Day 6 – Tracking Clicks on GPT Recommendations #LaravelGPT #ClickTracking #AIUX #ProductAnalytics #LaravelInsights

Today, we’ll implement click tracking so you know which GPT-recommended products users actually click on. This will help refine future recommendations and power feedback loops.

Table of Contents

🗂 Step 1: Create a Click Tracking Table

php artisan make:migration create_product_clicks_table

Update the migration:

public function up()
{
    Schema::create('product_clicks', function (Blueprint $table) {
        $table->id();
        $table->foreignId('user_id')->constrained()->onDelete('cascade');
        $table->foreignId('product_id')->constrained()->onDelete('cascade');
        $table->timestamp('clicked_at')->default(now());
        $table->timestamps();
    });
}

Then run:

php artisan migrate

👥 Step 2: Define Relationships

In User.php:

public function productClicks()
{
    return $this->hasMany(\App\Models\ProductClick::class);
}

In Product.php:

public function clicks()
{
    return $this->hasMany(\App\Models\ProductClick::class);
}

🎯 Step 3: Create Controller for Logging Clicks

php artisan make:controller ProductClickController

In ProductClickController.php:

use App\Models\ProductClick;
use Illuminate\Support\Facades\Auth;

public function store($productId)
{
    $user = Auth::user() ?? \App\Models\User::first(); // demo user

    ProductClick::create([
        'user_id' => $user->id,
        'product_id' => $productId,
        'clicked_at' => now(),
    ]);

    return redirect()->route('products.show', $productId); // you can customize this
}

🛣 Step 4: Define Route

In web.php:

use App\Http\Controllers\ProductClickController;

Route::post('/click/{product}', [ProductClickController::class, 'store'])->name('products.click');

🧠 Step 5: Update Blade to Log Clicks

In your Blade view:

<form method="POST" action="{{ route('products.click', $product->id) }}">
    @csrf
    <button type="submit" class="text-blue-500 text-sm mt-3 inline-block">
        View Product
    </button>
</form>

✅ Summary

✅ Today you:

Created a new table to track recommendation clicks
Logged when users engage with suggested items
Built the foundation for feedback-based AI improvements

✅ Up next (Day 7): We’ll begin using click tracking to influence GPT prompts, by weighting product types the user actually engages with.

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