH] libavcodec/sbr.h
    • [DH] libavcodec/sinewin.h
    • [DH] libavcodec/sipr.h
    • [DH] libavcodec/siren.c
    • [DH] libavcodec/svq1_cb.h
    • [DH] libavcodec/svq1enc.h
    • [DH] libavcodec/svq3.c
    • [DH] libavcodec/tableprint.h
    • [DH] libavcodec/takdec.c
    • [DH] libavcodec/truespeech.c
    • [DH] libavcodec/vorbis_data.c
    • [DH] libavcodec/vp3.c
    • [DH] libavcodec/vp56.h
    • [DH] libavcodec/vp8.h
    • [DH] libavcodec/vp9dec.h
    • [DH] libavcodec/vp9dsp.c
    • [DH] libavcodec/wma.h
    • [DH] libavcodec/wmalosslessdec.c
    • [DH] libavcodec/wmaprodec.c
    • [DH] libavcodec/wmavoice.c
    • [DH] libavcodec/wmv2.h
    • [DH] libavcodec/x86/constants.c
    • [DH] libavcodec/x86/fdct.c
    • [DH] libavcodec/x86/me_cmp_init.c
    • [DH] libavcodec/x86/mpegvideoenc.c
    • [DH] libavfilter/ebur128.c
    • [DH] libavfilter/vf_colorspace.c
    • [DH] libavfilter/vf_dctdnoiz.c
    • [DH] libavfilter/vf_fspp.c
    • [DH] libavfilter/vf_gradfun.c
    • [DH] libavfilter/vf_owdenoise.c
    • [DH] libavfilter/vf_pp7.c
    • [DH] libavfilter/vf_spp.c
    • [DH] libavfilter/vf_uspp.c
    • [DH] libavutil/aes_internal.h
    • [DH] libavutil/internal.h
    • [DH] libavutil/lls.h
    • [DH] libavutil/mem.h
    • [DH] libavutil/mem_internal.h
    • [DH] libavutil/tests/aes_ctr.c
    • [DH] libavutil/tests/des.c
    • [DH] libavutil/tx_priv.h
    • [DH] libavutil/version.h
    • [DH] libpostproc/postprocess_altivec_template.c
    • [DH] libpostproc/postprocess_internal.h
    • [
  • What is Behavioural Segmentation and Why is it Important ?

    28 septembre 2023, par Erin — Analytics Tips

    Amidst the dynamic landscape of web analytics, understanding customers has grown increasingly vital for businesses to thrive. While traditional demographic-focused strategies possess merit, they need to uncover the nuanced intricacies of individual online behaviours and preferences. As customer expectations evolve in the digital realm, enterprises must recalibrate their approaches to remain relevant and cultivate enduring digital relationships.

    In this context, the surge of technology and advanced data analysis ushers in a marketing revolution : behavioural segmentation. Businesses can unearth invaluable insights by meticulously scrutinising user actions, preferences and online interactions. These insights lay the foundation for precisely honed, high-performing, personalised campaigns. The era dominated by blanket, catch-all marketing strategies is yielding to an era of surgical precision and tailored engagement. 

    While the insights from user behaviours empower businesses to optimise customer experiences, it’s essential to strike a delicate balance between personalisation and respecting user privacy. Ethical use of behavioural data ensures that the power of segmentation is wielded responsibly and in compliance, safeguarding user trust while enabling businesses to thrive in the digital age.

    What is behavioural segmentation ?

    Behavioural segmentation is a crucial concept in web analytics and marketing. It involves categorising individuals or groups of users based on their online behaviour, actions and interactions with a website. This segmentation method focuses on understanding how users engage with a website, their preferences and their responses to various stimuli. Behavioural segmentation classifies users into distinct segments based on their online activities, such as the pages they visit, the products they view, the actions they take and the time they spend on a site.

    Behavioural segmentation plays a pivotal role in web analytics for several reasons :

    1. Enhanced personalisation :

    Understanding user behaviour enables businesses to personalise online experiences. This aids with delivering tailored content and recommendations to boost conversion, customer loyalty and customer satisfaction.

    2. Improved user experience :

    Behavioural segmentation optimises user interfaces (UI) and navigation by identifying user paths and pain points, enhancing the level of engagement and retention.

    3. Targeted marketing :

    Behavioural segmentation enhances marketing efficiency by tailoring campaigns to user behaviour. This increases the likelihood of interest in specific products or services.

    4. Conversion rate optimisation :

    Analysing behavioural data reveals factors influencing user decisions, enabling website optimisation for a streamlined purchasing process and higher conversion rates.

