### JavaScript Example: Fetching Data for Dynamic Content

Source: https://www.webpro.in/geo-generative-experience-optimization-is-not-the-new-seo-but-an-evolution-to-it-seo-in-a-new-avatar/

A JavaScript example showing how to fetch data from an API to dynamically update content on a web page, simulating personalized content delivery.

```JavaScript
async function loadPersonalizedContent(userId) {
    const contentElement = document.getElementById('personalized-content');
    if (!contentElement) {
        console.error('Element with ID "personalized-content" not found.');
        return;
    }

    try {
        // Simulate fetching user-specific data from an API
        // In a real scenario, this would be a fetch() call to your backend
        const userData = await fetchUserData(userId);

        // Simulate generating content based on user data
        const personalizedHtml = generateHtmlForUser(userData);

        contentElement.innerHTML = personalizedHtml;

    } catch (error) {
        console.error('Error loading personalized content:', error);
        contentElement.innerHTML = '<p>Could not load personalized content. Please try again later.</p>';
    }
}

// Mock API function to simulate fetching user data
async function fetchUserData(userId) {
    console.log(`Fetching data for user: ${userId}`);
    // Simulate network delay
    await new Promise(resolve => setTimeout(resolve, 500));
    // Mock data based on userId
    if (userId === 'user123') {
        return { name: 'Alice', interests: ['AI', 'SEO'], lastVisit: '2023-10-27' };
    } else if (userId === 'user456') {
        return { name: 'Bob', interests: ['Tech', 'Gadgets'], lastVisit: '2023-10-26' };
    } else {
        return { name: 'Guest', interests: [], lastVisit: null };
    }
}

// Mock function to generate HTML based on user data
function generateHtmlForUser(userData) {
    let html = `<h2>Welcome, ${userData.name}!</h2>`;
    if (userData.interests && userData.interests.length > 0) {
        html += `<p>Based on your interests in: ${userData.interests.join(', ')}</p>`;
        if (userData.interests.includes('AI')) {
            html += '<p>Check out our latest articles on Generative AI!</p>';
        }
    }
    if (userData.lastVisit) {
        html += `<p>Your last visit was on ${userData.lastVisit}.</p>`;
    }
    return html;
}

// Example Usage:
// Assuming a user ID is available, e.g., from a login session or URL parameter
const currentUserId = 'user123'; // Replace with actual user ID retrieval

// Call the function when the DOM is ready
document.addEventListener('DOMContentLoaded', () => {
    loadPersonalizedContent(currentUserId);
});

// HTML structure needed:
// <div id="personalized-content">Loading...</div>
```

--------------------------------

### Python Example: Generating Text with OpenAI API

Source: https://www.webpro.in/geo-generative-experience-optimization-is-not-the-new-seo-but-an-evolution-to-it-seo-in-a-new-avatar/

A Python example demonstrating how to use the OpenAI API to generate text content, such as product descriptions or blog post snippets, based on a given prompt.

```Python
import openai

# Ensure you have your OpenAI API key set as an environment variable
# export OPENAI_API_KEY='your-api-key'

openai.api_key = openai.api_key

def generate_text_content(prompt, max_tokens=150):
    """Generates text content using the OpenAI API."""
    try:
        response = openai.chat.completions.create(
            model="gpt-3.5-turbo", # Or "gpt-4"
            messages=[
                {"role": "system", "content": "You are a helpful assistant that generates creative content."},
                {"role": "user", "content": prompt}
            ],
            max_tokens=max_tokens,
            temperature=0.7 # Controls randomness: lower is more deterministic
        )
        return response.choices[0].message.content.strip()
    except Exception as e:
        return f"An error occurred: {e}"

# Example Usage:
user_prompt = "Write a short, engaging product description for a new eco-friendly water bottle."
generated_description = generate_text_content(user_prompt)

print("--- Generated Product Description ---")
print(generated_description)

user_prompt_blog = "Generate a blog post intro about the benefits of Generative Experience Optimization (GEO)."
generated_intro = generate_text_content(user_prompt_blog, max_tokens=200)

print("\n--- Generated Blog Intro ---")
print(generated_intro)
```

