Building a Marketplace and Fintech App: A Developer's Guide to User Engagement and Metrics

#analytics #eventdriven #product #reactnative

In today's digital landscape, marketplace and fintech apps play a crucial role in providing seamless experiences for users. As a developer, understanding user engagement and tracking relevant metrics is vital for optimizing app performance and driving success. In this article, we will explore key metrics and best practices for developing a marketplace and fintech app, focusing on user engagement and the unique considerations of this industry.

User Engagement and Onboarding: User onboarding is the first touchpoint where users are introduced to the app's features and functionality. Tracking user engagement during onboarding helps identify areas for improvement and optimizing the user experience. Consider implementing the following metrics:

Onboarding_Show:
- Measure the display of onboarding screens, segmented by market, payments, cashback, or cards.
- Gather data on which onboarding screens users are exposed to, providing insights into their initial interaction with different app features.
- Segment data based on specific onboarding steps to assess user progress and drop-off rates.
Onboarding_Action:
- Track user interactions during onboarding, such as navigating between steps (prev, next), skipping, or finishing the onboarding process.
- Analyze user behavior patterns to identify potential areas of confusion or friction during onboarding.
- Use this data to optimize the onboarding flow, ensuring a smooth and intuitive user experience.

App Open and User Authentication: Monitoring app open events provides insights into user behavior and authentication status. Capture the following metrics:

App_Open:
- Track the initial app open, including the source (home, push notification, deeplink), first-time open, and authentication status (logged in or not).
- Analyze user acquisition channels to identify the most effective sources driving app opens.
- Monitor authentication status to assess the user base's overall engagement and the proportion of registered users.

User Engagement within the App: To gauge user engagement within the app, it's essential to track various interactions and actions. Consider the following metrics:

Open_Scanner:
- Record user actions when accessing the scanner within the app, such as scanning a puntoOperator or checkTransaction.
- Measure the frequency of scanner usage to evaluate its popularity among users.
- Analyze user feedback and behavior to improve scanner functionality and optimize its integration into the app.
Support_Chat_Open:
- Monitor the opening of support chat, categorizing the source (order, parcel, profile, push, deeplink, transaction, receipt, kyc).
- Measure the volume and nature of support chat interactions to identify areas where users frequently seek assistance.
- Use this data to improve self-service features, provide proactive support, and streamline user inquiries.
Profile_Open:
- Track the frequency of profile screen access to understand user engagement with account-related features.
- Analyze patterns in profile opens to identify potential pain points or areas of interest for users.
- Use the data to optimize the layout and organization of profile screens and enhance the user experience.
Profile_Action:
- Track specific actions within the profile screen, such as editing profile details, managing orders, addresses, bank cards, and support interactions.
- Analyze user behavior within the profile screen to identify common actions and potential areas for improvement.
- Use this data to streamline profile-related features and enhance user control over their account settings.
Profile_Show_Notifications_Change:
- Capture events when users toggle the notification settings in their profile (set_value = true / false).
- Analyze the frequency and impact of users modifying their notification preferences.
- Use this data to optimize the delivery of relevant notifications and improve user engagement.
Bank_Card_Store

_Change:

Monitor events when users add or remove a bank card from their account (is_stored = true / false).
Track the frequency of bank card updates to identify user preferences and trends.
Use this data to enhance the payment experience, streamline card management, and improve transaction success rates.

Product Interaction and Marketplace Features: For a marketplace app, tracking user engagement with products, categories, and search functionality is crucial. Consider the following metrics:

Favorites_Change:
- Monitor user actions when adding or removing items from their favorites list.
- Track the frequency of favorites changes to gauge user interest and preferences.
- Analyze the data to improve personalized recommendations, enhance product discovery, and tailor marketing campaigns.
PDP (Product Details Page)_Open:
- Capture events when users view product details pages, categorizing the source (main, search, catalogue, favorites, orders, cart, product deeplink, brand, store).
- Track user interactions with product details pages to understand engagement levels and feature usage.
- Analyze user feedback and behavior to optimize the presentation of product information, images, and pricing.
PDP_Action:
- Monitor user interactions and actions within the product details page, such as selecting options, adding to cart, changing quantity, adding/removing from favorites, and accessing additional information.
- Analyze user behavior to identify popular features, potential friction points, and opportunities for enhancing the product details page.
- Use this data to improve the user experience, streamline purchasing flows, and drive conversion rates.
Catalogue_Open:
- Track user actions when accessing the catalogue via the tab bar.
- Monitor the frequency of catalogue opens to assess the app's overall usage and popularity of browsing products.
- Analyze user journeys within the catalogue to identify common paths and improve navigation.
Catalogue_Category_Open:
- Capture events when users open specific category sections within the catalogue, noting the source (catalogue, deeplink, carousel, categories tree).
- Monitor user engagement with different catalogue categories to identify popular sections and areas of interest.
- Use this data to refine category organization, improve product filtering options, and optimize the presentation of category-specific content.
Search_Screen_Open:
- Track user actions when initiating a search within the app, noting the source (main, category, catalogue).
- Monitor the frequency of search screen opens to understand user preferences for discovering products.
- Analyze search query patterns to improve search relevance, suggest relevant keywords, and enhance the overall search experience.
Search_Screen_Suggest_Load:
- Capture events when users load search suggestions based on their entered search text.
- Track the popularity and effectiveness of search suggestions, measured by the number of loaded suggestions.
- Use this data to refine search algorithms, optimize suggestion relevance, and enhance user satisfaction.
Search_Screen_Suggest_Choosed:
- Monitor events when users choose a suggestion from the search screen suggestions list.
- Track the most popular suggestions and their conversion rates to understand user search intent.
- Analyze this data to improve search result accuracy, enhance product discovery, and refine suggestion algorithms.

Here is the visualization of the metrics tree

Conclusion:
Developing a successful marketplace and fintech app requires a thorough understanding of user engagement and relevant metrics. By tracking key metrics related to onboarding, user engagement, and marketplace features, developers can gain valuable insights into user behavior, identify areas for improvement, and optimize the app's performance. By prioritizing user engagement and continuously refining the app based on user feedback and data-driven insights, developers can create a seamless and successful marketplace and fintech app experience.