    5. Data-driven decision-making :

    Behavioural segmentation empowers data-driven decisions. It identifies trends, behavioural patterns and emerging opportunities, facilitating adaptation to changing user preferences and market dynamics.

    6. Ethical considerations :

    Behavioural segmentation provides valuable insights but raises ethical concerns. User data collection and use must prioritise transparency, privacy and responsible handling to protect individuals’ rights.

    The significance of ethical behavioural segmentation will be explored more deeply in a later section, where we will delve into the ethical considerations and best practices for collecting, storing and utilising behavioural data in web analytics. It’s essential to strike a balance between harnessing the power of behavioural segmentation for business benefits and safeguarding user privacy and data rights in the digital age.

    A woman surrounded by doors shaped like heads of different

    Different types of behavioural segments with examples

    1. Visit-based segments : These segments hinge on users’ visit patterns. Analyse visit patterns, compare first-time visitors to returning ones, or compare users landing on specific pages to those landing on others.
      • Example : The real estate website Zillow can analyse how first-time visitors and returning users behave differently. By understanding these patterns, Zillow can customise its website for each group. For example, they can highlight featured listings and provide navigation tips for first-time visitors while offering personalised recommendations and saved search options for returning users. This could enhance user satisfaction and boost the chances of conversion.
    2. Interaction-based segments : Segments can be created based on user interactions like special events or goals completed on the site.
      • Example : Airbnb might use this to understand if users who successfully book accommodations exhibit different behaviours than those who don’t. This insight could guide refinements in the booking process for improved conversion rates.
    3. Campaign-based segments : Beyond tracking visit numbers, delve into usage differences of visitors from specific sources or ad campaigns for deeper insights.
      • Example : Nike might analyse user purchase behaviour from various traffic sources (referral websites, organic, direct, social media and ads). This informs marketing segmentation adjustments, focusing on high-performance channels. It also customises the website experience for different traffic sources, optimising content, promotions and navigation. This data-driven approach could boost user experiences and maximise marketing impact for improved brand engagement and sales conversions.
    4. Ecommerce segments : Separate users based on purchases, even examining the frequency of visits linked to specific products. Segment heavy users versus light users. This helps uncover diverse customer types and browsing behaviours.
      • Example : Amazon could create segments to differentiate between visitors who made purchases and those who didn’t. This segmentation could reveal distinct usage patterns and preferences, aiding Amazon in tailoring its recommendations and product offerings.
    5. Demographic segments : Build segments based on browser language or geographic location, for instance, to comprehend how user attributes influence site interactions.
      • Example : Netflix can create user segments based on demographic factors like geographic location to gain insight into how a visitor’s location can influence content preferences and viewing behaviour. This approach could allow for a more personalised experience.
    6. Technographic segments : Segment users by devices or browsers, revealing variations in site experience and potential platform-specific issues or user attitudes.
      • Example : Google could create segments based on users’ devices (e.g., mobile, desktop) to identify potential issues in rendering its search results. This information could be used to guide Google in providing consistent experiences regardless of device.
    A group of consumers split into different segments based on their behaviour

    The importance of ethical behavioural segmentation

    Respecting user privacy and data protection is crucial. Matomo offers features that align with ethical segmentation practices. These include :

    • Anonymization : Matomo allows for data anonymization, safeguarding individual identities while providing valuable insights.
    • GDPR compliance : Matomo is GDPR compliant, ensuring that user data is handled following European data protection regulations.
    • Data retention and deletion : Matomo enables businesses to set data retention policies and delete user data when it’s no longer needed, reducing the risk of data misuse.
    • Secured data handling : Matomo employs robust security measures to protect user data, reducing the risk of data breaches.

    Real-world examples of ethical behavioural segmentation :

    1. Content publishing : A leading news website could utilise data anonymization tools to ethically monitor user engagement. This approach allows them to optimise content delivery based on reader preferences while ensuring the anonymity and privacy of their target audience.
    2. Non-profit organisations : A charity organisation could embrace granular user control features. This could be used to empower its donors to manage their data preferences, building trust and loyalty among supporters by giving them control over their personal information.
    Person in a suit holding a red funnel that has data flowing through it into a file

    Examples of effective behavioural segmentation

    Companies are constantly using behavioural insights to engage their audiences effectively. In this section, we’ll delve into real-world examples showcasing how top companies use behavioural segmentation to enhance their marketing efforts.

    A woman standing in front of a pie chart pointing to the top right-hand section of customers in that segment
    1. Coca-Cola’s behavioural insights for marketing strategy : Coca-Cola employs behavioural segmentation to evaluate its advertising campaigns. Through analysing user engagement across TV commercials, social media promotions and influencer partnerships, Coca-Cola’s marketing team can discover that video ads shared by influencers generate the highest ROI and web traffic.