--------------------------------

### Transforming Search Queries to AI Prompts

Source: https://www.webpro.in/are-the-ai-prompts-the-new-search-queries/

Illustrates how common search queries can be reframed into more effective AI prompts by adding context, specifying desired output format, and defining the target audience.

```AI Prompt Examples
1. Learning a Concept:
   Search Query: how does blockchain work
   AI Prompt: "Explain blockchain in simple terms using a supply chain example. Include real-world use cases."

2. Professional Writing Help:
   Search Query: cover letter for marketing job
   AI Prompt: "Write a cover letter for a mid-level marketing role emphasizing skills in digital strategy and analytics. Keep it to 300 words."

3. Summarizing Content:
   Search Query: summary of To Kill a Mockingbird
   AI Prompt: "Summarize 'To Kill a Mockingbird' in 5 bullet points for a high school student, focusing on main themes and character arcs."

4. Task Completion:
   Search Query: how to make pasta with tomatoes and spinach
   AI Prompt: "Give me a quick vegetarian pasta recipe using only tomatoes, garlic, olive oil, and spinach. Prep time under 20 minutes."
```

--------------------------------

### Google SGE Interaction Example

Source: https://www.webpro.in/seo-in-the-age-of-ai-and-sge-search-generative-experience/

Illustrates how users can interact with Google's Search Generative Experience (SGE) by asking follow-up questions to explore topics further, moving into a conversational search mode.

```APIDOC
SearchGenerativeExperience (SGE):
  Functionality: AI-powered search summaries and conversational follow-ups.
  User Interaction:
    1. Initial Search Query -> AI-powered snapshot summary at the top of SERPs.
    2. Snapshot includes pertinent considerations and useful information.
    3. Snapshot acts as a starting point for exploring diverse content.
    4. Suggested next steps appear below the snapshot.
    5. Example Follow-up Question: "How long to spend at Bryce Canyon with kids?"
    6. Tapping follow-up questions initiates a new conversational mode.
  Key Features:
    - Generates new content (text, summaries).
    - Provides thorough and insightful responses.
    - Offers a dynamic and interactive search experience.
    - Understands user intent to generate tailored overviews.
  Dependencies:
    - Google Chrome (for opt-in via Search Labs).
    - Access to Search Labs.
  Limitations:
    - Experimental feature.
    - Availability may vary.
```

--------------------------------

### Define Product Database Schema (SQL)

Source: https://www.webpro.in/seo-for-e-commerce-sites/

An example SQL CREATE TABLE statement for a products table. It outlines essential fields like id, name, category, and features, which are necessary for populating meta tag templates.

```sql
CREATE TABLE products (
	id INT PRIMARY KEY,
	name VARCHAR(255),
	category VARCHAR(255),
	feature1 VARCHAR(255),
	feature2 VARCHAR(255),
	...
);
```

--------------------------------

### Webpro.in Prefetching Configuration

Source: https://www.webpro.in/how-to-demonstrate-e-e-a-t-in-your-content/

JSON configuration object specifying prefetching strategies for the webpro.in website. It defines resources to be prefetched based on document source, href matches, and exclusion rules for specific paths and elements.

```json
{"prefetch":[{"source":"document","where":{"and":[{"href_matches":"\/\*"},{"not":{"href_matches":["\/wp-*.php","\/wp-admin\/\*","\/wp-content\/uploads\/\*","\/wp-content\/\*","\/wp-content\/plugins\/\*","\/wp-content\/themes\/ark\/\*","\/\*\\?(.+)"]}},{"not":{"selector_matches":"a[rel~=\"nofollow\"]"}},{"not":{"selector_matches":".no-prefetch, .no-prefetch a"}}]},"eagerness":"conservative"}]}
```

--------------------------------

### CSS Image Containment Rule

Source: https://www.webpro.in/website-maintenance-services/

A CSS rule that applies intrinsic sizing to images based on their 'sizes' attribute. It specifically targets images where 'sizes' is 'auto' or starts with 'auto,'.

```css
img:is([sizes="auto" i], [sizes^="auto," i]) { contain-intrinsic-size: 3000px 1500px }
```

--------------------------------

### Webpro.in Prefetching Configuration

Source: https://www.webpro.in/how-seo-is-like-yoga-for-your-website-happy-international-yoga-day/

JSON configuration object specifying prefetching strategies for the webpro.in website. It defines resources to be prefetched based on document source, href matches, and exclusion rules for specific paths and elements.

```json
{"prefetch":[{"source":"document","where":{"and":[{"href_matches":"\/\*"},{"not":{"href_matches":["\/wp-*.php","\/wp-admin\/\*","\/wp-content\/uploads\/\*","\/wp-content\/\*","\/wp-content\/plugins\/\*","\/wp-content\/themes\/ark\/\*","\/\*\\?(.+)"]}},{"not":{"selector_matches":"a[rel~=\"nofollow\"]"}},{"not":{"selector_matches":".no-prefetch, .no-prefetch a"}}]},"eagerness":"conservative"}]}
```

--------------------------------

### Webpro.in Prefetching Configuration

Source: https://www.webpro.in/amp-pages-shown-main-google-search-results-preview-experience/

