How to track analytics with Supabase?

 

Step 1: Set Up a Supabase Project

 

To start tracking analytics with Supabase, you first need to set up a Supabase project.

• Go to the Supabase website and log in to your account.
• Click on the "New Project" button on your dashboard.
• Fill in the project details such as name, organization, and the database password.
• Click "Create" to set up your project.

 

Step 2: Connect to Your Database

 

Once your project is created, you need to connect to your database to store and retrieve analytics data.

• Navigate to the "Settings" tab on your project dashboard.
• Click on "Database" to find connection details.
• Use the provided URL, username, and password to connect to your PostgreSQL database.

You can use a PostgreSQL client locally or embed the connection information within your application code.

 

Step 3: Create a Table for Analytics

 

Now, create a table where analytics data will be stored.

• Go to the "Table Editor" in your Supabase dashboard.
• Click on "New Table" and define columns relevant for analytics data (e.g., event_name, timestamp, user_id, and extra_data).
• Save the new table.

Here is an example SQL command to create a basic analytics table:

CREATE TABLE analytics (
    id SERIAL PRIMARY KEY,
    event\_name VARCHAR(255),
    timestamp TIMESTAMP DEFAULT CURRENT\_TIMESTAMP,
    user\_id INT,
    extra\_data JSONB
);

 

Step 4: Insert Analytics Data

 

With the table created, you can now begin inserting analytics data.

For JavaScript integration via Supabase Client, use the following code snippet:

import { createClient } from '@supabase/supabase-js';

const supabase = createClient('https://your-project-url.supabase.co', 'public-anon-key');

async function trackEvent(event_name, user_id, extra\_data = {}) {
  let { data, error } = await supabase
    .from('analytics')
    .insert([
      { event_name, user_id, extra\_data },
    ]);

  if (error) console.error('Error inserting data:', error);
  else console.log('Data inserted:', data);
}

// Example usage
trackEvent('page\_view', 1, { page: 'homepage' });

Make sure you replace 'https://your-project-url.supabase.co' and 'public-anon-key' with your actual Supabase project details.

 

Step 5: Query Analytics Data

 

To analyze the collected analytics data, you can execute SQL queries directly on Supabase or programmatically fetch and process this data.

For example, to get all events:

async function fetchEvents() {
  let { data, error } = await supabase
    .from('analytics')
    .select('\*');

  if (error) console.error('Error fetching data:', error);
  else console.log('Analytics data:', data);
}

fetchEvents();

 

Step 6: Visualize Analytics Data

 

Visualizing your analytics data can provide more insights than raw data.

• You can connect the Supabase database to third-party visualization tools, such as Tableau, Metabase, or any other that supports PostgreSQL.
• Alternatively, implement visualization within your application using libraries such as Chart.js or D3.js by fetching data through the Supabase client.

 

Step 7: Automate & Monitor

 

Set up automated data tracking with regular jobs or triggers:

• You can use Supabase's "Functions" feature for creating serverless functions that run automatically based on triggers or schedules.
• You may also integrate a monitoring system using alerts to track the health of your analytics tracking.

 

By following these steps, you efficiently track and analyze user interactions through Supabase and gain valuable insights into user behaviors.