      This insight guides the reallocation of resources, leading to increased sales and a more effective advertising strategy.

    2. eBay’s custom conversion approach : eBay excels in conversion optimisation through behavioural segmentation. When users abandon carts, eBay’s dynamic system sends personalised email reminders featuring abandoned items and related recommendations tailored to user interests and past purchase decisions.

      This strategy revives sales, elevates conversion rates and sparks engagement. eBay’s adeptness in leveraging behavioural insights transforms user experience, steering a customer journey toward conversion.

    3. Sephora’s data-driven conversion enhancement : Data analysts can use Sephora’s behavioural segmentation strategy to fuel revenue growth through meticulous data analysis. By identifying a dedicated subset of loyal customers who exhibit a consistent preference for premium skincare products, data analysts enable Sephora to customise loyalty programs.

      These personalised rewards programs provide exclusive discounts and early access to luxury skincare releases, resulting in heightened customer engagement and loyalty. The data-driven precision of this approach directly contributes to amplified revenue from this specific customer segment.

    Examples of the do’s and don’ts of behavioural segmentation 

    Happy woman surrounded by icons of things and activities she enjoys

    Behavioural segmentation is a powerful marketing and data analysis tool, but its success hinges on ethical and responsible practices. In this section, we will explore real-world examples of the do’s and don’ts of behavioural segmentation, highlighting companies that have excelled in their approach and those that have faced challenges due to lapses in ethical considerations.

    Do’s of behavioural segmentation :

    • Personalised messaging :
      • Example : Spotify
        • Spotify’s success lies in its ability to use behavioural data to curate personalised playlists and user recommendations, enhancing its music streaming experience.
    • Transparency :
      • Example : Basecamp
        • Basecamp’s transparency in sharing how user data is used fosters trust. They openly communicate data practices, ensuring users are informed and comfortable.
    • Anonymization
      • Example : Matomo’s anonymization features
        • Matomo employs anonymization features to protect user identities while providing valuable insights, setting a standard for responsible data handling.
    • Purpose limitation :
      • Example : Proton Mail
        • Proton Mail strictly limits the use of user data to email-related purposes, showcasing the importance of purpose-driven data practices.
    • Dynamic content delivery : 
      • Example : LinkedIn
        • LinkedIn uses behavioural segmentation to dynamically deliver job recommendations, showcasing the potential for relevant content delivery.
    • Data security :
      • Example : Apple
        • Apple’s stringent data security measures protect user information, setting a high bar for safeguarding sensitive data.
    • Adherence to regulatory compliance : 
      • Example : Matomo’s regulatory compliance features
        • Matomo’s regulatory compliance features ensure that businesses using the platform adhere to data protection regulations, further promoting responsible data usage.

    Don’ts of behavioural segmentation :

    • Ignoring changing regulations
      • Example : Equifax
        • Equifax faced major repercussions for neglecting evolving regulations, resulting in a data breach that exposed the sensitive information of millions.
    • Sensitive attributes
      • Example : Twitter
        • Twitter faced criticism for allowing advertisers to target users based on sensitive attributes, sparking concerns about user privacy and data ethics.
    • Data sharing without consent
      • Example : Meta & Cambridge Analytica
        • The Cambridge Analytica scandal involving Meta (formerly Facebook) revealed the consequences of sharing user data without clear consent, leading to a breach of trust.
    • Lack of control
      • Example : Uber
        • Uber faced backlash for its poor data security practices and a lack of control over user data, resulting in a data breach and compromised user information.
    • Don’t be creepy with invasive personalisation
      • Example : Offer Moment
        • Offer Moment’s overly invasive personalisation tactics crossed ethical boundaries, unsettling users and eroding trust.

    These examples are valuable lessons, emphasising the importance of ethical and responsible behavioural segmentation practices to maintain user trust and regulatory compliance in an increasingly data-driven world.

    Continue the conversation

    Diving into customer behaviours, preferences and interactions empowers businesses to forge meaningful connections with their target audience through targeted marketing segmentation strategies. This approach drives growth and fosters exceptional customer experiences, as evident from the various common examples spanning diverse industries.

    In the realm of ethical behavioural segmentation and regulatory compliance, Matomo is a trusted partner. Committed to safeguarding user privacy and data integrity, our advanced web analytics solution empowers your business to harness the power of behavioral segmentation, all while upholding the highest standards of compliance with stringent privacy regulations.

