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• 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.

  

  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.

  

  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.

  

  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.

  

  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 

  

  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. 

• The screen recorder utility has failed to store the actual screen recording iOS

  31 mai 2023, par manoj

  I am getting the below issue when I run my code to record the screen on failure.

  


  An unknown server-side error occurred while processing the command. Original error : The screen recorder utility has failed to store the actual screen recording at '/var/folders/js/h2_7h9bj1fj8cn19tqcm8hnw0000gn/T/202341-30610-87cfav.bsg2u/appium_3f7703.mp4'

  


  Note : This issue is occurring during the tearDown.

  


  the code is showing stop recording is failing and this issue is occurring for only one test class

  


  public static File screenRecording(String prefix) throws IOException {
        File classpathRoot = new File(System.getProperty("user.dir"));
        String screenRec = ((CanRecordScreen) driver).stopRecordingScreen();
        byte[] screenRecord = Base64.decodeBase64(screenRec);
        String destinationPath = classpathRoot.getAbsolutePath() + "/screenRecordings/" + driver.getPlatformName()
                + " Video " + prefix + " " + new Date() + ".mp4";
        Path filePath = Paths.get(destinationPath);
        Files.write(filePath, screenRecord);
        File recordedFile = FileUtils.getFile(String.valueOf(filePath));
        return recordedFile;
    }


  


  The same thing when I run it successfully is passing in other test

  


  This is the thread that I was reffering

  


  Appium stack

  


  [ INFO ] 2023-05-26 13:38:51.636 [TestHelpers.PropertiesHelper.getRestartDeviceProperty(PropertiesHelper.java:181)] - Loading the 'RestartDevice' Property from the 'appiumTests.properties' file
[ INFO ] 2023-05-26 13:38:51.641 [TestFixtures.BaseTestFixture.globalSetup(BaseTestFixture.java:81)] - Building Appium Server...
[ INFO ] 2023-05-26 13:38:51.733 [TestFixtures.BaseTestFixture.globalSetup(BaseTestFixture.java:88)] - Appium server is built.
[ INFO ] 2023-05-26 13:38:51.733 [TestFixtures.BaseTestFixture.globalSetup(BaseTestFixture.java:89)] - Starting appium server...
[Appium] Welcome to Appium v1.22.2
[Appium] Non-default server args:
[Appium]   port: 3022
[Appium]   logFile: /Users/subh/IdeaProjects/tile_mobile_automation/logs/appium.log
[Appium]   loglevel: info
[Appium]   relaxedSecurityEnabled: true
[Appium] Appium REST http interface listener started on 0.0.0.0:3022
[HTTP] --> GET /wd/hub/status
[HTTP] {}
[HTTP] <-- GET /wd/hub/status 200 5 ms - 68
[HTTP] 
[ INFO ] 2023-05-26 13:38:53.069 [TestFixtures.BaseTestFixture.globalSetup(BaseTestFixture.java:91)] - Appium server started.