JSON configuration object specifying prefetching strategies for the webpro.in website. It defines resources to be prefetched based on document source, href matches, and exclusion rules for specific paths and elements.

```json
{"prefetch":[{"source":"document","where":{"and":[{"href_matches":"\/\*"},{"not":{"href_matches":["\/wp-*.php","\/wp-admin\/\*","\/wp-content\/uploads\/\*","\/wp-content\/\*","\/wp-content\/plugins\/\*","\/wp-content\/themes\/ark\/\*","\/\*\\?(.+)"]}},{"not":{"selector_matches":"a[rel~=\"nofollow\"]"}},{"not":{"selector_matches":".no-prefetch, .no-prefetch a"}}]},"eagerness":"conservative"}]}
```

--------------------------------

### Render Dynamic Meta Tags in HTML

Source: https://www.webpro.in/seo-for-e-commerce-sites/

An example HTML template (product.html) showing how to dynamically insert generated meta title and description content. It uses Jinja2-style templating syntax like {{ meta_title }} and {{ meta_description }}.

```html
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>{{ meta_title }}</title>
<meta name="description" content="{{ meta_description }}">
<!-- Other head elements -->
</head>
<body>
<!-- Product page content -->
</body>
</html>
```

--------------------------------

### AI Chatbot for Real-time Solutions

Source: https://www.webpro.in/geo-generative-experience-optimization-is-not-the-new-seo-but-an-evolution-to-it-seo-in-a-new-avatar/

Implement AI-powered chatbots to provide real-time, AI-generated solutions to user questions or guide them through processes like purchasing. This enhances customer support and engagement.

```APIDOC
Component: AI Chatbot
Functionality: Real-time User Interaction & Support
Description: Provides instant, AI-generated responses to user queries, offering solutions and guidance.
Key Features:
  - Natural Language Understanding (NLU)
  - Conversational AI
  - Integration with knowledge bases or product catalogs
Use Cases:
  - Answering customer FAQs
  - Guiding users through product selection
  - Assisting with checkout processes
  - Troubleshooting common issues
Parameters:
  - user_query: The text input from the user.
  - context: (Optional) Previous conversation history or user session data.
Returns:
  - AI-generated response text.
  - Actionable suggestions or links.
```

--------------------------------

### WebPro.in Article Links

Source: https://www.webpro.in/understanding-google-amp-cache/

This section lists articles from WebPro.in, each with a title, thumbnail image, and a direct link to the full content. Topics include AI prompts replacing search queries, SEO in the context of short-form video, the evolving role of SEO professionals, and the importance of email marketing.

```html
<a href="https://www.webpro.in/are-the-ai-prompts-the-new-search-queries/">
    <img src="https://www.webpro.in/wp-content/uploads/2025/06/search-queries-AI-Prompts-150x150.png" alt="AI Prompts as New Search Queries">
    Are the AI Prompts the New Search Queries?
</a>

<a href="https://www.webpro.in/seo-in-the-era-of-short-form-video-are-blogs-still-relevant-in-2025/">
    <img src="https://www.webpro.in/wp-content/uploads/2025/05/blogs-short-videos-150x150.png" alt="SEO in Short-Form Video Era">
    SEO in the Era of Short-Form Video: Are Blogs Still Relevant in 2025?
</a>

<a href="https://www.webpro.in/the-changing-role-of-seo-professionals-from-optimizers-to-experience-architects/">
    <img src="https://www.webpro.in/wp-content/uploads/2025/04/SEO-Architect-150x150.png" alt="Changing Role of SEO Professionals">
    The Changing Role of SEO Professionals: From Optimizers to Experience Architects
</a>

<a href="https://www.webpro.in/the-importance-of-email-marketing-in-2025/">
    <img src="https://www.webpro.in/wp-content/uploads/2025/04/Email-Marketing-150x150.png" alt="Email Marketing Importance">
    The Importance of Email Marketing in 2025
</a>
```

--------------------------------

### llms.txt File Format Example

Source: https://www.webpro.in/the-importance-of-llms-txt-for-websites-in-the-era-of-ai-driven-search-results/

Demonstrates the structure and directives of an llms.txt file, used to control AI model access to website content. It follows a format similar to robots.txt, specifying user agents and their allowed/disallowed paths.

```text
User-agent: OpenAI-GPT
Disallow: /private/
Allow: /public/

User-agent: Google-LLM
Disallow: /proprietary-content/
Allow: /blog/

User-agent: *
Disallow: /

```

--------------------------------

### Website Configuration Variables

Source: https://www.webpro.in/how-to-use-python-for-seo-automating-seo-tasks-and-gaining-insights/