    To gain deeper insight into your visitors and execute impactful marketing campaigns, explore how Matomo can elevate your efforts. Try Matomo free for 21-days, no credit card required. 

  • Blog series part 2 : How to increase engagement of your website visitors, and turn them into customers

    8 septembre 2020, par Joselyn Khor — Analytics Tips, Marketing

    Long gone are the days of simply tracking page views as a measure of engagement. Now it’s about engagement analysis, which is layered and provides insight for effective data-driven decisions.

    Discover how engaged people are with your website by uncovering behavioural patterns that tell you how well your site and content is or isn’t performing. This insight helps you re-evaluate, adapt and optimise your content and strategy. The more engaged they are, the more likely you’ll be able to guide them on a predetermined journey that results in more conversions ; and helps you reach the goals you’ve set for your business. 

    Why is visitor engagement important ?

    It’s vital to measure engagement if you have anything content related that plays a role in your customer’s journey. Some websites may find more value in figuring out how engaging their entire site is, while others may only want to zone in on, say, a blogging section, e-newsletters, social media channels or sign-up pages.

    In the larger scheme of things, engagement can be seen as what’s running your site. Every aspect of the buyer’s journey requires your visitors to be engaged. Whether you’re trying to attract, convert or build a loyal audience base, you need to know your content is optimised to maintain their attention and encourage them along the path to purchase, conversion or loyalty.

    How to increase engagement with Matomo

    You need to know what’s going right or wrong to eventually be able to deliver more riveting content your visitors can’t help but be drawn to. Learn how to apply Matomo’s easy-to-use features to increase engagement :

    1. The Behaviour feature
    2. Heatmaps
    3. A/B Testing
    4. Media Analytics
    5. Transitions
    6. Custom reports
    7. Other metrics to keep an eye on

    1. Look at the Behaviour feature

    It allows you to learn how visitors are responding to your content. This information is gathered by drawing insight from features such as site search, downloads, events and content interactions. Learn more

    Matomo's behaviour feature

    Matomo’s top five ways to increase engagement with the Behaviour feature :

    Behaviour -> Pages
    Get complete insights on what pages your users engage with, what pages provide little value to your business and see the results of entry and exit pages. If important content is generating low traffic, you need to place it where it can be seen. Spend time where it matters and focus on the content that will engage with your users and see how it eventually converts them into customers.

    Behaviour -> Site search
    Site search tracks how people use your website’s internal search engine. You can see :

    • What search keywords visitors used on your website’s internal search.
    • Which of those keywords resulted in no results (what content your visitors are looking for but cannot find).
    • What pages visitors visited immediately after a search.
    • What search categories visitors use (if your website employs search categories).

    Behaviour -> Downloads
    What are users wanting to take away with them ? They could be downloading .pdfs, .zip files, ebooks, infographics or other free/paid resources. For example, if you were working for an education institution and created valuable information packs for students that you made available online in .pdf format. To see an increase in downloads meant students were finding the .pdfs and realising the need to download them. No downloads could mean the information packs weren’t being found which would be problematic.

    Behaviour -> Events
    Tracking events is a very useful way to measure the interactions your users have with your website content, which are not directly page views or downloads.

    How have Events been used effectively ? A great example comes from one of our customers, Catalyst. They wanted to capture and measure the user interaction of accordions (an area of content that expands or closes depending on how a user interacts with it) to see if people were actually getting all the information available to them on this one page. By creating an Event to record which accordion had been opened, as well as creating events for other user interactions, they were able to figure out which content got the most engagement and which got the least. Being able to see how visitors navigated through their website helped them optimise the site to ensure people were getting the relevant information they were craving.

    Behaviour -> Content interactions
    Content tracking allows you to track interaction within the content of your web page. Go beyond page views, bounce rates and average time spent on page with your content. Instead, you can analyse content interaction rates based on mouse clicking and configuring scrolling or hovering behaviours to see precisely how engaged your users are. If interaction rates are low, perhaps you need to restructure your page layout to grab your user’s attention sooner. Possibly you will get more interaction when you have more images or banner ads to other areas of your business.

    Watch this video to learn about the Behaviour feature

    2. Set up Heatmaps

    Effortlessly discover how your visitors truly engage with your most important web pages that impact the success of your business. Heatmaps shows you visually where your visitors try to click, move the mouse and how far down they scroll on each page.

    Matomo's heatmaps feature

    You don’t need to waste time digging for key metrics or worry about putting together tables of data to understand how your visitors are interacting with your website. Heatmaps make it easy and fast to discover where your users are paying their attention, where they have problems, where useless content is and how engaging your content is. Get insights that you cannot get from traditional reports. Learn more

    3. Carry out A/B testing

    With A/B Testing you reduce risk in your decision-making and can test what your visitors are responding well to. 