[ffmpeg] Output #0, mp4, to '/var/folders/js/h2_7h9bj1fj8cn19tqcm8hnw0000gn/T/2023426-9341-y22m7g.0jfd/appium_eca508.mp4':
[ffmpeg]   Metadata:
[ffmpeg]     encoder         : Lavf59.27.100
[ffmpeg]   Stream #0:0: Video: h264 (avc1 / 0x31637661), yuvj420p(pc, bt470bg/unknown/unknown, progressive), 720x1280 [SAR 520:633 DAR 195:422], q=2-31, 25 fps, 12800 tbn
[ffmpeg]     Metadata:
[ffmpeg]       encoder         : Lavc59.37.100 libx264
[ffmpeg] 
[ffmpeg]     Side data:
[ffmpeg]       cpb: bitrate max/min/avg: 0/0/0 buffer size: 0 vbv_delay: N/A
[ffmpeg] 
[XCUITest] Starting screen capture on the device 'xxxxxxxx-xxxxxxxxxxxxxxxx' with command: 'ffmpeg -f mjpeg -i http://127.0.0.1:9100 -vf scale=720:1280 -vcodec h264 -y /var/folders/js/h2_7h9bj1fj8cn19tqcm8hnw0000gn/T/2023426-9341-y22m7g.0jfd/appium_eca508.mp4'. Will timeout in 1800000ms
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/appium/start_recording_screen 200 621 ms - 12
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/appium/device/terminate_app
[HTTP] {"bundleId":"com.apple.Preferences"}
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/appium/device/terminate_app 200 6 ms - 15
[HTTP] 
[ INFO ] 2023-05-26 13:39:15.082 [TestFixtures.BaseTestFixture.setUp(BaseTestFixture.java:200)] - App Version is 2.115.0(7936)
<-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element 200 208 ms - 137
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/CC010000-0000-0000-1709-000000000000/click
[HTTP] {"id":"CC010000-0000-0000-1709-000000000000"}
[W3C (9a4d93a9)] Driver proxy active, passing request on via HTTP proxy
[WD Proxy] Replacing sessionId 643ECEF8-D0E3-47D0-AE3D-3FC884C69235 with 9a4d93a9-b723-4e2e-abad-db859e5efeed
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/CC010000-0000-0000-1709-000000000000/click 200 805 ms - 65
[HTTP] 
[HTTP] --> GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/context
[HTTP] {}
[HTTP] <-- GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/context 200 1 ms - 22
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element
[HTTP] {"using":"id","value":"OK"}
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element 200 309 ms - 137
[HTTP] 
[HTTP] --> GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/39020000-0000-0000-1709-000000000000/displayed
[HTTP] {}
[W3C (9a4d93a9)] Driver proxy active, passing request on via HTTP proxy
[WD Proxy] Replacing sessionId 643ECEF8-D0E3-47D0-AE3D-3FC884C69235 with 9a4d93a9-b723-4e2e-abad-db859e5efeed
[HTTP] <-- GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/39020000-0000-0000-1709-000000000000/displayed 200 134 ms - 65
[HTTP] 
[HTTP] --> GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/context
[HTTP] {}
[HTTP] <-- GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/context 200 1 ms - 22
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element
[HTTP] {"using":"id","value":"OK"}
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element 200 253 ms - 137
[HTTP] 
[HTTP] --> GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/39020000-0000-0000-1709-000000000000/text
[HTTP] {}
[W3C (9a4d93a9)] Driver proxy active, passing request on via HTTP proxy
[WD Proxy] Replacing sessionId 643ECEF8-D0E3-47D0-AE3D-3FC884C69235 with 9a4d93a9-b723-4e2e-abad-db859e5efeed
[HTTP] <-- GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/39020000-0000-0000-1709-000000000000/text 200 117 ms - 65
[HTTP] 
[HTTP] --> GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/context
[HTTP] {}
[HTTP] <-- GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/context 200 1 ms - 22
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element
[HTTP] {"using":"id","value":"OK"}
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element 200 247 ms - 137
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/39020000-0000-0000-1709-000000000000/click
[HTTP] {"id":"39020000-0000-0000-1709-000000000000"}
[W3C (9a4d93a9)] Driver proxy active, passing request on via HTTP proxy
[WD Proxy] Replacing sessionId 643ECEF8-D0E3-47D0-AE3D-3FC884C69235 with 9a4d93a9-b723-4e2e-abad-db859e5efeed
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/39020000-0000-0000-1709-000000000000/click 200 778 ms - 65
[HTTP] 
[HTTP] --> GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/context
[HTTP] {}
