Visual search optimization in SEO Fundamentals - Mini Project: Build & Apply

Visual Search Optimization

📖 Scenario: You are managing an online store and want to improve how your product images appear in visual search engines like Google Lens or Pinterest Lens. Visual search helps customers find products by uploading or taking photos instead of typing keywords.

🎯 Goal: Build a checklist of key visual search optimization techniques to improve your product images' chances of being found and ranked well in visual search results.

📋 What You'll Learn

Create a list of important image attributes for visual search

Add a configuration variable for minimum image resolution

Use a loop to filter images that meet the resolution requirement

Add a final summary statement about visual search optimization

💡 Why This Matters

🌍 Real World

Online stores and content creators use visual search optimization to help customers find products by images, improving user experience and sales.

💼 Career

SEO specialists and digital marketers apply these techniques to increase organic traffic from visual search platforms.

1

Create a list of image attributes

Create a list called image_attributes with these exact items: 'alt text', 'file name', 'image size', 'image format', and 'structured data'.

SEO Fundamentals

# Create the list image_attributes with the specified items
# Your code here

Need a hint?

Use square brackets to create a list and include all items as strings separated by commas.

2

Set minimum image resolution

Create a variable called min_resolution and set it to 800. This represents the minimum width or height in pixels recommended for visual search images.

SEO Fundamentals

image_attributes = ['alt text', 'file name', 'image size', 'image format', 'structured data']
# Set min_resolution to 800
# Your code here

Need a hint?

Assign the number 800 directly to the variable min_resolution.

3

Filter images by resolution

Given a list called images where each image is a dictionary with a key 'size' holding a tuple of (width, height), create a new list called high_res_images that includes only images where width or height is greater than or equal to min_resolution. Use a for loop with variables image and check image['size'].

SEO Fundamentals

image_attributes = ['alt text', 'file name', 'image size', 'image format', 'structured data']
min_resolution = 800
images = [
    {'file name': 'shirt.jpg', 'size': (1024, 768)},
    {'file name': 'hat.png', 'size': (640, 480)},
    {'file name': 'shoes.jpeg', 'size': (800, 800)}
]
# Create high_res_images list with images meeting min_resolution
# Your code here

Need a hint?

Use a for loop to check each image's width and height, then add qualifying images to high_res_images.

4

Add final summary statement

Create a string variable called summary with this exact text: 'Optimizing images with proper attributes and resolution improves visual search results.'

SEO Fundamentals

image_attributes = ['alt text', 'file name', 'image size', 'image format', 'structured data']
min_resolution = 800
images = [
    {'file name': 'shirt.jpg', 'size': (1024, 768)},
    {'file name': 'hat.png', 'size': (640, 480)},
    {'file name': 'shoes.jpeg', 'size': (800, 800)}
]
high_res_images = []
for image in images:
    width, height = image['size']
    if width >= min_resolution or height >= min_resolution:
        high_res_images.append(image)
# Add the summary string variable
# Your code here

Need a hint?

Assign the exact text to the variable summary using quotes.