how to explain device ID and how the tracking for users in an anonymous state works and
Something like this: For these segments of users, because they are anonymous at this point, we are still able to monitor any spikes in errors using device ID.
Complete it
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Certainly! Here’s a complete explanation based on the knowledge sources: For these segments of users, because they are anonymous at this point, we are still able to monitor any spikes in errors using device ID. Mixpanel automatically assigns a unique $device_id to each device when a user interacts with your product in an anonymous state. All events tracked before a user logs in or registers are associated with this $device_id. This means that even if we don’t know who the user is, we can still group and analyze their actions, such as tracking error rates or behavioral patterns, by device. The $device_id acts as an anonymous identifier, allowing us to monitor trends and issues among users who haven’t yet identified themselves, without collecting any personally identifiable information. Once a user logs in or registers, their previous anonymous activity (tied to $device_id) can be merged with their identified profile, providing a complete view of their journey Reserved Properties Reference Identifying Users (Simplified).This approach ensures that we can detect and respond to issues affecting anonymous users, such as error spikes, while respecting user privacy.
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Yes, if the same user uses two different browsers on the same device, Mixpanel will assign a separate $device_id for each browser. This is because the $device_id is generated and stored locally by the SDK in the browser’s storage (such as cookies or localStorage), and each browser maintains its own storage. As a result, activity from the same user in different browsers on the same device will be tracked under different anonymous $device_ids until the user logs in or is otherwise identified, at which point those IDs can be merged if proper identity management is implemented Identifying Users (Simplified).
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To refine and improve your rationale for tracking, you could state: We want to identify which cards are most popular among users and analyze how their position within the interface influences user engagement. By tracking both the card identifier and its position as event properties, we can break down user interactions across different dimensions—such as card type, position, and user segment. This structured approach enables us to answer questions like: “Are certain cards more likely to be selected because of their content, or does their placement drive popularity?” Optimizing our data structure in this way allows for efficient analysis and reduces complexity, making it easier to uncover actionable insights about user preferences and interface design effectiveness How to use Mixpanel to get closer to data democratization.
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To define "position" as an event property when there are 6 cards, you should use a property (e.g., card_position) that captures the index or order of the card as it appears in the interface. For example, you can assign values from 1 to 6, where 1 represents the first card, 2 the second, and so on up to 6 for the last card. This approach allows you to analyze user interactions based on the card's placement.Mixpanel recommends using clear and consistent event properties to provide context for events, such as the position of a card when a user interacts with it. This enables you to break down and compare engagement across different positions efficiently, without creating separate events for each card or position. For example, you might track an event like card_clicked with properties such as card_id and card_position set to values between 1 and 6 Best Practices: Keep Events as Actions.If you want to analyze whether certain positions are more popular, this structure will allow you to easily filter and compare interactions by the card_position property.
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Tracking which task list options are shown to different user segments—and how those options impact first session or early engagement—is important for several reasons: By capturing which options are presented to each segment and measuring subsequent engagement events (such as task completions or feature usage), you can determine which configurations are most effective at driving early user activity. This allows you to compare engagement rates across segments and optimize the onboarding experience for each group.Mixpanel’s segmentation and cohort analysis features are designed for exactly this type of analysis. You can break down user engagement by segment and by the specific options shown, helping you identify which combinations lead to higher activation and retention. This data-driven approach enables you to iterate on your onboarding and task list strategies, ensuring that each user segment receives the most engaging experience possible How fintech companies can use product analytics to improve customer lifetime value Identify problematic areas in your product.In summary, tracking these details helps you answer: “Which task list options, when shown to specific user segments, result in higher first session or early engagement?”—enabling you to personalize and improve the user journey.