[HTTP] <-- GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/context 200 1 ms - 22
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element
[HTTP] {"using":"id","value":"btn_add_tile"}
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element 200 285 ms - 137
[HTTP] 
[HTTP] --> GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/06010000-0000-0000-1709-000000000000/displayed
[HTTP] {}
[W3C (9a4d93a9)] Driver proxy active, passing request on via HTTP proxy
[WD Proxy] Replacing sessionId 643ECEF8-D0E3-47D0-AE3D-3FC884C69235 with 9a4d93a9-b723-4e2e-abad-db859e5efeed
[HTTP] <-- GET /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/element/06010000-0000-0000-1709-000000000000/displayed 200 133 ms - 65
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/appium/app/reset
[HTTP] {}
[DevCon Factory] Releasing connections for xxxxxxxx-xxxxxxxxxxxxxxxx device on 9100 port number
[DevCon Factory] No cached connections have been found
[DevCon Factory] Releasing connections for xxxxxxxx-xxxxxxxxxxxxxxxx device on any port number
[DevCon Factory] Found cached connections to release: ["00008110-0004150236E8401E:8100"]
[DevCon Factory] Releasing the listener for 'xxxxxxxx-xxxxxxxxxxxxxxxx:8100'
[BaseDriver] The following capabilities are not standard capabilities and should have an extension prefix:
[BaseDriver]   appPushTimeout
[BaseDriver]   app
[BaseDriver]   automationName
[BaseDriver]   deviceName
[BaseDriver]   fullReset
[BaseDriver]   newCommandTimeout
[BaseDriver]   noReset
[BaseDriver]   platformVersion
[BaseDriver]   processArguments
[BaseDriver]   showXcodeLog
[BaseDriver]   udid
[BaseDriver]   xcodeOrgId
[BaseDriver]   xcodeSigningId
[BaseDriver] Session created with session id: 7950b9ef-eac2-4169-a035-2d183deacf68
[XCUITest] Determining device to run tests on: udid: 'xxxxxxxx-xxxxxxxxxxxxxxxx', real device: true
[XCUITest] Normalized platformVersion capability value '16.4.1' to '16.4'
[BaseDriver] Using local app '/Users/subh/IdeaProjects/tile_mobile_automation/apps/tile_appstore_adhoc.ipa'
[BaseDriver] Will reuse previously cached application at '/var/folders/js/h2_7h9bj1fj8cn19tqcm8hnw0000gn/T/2023426-9341-af6qqi.jfr2v/tile.app'
[WebDriverAgent] Using WDA path: '/usr/local/lib/node_modules/appium/node_modules/appium-webdriveragent'
[WebDriverAgent] Using WDA agent: '/usr/local/lib/node_modules/appium/node_modules/appium-webdriveragent/WebDriverAgent.xcodeproj'
[XCUITest] Setting up real device
[XCUITest] App installation succeeded after 14402ms
[DevCon Factory] Requesting connection for device xxxxxxxx-xxxxxxxxxxxxxxxx on local port 8100, device port 8100
[DevCon Factory] Successfully requested the connection for xxxxxxxx-xxxxxxxxxxxxxxxx:8100
[WebDriverAgent] Will reuse previously cached WDA instance at 'http://127.0.0.1:8100/' with 'com.facebook.WebDriverAgentRunner'. Set the wdaLocalPort capability to a value different from 8100 if this is an undesired behavior.
[WebDriverAgent] Using provided WebdriverAgent at 'http://127.0.0.1:8100/'
[WD Proxy] Determined the downstream protocol as 'W3C'
[XCUITest] Skipping setting of the initial display orientation. Set the "orientation" capability to either "LANDSCAPE" or "PORTRAIT", if this is an undesired behavior.
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/appium/app/reset 200 18735 ms - 14
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/appium/device/terminate_app
[HTTP] {"bundleId":"com.apple.Preferences"}
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/appium/device/terminate_app 200 1046 ms - 14
INFO: Loading the 'SaveVideoOnSuccess' Property from the 'appiumTests.properties' file
[HTTP] 
[HTTP] --> POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/appium/stop_recording_screen
[HTTP] {}
[DevCon Factory] Releasing connections for xxxxxxxx-xxxxxxxxxxxxxxxx device on 9100 port number
[DevCon Factory] No cached connections have been found
[XCUITest] The screen recorder utility has failed to store the actual screen recording at '/var/folders/js/h2_7h9bj1fj8cn19tqcm8hnw0000gn/T/2023426-9341-y22m7g.0jfd/appium_eca508.mp4'
[DevCon Factory] Releasing connections for xxxxxxxx-xxxxxxxxxxxxxxxx device on 9100 port number
[DevCon Factory] No cached connections have been found
[HTTP] <-- POST /wd/hub/session/9a4d93a9-b723-4e2e-abad-db859e5efeed/appium/stop_recording_screen 500 14 ms - 841
[HTTP] 

