Step 1: Set Up Your Adalo App

• Create a new Adalo app or open an existing one where you want to implement smart recommendations.
• Ensure you have a clear idea of the types of recommendations you want to provide (e.g., product, content, user connections).

Step 2: Define Your Collections

• Navigate to the Database section of your app.
• Create collections that will store the data you want to recommend. For instance, if you are recommending products, create a “Products” collection.
• Add necessary properties to these collections, such as product name, category, user ratings, etc.

Step 3: Add User Behavior Tracking

• To make recommendations smart, track user interactions like views, likes, or buys. Add these as properties in the 'Users' collection, e.g., “Viewed Products,” “Liked Products.”
• Create actions to update these properties whenever a user interacts with items in your app. For instance, when a user views a product, add that product to the “Viewed Products” property for that user.

Step 4: Create Relationships Between Collections

• Define relationships between your collections. For example, if you’re recommending products, create a relationship between the “Users” and “Products” collections to associate users with their viewed or liked products.
• These relationships will help you build filters to display personalized recommendations.

Step 5: Implement Filtering and Sorting Mechanisms

• Use Adalo's filtering and sorting functionalities to create smart recommendation lists.
• For instance, to display products that a user may like, filter the products based on categories or tags that are similar to those the user has viewed or liked.
• To do this, add a list component, set it to display your “Products” collection, and add a filter to show only products that match the user’s interaction history.

Step 6: Customize Your Recommendation Algorithm

• Enhance the recommendation logic by using more advanced algorithms like collaborative filtering or content-based filtering.
• For collaborative filtering, you could compare users based on their interaction histories and recommend products seen by similar users.
• For content-based filtering, recommend items similar to those a user has interacted with, based on attributes like tags, categories, or descriptions.

Step 7: Display Recommendations on UI

• Add the recommendation lists to the relevant screens in your app.
• Use list and card components that dynamically display the smartly filtered and sorted data.
• Customize the appearance to make the recommendations visually appealing and relevant.

Step 8: Test and Iterate

• After setting up, test the recommendations thoroughly to ensure they are accurate and pertinent.
• Gather feedback from users and make necessary adjustments to your algorithm to improve the precision of recommendations.
• Regularly update your recommendation criteria based on new data and trends.