    Matomo's a/b testing feature

    Ever had discussions with colleagues about where to place content on a landing page ? Or discussed what the call-to-action should be and assumed you were making the best decisions ? The truth is, you never know what really works the best (and what doesn’t) unless you test it. Learn more

    How to increase engagement with A/B Testing : Test, test and test. This is a surefire way to learn what content is leading your visitors on a path to conversion and what isn’t.

    4. Media Analytics

    Tells you how visitors are engaging with your video or audio content, and whether they’re leading to your desired conversions. Track :

    • How many plays your media gets and which parts they viewed
    • Finish rates
    • How your media was consumed over time
    • How media was consumed on specific days
    • Which locations your users were viewing your content from
    • Learn more
    Media Analytics

    How to increase engagement with Media Analytics : These metrics give a picture of how audiences are behaving when it comes to your content. By showing insights such as, how popular your media content is, how engaging it is and which days content will be most viewed, you can tailor content strategies to produce content people will actually find interesting and watch/listen.

    Matomo example : When we went through the feature video metrics on our own site to see how our videos were performing, we noticed our Acquisition video had a 95% completion rate. Even though it was longer than most videos, the stats showed us it had, by far, the most engagement. By using Media Analytics to get insights on the best and worst performing videos, we gathered useful info to help us better allocate resources effectively so that in the future, we’re producing more videos that will be watched.

    5. Investigate transitions

    See which page visitors are entering the site from and where they exit to. Transitions shows engagement on each page and whether the content is leading them to the pages you want them to be directed to.

    Transitions

    This gives you a greater understanding of user pathways. You may be assuming visitors are finding your content from one particular pathway, but figure out users are actually coming through other channels you never thought of. Through Transitions, you may discover and capitalise on new opportunities from external sites.

    How to increase engagement with Transitions : Identify clearly where users may be getting distracted to click away and where other pages are creating opportunity to click-through to conversion. 

    6. Create Custom Reports

    You can choose from over 200 dimensions and metrics to get the insights you need as well as various visualisation options. This makes understanding the data incredibly easy and you can get the insights you need instantly for faster results without the need for a developer. Learn more

    Custom Reports

    How to increase engagement with Custom Reports : Set custom reports to see when content is being viewed and figure out how engaged users are by looking at different hours of the day or which days of the week they’re visiting your website. For example, you could be wondering what hour of the day performed best for converting your customers. Understanding these metrics helps you figure out the best time to schedule your blog posts, pay-per-click advertising, edms or social media posts knowing that your visitors are more likely to convert at different times.

    7. Other metrics to key an eye on …

    A good indication of a great experience and of engagement is whether your readers, viewers or listeners want to do it again and again.

    “Best” metrics are hard to determine so you’ll need to ask yourself what you want to do or what you want your site to do. How do you want your users to behave or what kind of buyer’s journey do you want them to have ?

    Want to know where to start ? Look at …

    • Bounce rate – a high bounce rate isn’t great as people aren’t finding what they’re looking for and are leaving without taking action. (This offers great opportunities as you can test to see why people are bouncing off your site and figure out what you need to change.)
    • Time on site – a long time on site is usually a good indication that people are spending time reading, navigating and being engaged with your website. 
    • Frequency of visit – how often do people come back to interact with the content on your website ? The higher the % of your visitors that come back time and time again will show how engaged they are with your content.
    • Session length/average session duration – how much time users spend on site each session
    • Pages per session – is great to show engagement because it shows visitors are happy going through your website and learn more about your business.

    Key takeaway

    Whichever stage of the buyer’s journey your visitors are in, you need to ensure your content is optimised for engagement so that visitors can easily spend time on your website.

    “Every single visit by every single visitor is no longer judged as a success or a failure at the end of 29 min (max) session in your analytics tool. Every visit is not a ‘last-visit’, rather it becomes a continuous experience leading to a win-win outcome.” – Avinash Kaushik

    As you can tell, one size does not fit all when it comes to analysing and measuring engagement, but with a toolkit of features, you can make sure you have everything you need to experiment and figure out the metrics that matter to the success of your business and website.

    Concurrently, these gentle nudges for visitors to consume more and more content encourages them along their path to purchase, conversion or loyalty. They get a more engaging website experience over time and you get happy visitors/customers who end up coming back for more.

    Want to learn how to increase conversions with Matomo ? Look out for the final in this series : part 3 ! We’ll go through how you can boost conversions and meet your business goals with web analytics.