org.openqa.selenium.WebDriverException: An unknown server-side error occurred while processing the command. Original error: The screen recorder utility has failed to store the actual screen recording at '/var/folders/js/h2_7h9bj1fj8cn19tqcm8hnw0000gn/T/2023426-9341-y22m7g.0jfd/appium_eca508.mp4'
Build info: version: '3.141.59', revision: 'e82be7d358', time: '2018-11-14T08:17:03'
System info: host: 'localhost', ip: 'fe80:0:0:0:8c8:c2c0:abb2:3b1a%en0', os.name: 'Mac OS X', os.arch: 'x86_64', os.version: '11.2', java.version: '11.0.11'
Driver info: io.appium.java_client.ios.IOSDriver
Capabilities {app: /Users/subh/IdeaProjects/ti..., appPushTimeout: 50000, automationName: XCUITest, browserName: , databaseEnabled: false, deviceName: Tile DEV QA?s iPhone, fullReset: true, javascriptEnabled: true, locationContextEnabled: false, networkConnectionEnabled: false, newCommandTimeout: 30, noReset: false, platform: MAC, platformName: ios, platformVersion: 16.4.1, processArguments: {arguments: -com.apple.CoreData.Concurr...}, showXcodeLog: true, takesScreenshot: true, udid: xxxxxxxx-xxxxxxxxxxxxxxxx, webStorageEnabled: false, xcodeOrgId: XK64B7G5HB, xcodeSigningId: iPhone Developer}
Session ID: 9a4d93a9-b723-4e2e-abad-db859e5efeed

