Reteno offers you pre-set pulls of events in mobile apps, messages, and eCommerce projects. By leveraging Reteno’s standard events, you can systematically track and analyze user interactions, enhancing your ability to deliver personalized experiences and achieve business goals.
SDK
Reteno’s SDK contains API methods for tracking custom events, enriching user profiles, and sending push notifications to app users.
After integrating SDK, the system starts to collect such events:
-
Screen Event
- Screen viewed
-
Session Events
- Session started
- Session ended
-
App Lifecycle Events
- Application installed
- Application updated
- Application opened
- Application backgrounded
- Push notifications subscribed
- Push notifications unsubscribed
- Session started
- Session ended
Note
By default, tracking the Screen view event is inactive, while tracking Session and App Lifecycle events is active in the SDK settings.
Messaging
Messaging events include actions that occur in your omnichannel campaigns. These events are vital for optimizing engagement and ensuring effective communication strategies.
The system tracks the following events in messages (they may differ depending on the channel):
- Send
- Delivery
- Delivery error
- Open
- Click
- Click on a button in email
- Unsubscribe
- Unavailable when being sent
- Spam complains
eCommerce
Web tracking for eCommerce involves monitoring and analyzing the behavior and activities of website visitors. This process helps to understand how users interact with the site, what products they are interested in, and what factors influence their purchasing decisions. Web tracking is crucial for optimizing the user experience, increasing conversions, and making data-driven decisions.
After enabling web tracking, the system starts to collect such events:
- Online Store Events
- Product page viewed (view of the product card)
- Page viewed
- Category page viewed
- Added to cart
- Orders
- Search request
- Added to wishlist
- Product Events
- Viewed item is in a stock
- Item from wishlist is in stock
- Regular demand
- Price drop
- Predicted Event
Machine learning models select contacts most likely to purchase within the next 30 days. This segmentation method allows you to interact only with the most potential buyers, so you save your budget on those with a low chance of buying.