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We want to validate one of the design team hypothesis on whether the secondary CTA is not driving any meaningful engagement and can be sunset. Also to validate whether for users presented with the “explore” if shown both options is introducing user confusion. Refine and make clearer kapa.ai for rationale for tracking
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Certainly! Here’s a refined and clearer rationale for tracking, grounded in Mixpanel best practices: We want to validate the design team’s hypothesis that the secondary CTA may not be contributing to meaningful user engagement and could potentially be removed. Additionally, we aim to assess whether presenting users with both the primary and “explore” CTAs at the same time leads to confusion or impacts engagement negatively. By tracking user interactions with each CTA, as well as subsequent engagement metrics, we can quantitatively determine the effectiveness of the secondary CTA and identify any friction or drop-off when both options are shown. This data-driven approach will help us make informed decisions about interface simplification and optimize the user journey based on actual behavior rather than assumptions Why designers should love (not fear) product analytics How Mixpanel uses Mixpanel: Expert advice.
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Track users interaction with the notification bell
Rationale:
To validate if it is the first action done by a user when they land on the landing page.
To validate if member clicks in a session at all.
To validate if members are clicking when there is an item in notification dropdown to complete or not.
Track user interaction with the items in the notification bell.
Rationale:
To validate the success rate of users completing the task listed in the notification dropdown using this entry point.
Refine and improve make concise and clear rationale, improve to ensure it make sense kapa.ai
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Certainly! Here’s a refined, concise, and clear rationale for tracking, aligned with Mixpanel best practices: 1. Track user interaction with the notification bell Rationale: - Determine if the notification bell is the first action users take upon landing on the page. - Measure overall engagement with the notification bell during a session. - Assess whether users are more likely to click the bell when actionable items are present in the dropdown.2. Track user interaction with items in the notification dropdown Rationale: - Evaluate the completion rate of tasks initiated from the notification dropdown, helping to understand the effectiveness of this entry point.This approach ensures you capture actionable data to validate user behavior hypotheses and optimize the notification experience, following Mixpanel’s guidance to track meaningful events and properties for clear analysis Best Practices: Keep Events as Actions Build Your Tracking Strategy.
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This design screens highlighted in rectangular in this ticket is purely for showing what needs to be tracked. This applies to all 6 links in the card Call out that it's just there to aid with understanding what needs to be done and should be relied as source of truth for what is presented in the figma and it's purely for showing an example of what needs to be track and not that the only item highlighted should be tracked kapa.ai
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To clarify, the design screens highlighted in rectangles within this ticket are intended solely to illustrate examples of what should be tracked. They are provided to aid understanding of the tracking requirements and should not be considered the source of truth for what is presented in Figma. The highlights are not exhaustive—tracking should not be limited only to the items shown as highlighted. Instead, refer to the tracking plan and Figma documentation for the complete and authoritative list of elements and interactions that need to be tracked. This approach aligns with Mixpanel’s best practices, which recommend maintaining a centralized and continuously updated tracking plan as the definitive reference for implementation Create A Tracking Plan.
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To refine this for a ticket and provide clear context, you could write: Please note: The requirements for tracking member interactions with the registration fail screen and sign-in fail screen are documented separately in a dedicated analytics ticket. This ensures that tracking for these specific error states is managed independently and can be referenced as needed. For comprehensive tracking coverage, always refer to the centralized tracking plan as the source of truth Create A Tracking Plan.This approach aligns with Mixpanel’s best practices of maintaining a clear, centralized, and continuously updated tracking plan, and helps avoid confusion about where to find requirements for different user flows.
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In Mixpanel, the primary identifier used to map and analyze users is the distinct_id. This property uniquely identifies each user and is used for aggregating user-level metrics, such as determining how many unique members are affected by a particular issue or event. If your data point unique_id refers to the distinct_id property, then yes, you can rely on it to map out the scale of members affected. However, if unique_id is a custom property and not the standard distinct_id, you should ensure it is consistently and uniquely assigned to each user to avoid inaccuracies. Mixpanel’s reporting and segmentation are based on the distinct_id for user uniqueness Identity Management Overview.If you are using the standard distinct_id, you can confidently use it to measure the number of unique members impacted. If you are referring to a different property, please verify its implementation and consistency.
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