  at java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
  at java.base/jdk.internal.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
  at java.base/jdk.internal.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
  at java.base/java.lang.reflect.Constructor.newInstance(Constructor.java:490)
  at org.openqa.selenium.remote.http.W3CHttpResponseCodec.createException(W3CHttpResponseCodec.java:187)
  at org.openqa.selenium.remote.http.W3CHttpResponseCodec.decode(W3CHttpResponseCodec.java:122)
  at org.openqa.selenium.remote.http.W3CHttpResponseCodec.decode(W3CHttpResponseCodec.java:49)
  at org.openqa.selenium.remote.HttpCommandExecutor.execute(HttpCommandExecutor.java:158)
  at io.appium.java_client.remote.AppiumCommandExecutor.execute(AppiumCommandExecutor.java:250)
  at org.openqa.selenium.remote.RemoteWebDriver.execute(RemoteWebDriver.java:552)
  at io.appium.java_client.DefaultGenericMobileDriver.execute(DefaultGenericMobileDriver.java:45)
  at io.appium.java_client.AppiumDriver.execute(AppiumDriver.java:1)
  at io.appium.java_client.ios.IOSDriver.execute(IOSDriver.java:1)
  at io.appium.java_client.screenrecording.CanRecordScreen.stopRecordingScreen(CanRecordScreen.java:72)
  at TestFixtures.BaseTestFixture.tearDown(BaseTestFixture.java:253)
  at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
  at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
  at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
  at java.base/java.lang.reflect.Method.invoke(Method.java:566)
  at org.testng.internal.invokers.MethodInvocationHelper.invokeMethod(MethodInvocationHelper.java:135)
  at org.testng.internal.invokers.MethodInvocationHelper.invokeMethodConsideringTimeout(MethodInvocationHelper.java:65)
  at org.testng.internal.invokers.ConfigInvoker.invokeConfigurationMethod(ConfigInvoker.java:381)
  at org.testng.internal.invokers.ConfigInvoker.invokeConfigurations(ConfigInvoker.java:319)
  at org.testng.internal.invokers.TestInvoker.runConfigMethods(TestInvoker.java:803)
  at org.testng.internal.invokers.TestInvoker.runAfterConfigurations(TestInvoker.java:772)
  at org.testng.internal.invokers.TestInvoker.invokeMethod(TestInvoker.java:748)
  at org.testng.internal.invokers.TestInvoker.invokeTestMethod(TestInvoker.java:220)
  at org.testng.internal.invokers.MethodRunner.runInSequence(MethodRunner.java:50)
  at org.testng.internal.invokers.TestInvoker$MethodInvocationAgent.invoke(TestInvoker.java:945)
  at org.testng.internal.invokers.TestInvoker.invokeTestMethods(TestInvoker.java:193)
  at org.testng.internal.invokers.TestMethodWorker.invokeTestMethods(TestMethodWorker.java:146)
  at org.testng.internal.invokers.TestMethodWorker.run(TestMethodWorker.java:128)
  at java.base/java.util.ArrayList.forEach(ArrayList.java:1541)
  at org.testng.TestRunner.privateRun(TestRunner.java:808)
  at org.testng.TestRunner.run(TestRunner.java:603)
  at org.testng.SuiteRunner.runTest(SuiteRunner.java:429)
  at org.testng.SuiteRunner.runSequentially(SuiteRunner.java:423)
  at org.testng.SuiteRunner.privateRun(SuiteRunner.java:383)
  at org.testng.SuiteRunner.run(SuiteRunner.java:326)
  at org.testng.SuiteRunnerWorker.runSuite(SuiteRunnerWorker.java:52)
  at org.testng.SuiteRunnerWorker.run(SuiteRunnerWorker.java:95)
  at org.testng.TestNG.runSuitesSequentially(TestNG.java:1249)
  at org.testng.TestNG.runSuitesLocally(TestNG.java:1169)
  at org.testng.TestNG.runSuites(TestNG.java:1092)
  at org.testng.TestNG.run(TestNG.java:1060)
  at com.intellij.rt.testng.IDEARemoteTestNG.run(IDEARemoteTestNG.java:66)
  at com.intellij.rt.testng.RemoteTestNGStarter.main(RemoteTestNGStarter.java:109)




  


• How to Conduct a Customer Journey Analysis (Step-by-Step)

  9 mai 2024, par Erin

  Your customers are everything.

  Treat them right, and you can generate recurring revenue for years. Treat them wrong ; you’ll be spinning your wheels and dealing with churn.

  How do you give your customers the best experience possible so they want to stick around ?

  Improve their customer experience.

  How ?

  By conducting a customer journey analysis.

  When you know how your customers experience your business, you can improve it to meet and exceed customer expectations.

  In this guide, we’ll break down how the customer journey works and give you a step-by-step guide to conduct a thorough customer journey analysis so you can grow your brand.

  What is a customer journey analysis ?

  Every customer you’ve ever served went on a journey to find you.

  From the moment they first heard of you, to the point that they became a customer. 

  Everything in between is the customer journey.

  A customer journey analysis is how you track and analyse how your customers use different channels to interact with your brand.

  

  Analysing your customer journey involves identifying the customer’s different touchpoints with your business so you can understand how it impacts their experience. 

  This means looking at every moment they interacted with your brand before, during and after a sale to help you gain actionable insights into their experience and improve it to reach your business objectives.

  Your customers go through specific customer touchpoints you can track. By analysing this customer journey from a bird’s eye view, you can get a clear picture of the entire customer experience.

  4 benefits of customer journey analysis

  Before we dive into the different steps involved in a customer journey analysis, let’s talk about why it’s vital to analyse the customer journey.

  By regularly analysing your customer journey, you’ll be able to improve the entire customer experience with practical insights, allowing you to :

  Understand your customers better

  What’s one key trait all successful businesses have ?

  They understand their customers.

  By analysing your customer journey regularly, you’ll gain new insights into their wants, needs, desires and behaviours, allowing you to serve them better. These insights will show you what led them to buy a product (or not).

  For example, through conducting a customer journey analysis, a company might find out that customers who come from LinkedIn are more likely to buy than those coming from Facebook.

  Find flaws in your customer journey

  Nobody wants to hear they have flaws. But the reality is your customer journey likely has a few flaws you could improve.

  By conducting customer journey analysis consistently, you’ll be able to pinpoint precisely where you’re losing prospects along the way. 

  For example, you may discover you’re losing customers through Facebook Ads. Or you may find your email strategy isn’t as good as it used to be.

  But it’s not just about the channel. It could be a transition between two channels. For example, you may have great engagement on Instagram but are not converting them into email subscribers. The issue may be that your transition between the two channels has a leak.

  Or you may find that prospects using certain devices (i.e., mobile, tablet, desktop) have lower conversions. This might be due to design and formatting issues across different devices.

  By looking closely at your customer journey and the different customer touchpoints, you’ll see issues preventing prospects from turning into leads or customers from returning to buy again as loyal customers.

  Gain insights into how you can improve your brand

  Your customer journey analysis won’t leave you with a list of problems. Instead, you’ll have a list of opportunities.

  Since you’ll be able to better understand your customers and where they’re falling off the sales funnel, you’ll have new insights into how you can improve the experience and grow your brand.

  For example, maybe you notice that your visitors are getting stuck at one stage of the customer journey and you’re trying to find out why.

  So, you leverage Matomo’s heatmaps, sessions recordings and scroll depth to find out more.

  In the case below, we can see that Matomo’s scroll map is showing that only 65% of the visitors are reaching the main call to action (to write a review). 

  

  To try to push for higher conversions and get more reviews, we could consider moving that button higher up on the page, ideally above the fold.

  Rather than guessing what’s preventing conversions, you can use user behaviour analytics to “step in our user’s shoes” so you can optimise faster and with confidence.

  Try Matomo for Free

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

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  Grow your revenue

  By taking charge of your customer journey, you can implement different strategies that will help you increase your reach, gain more prospects, convert more prospects into customers and turn regulars into loyal customers.

  Using customer journey analysis will help you optimise those different touchpoints to maximise the ROI of your channels and get the most out of each marketing activity you implement.

  7 steps to conduct a customer journey analysis

  Now that you know the importance of conducting a customer journey analysis regularly, let’s dive into how to implement an analysis.

  Here are the seven steps you can take to analyse the customer journey to improve your customer experience :

  

  1. Map out your customer journey

  Your first step to conducting an effective customer journey analysis is to map your entire customer journey.

  Customer journey mapping means looking at several factors :

  • Buying process
  • Customer actions
  • Buying emotions
  • Buying pain points
  • Solutions

  Once you have an overview of your customer journey maps, you’ll gain insights into your customers, their interests and how they interact with your brand. 

  After this, it’s time to dive into the touchpoints.

  2. Identify all the customer touchpoints 

  To improve your customer journey, you need to know every touchpoint a customer can (and does) make with your brand.

  This means taking note of every single channel and medium they use to communicate with your brand :

  • Website
  • Social media
  • Search engines (SEO)
  • Email marketing
  • Paid advertising
  • And more

  Essentially, anywhere you communicate and interact with your customers is fair game to analyse.

  If you want to analyse your entire sales funnel, you can try Matomo, a privacy-friendly web analytics tool. 

  You should make sure to split up your touchpoints into different customer journey stages :

  • Awareness
  • Consideration
  • Conversion
  • Advocacy

  Then, it’s time to move on to how customers interact on these channels.

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

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  No credit card required

  3. Measure how customers interact on each channel

  To understand the customer journey, you can’t just know where your customers interact with you. You end up learning how they’re interacting.

  This is only possible by measuring customer interactions.

  How ?

  By using a web analytics tool like Matomo.

  With Matomo, you can track every customer action on your website.

  This means anytime they :

  • Visit your website
  • View a web page
  • Click a link
  • Fill out a form
  • Purchase a product
  • View different media
  • And more

  You should analyse your engagement on your website, apps and other channels, like email and social media.

  4. Implement marketing attribution

  Now that you know where your customers are and how they interact, it’s time to analyse the effectiveness of each channel based on your conversion rates.

  Implementing marketing attribution (or multi-touch attribution) is a great way to do this.

  Attribution is how you determine which channels led to a conversion.

  While single-touch attribution models credit one channel for a conversion, marketing attribution gives credit to a few channels.

  For example, let’s say Bob is looking for a new bank. He sees an Instagram post and finds himself on HSBC’s website. After looking at a few web pages, he attends a webinar hosted by HSBC on financial planning and investment strategies. One week later, he gets an email from HSBC following up on the webinar. Then, he decides to sign up for HSBC’s online banking.

  Single touch attribution would attribute 100% of the conversion to email, which doesn’t show the whole picture. Marketing attribution would credit all channels : social media, website content, webinars and email.

  Matomo offers multiple attribution models. These models leverage different weighting factors, like time decay or linear, so that you can allocate credit to each touchpoint based on its impact.

  Matomo’s multi-touch attribution reports give you in-depth insights into how revenue is distributed across different channels. These detailed reports help you analyse each channel’s contribution to revenue generation so you can optimise the customer journey and improve business outcomes.

  Try Matomo for Free

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

  Start for free

  No credit card required

  5. Use a funnels report to find where visitors are leaving

  Once you set up your marketing attribution, it’s time to analyse where visitors are falling off.

  You can leverage Matomo funnels to find out the conversion rate at each step of the journey on your website. Funnel reports can help you see exactly where visitors are falling through the cracks so you can increase conversions.

  6. Analyse why visitors aren’t converting

  Once you can see where visitors are leaving, you can start to understand why.

  For example, let’s say you analyse your funnels report in Matomo and see your landing page is experiencing the highest level of drop-offs.

  

  You can also use form analytics to find out why users aren’t converting on your landing pages – a crucial part of the customer journey.

  7. A/B test to improve the customer journey

  The final step to improve your customer journey is to conduct A/B tests. These are tests where you test one version of a landing page to see which one converts better, drives more traffic, or generates more revenue.

  For example, you could create two versions of a header on your website and drive 50% of your traffic to each version. Then, once you’ve got your winner, you can keep that as your new landing page.

  

  Using the data from your A/B tests, you can optimise your customer journey to help convert more prospects into customers.

  Use Matomo to improve your customer journey analysis

  Now that you understand why it’s important to conduct customer journey analysis regularly and how it works, it’s time to put this into practice.

  To improve the customer journey, you need to understand what’s happening at each stage of your funnel. 

  Matomo gives you insights into your customer journey so you can improve website performance and convert more visitors into customers.

  Used by over 1 million websites, Matomo is the leading privacy-friendly web analytics solution in the world. 

  Matomo provides you with accurate, unsampled data so you understand exactly what’s going on with your website performance.

  The best part ?

  It’s easy to use and is compliant with the strictest privacy regulations.

  Try Matomo free for 21-days and start Improving your customer journey. No credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

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