Defines essential configuration variables for a website, including the AJAX endpoint URL and the theme template directory path. These are commonly used in WordPress or similar CMS environments for dynamic content loading and theme asset management.

```javascript
var ajaxurl = "https://www.webpro.in/wp-admin/admin-ajax.php";
var ff_template_url = "https://www.webpro.in/wp-content/themes/ark";
```

--------------------------------

### Create Meta Description Template (HTML)

Source: https://www.webpro.in/seo-for-e-commerce-sites/

This HTML snippet defines a template for meta descriptions, incorporating key product features. It uses placeholders such as {{product.feature1}} and {{product.feature2}} to dynamically populate descriptions with product specifics.

```html
<meta name="description" content="Shop {{product.name}} featuring {{product.feature1}}, {{product.feature2}}, and more at {{store.name}}. Enjoy great deals and fast shipping.">
```

--------------------------------

### Webpro.in Prefetching Configuration

Source: https://www.webpro.in/how-to-use-python-for-seo-automating-seo-tasks-and-gaining-insights/

JSON configuration object specifying prefetching strategies for the webpro.in website. It defines resources to be prefetched based on document source, href matches, and exclusion rules for specific paths and elements.

```json
{"prefetch":[{"source":"document","where":{"and":[{"href_matches":"\/\*"},{"not":{"href_matches":["\/wp-*.php","\/wp-admin\/\*","\/wp-content\/uploads\/\*","\/wp-content\/\*","\/wp-content\/plugins\/\*","\/wp-content\/themes\/ark\/\*","\/\*\\?(.+)"]}},{"not":{"selector_matches":"a[rel~=\"nofollow\"]"}},{"not":{"selector_matches":".no-prefetch, .no-prefetch a"}}]},"eagerness":"conservative"}]}
```

--------------------------------

### Dynamic Landing Page Generation (Example)

Source: https://www.webpro.in/geo-generative-experience-optimization-is-not-the-new-seo-but-an-evolution-to-it-seo-in-a-new-avatar/

Utilize AI to dynamically generate landing pages customized based on user attributes like location, behavior, or preferences. This enhances relevance and conversion rates.

```APIDOC
Feature: Dynamic Landing Pages
Description: AI-driven generation of personalized landing page content and layout.
Purpose: Increase user engagement and conversion by tailoring the experience.
Inputs:
  - User ID or Session Data:
    - Location (e.g., 'New York', 'London')
    - Browsing History (e.g., 'viewed_product_X', 'added_to_cart_Y')
    - User Preferences (e.g., 'interested_in_electronics', 'budget_conscious')
  - Content Templates:
    - Pre-defined sections and components for landing pages.
AI Logic:
  - Analyzes user data to select relevant content modules.
  - Generates personalized headlines, product recommendations, or calls-to-action.
Outputs:
  - Dynamically rendered HTML page.
Example Scenario:
  An e-commerce site shows product recommendations based on browsing history.
  User A (viewed 'running shoes'): Sees 'New Arrivals: Running Shoes'.
  User B (viewed 'hiking boots'): Sees 'Featured: Hiking Gear'.
```

--------------------------------

### Webpro.in Prefetching Configuration

Source: https://www.webpro.in/leasing-renting-subdomains-google-say/

JSON configuration object specifying prefetching strategies for the webpro.in website. It defines resources to be prefetched based on document source, href matches, and exclusion rules for specific paths and elements.

```json
{"prefetch":[{"source":"document","where":{"and":[{"href_matches":"\/\*"},{"not":{"href_matches":["\/wp-*.php","\/wp-admin\/\*","\/wp-content\/uploads\/\*","\/wp-content\/\*","\/wp-content\/plugins\/\*","\/wp-content\/themes\/ark\/\*","\/\*\\?(.+)"]}},{"not":{"selector_matches":"a[rel~=\"nofollow\"]"}},{"not":{"selector_matches":".no-prefetch, .no-prefetch a"}}]},"eagerness":"conservative"}]}
```

--------------------------------

### CSS Root Variables

Source: https://www.webpro.in/what-is-influencer-marketing-how-to-check-instagram-influencer-demographics/

Defines CSS root variables, such as '--wp--pre', likely for theme customization or global styling. This snippet indicates the start of a CSS variable declaration block.

```css
:root{
  --wp--pre
```

--------------------------------

### Google Jamboard Collaboration and Interaction

Source: https://www.webpro.in/google-jamboard-integration-whiteboard-cloud/

Details on how users can interact with Google Jamboard sessions, including logging in, starting, joining, and remote participation via companion applications. It also notes platform compatibility and limitations.

```APIDOC
Jamboard Collaboration System:

Functionality:
  Facilitates collaborative work on projects using an interactive cloud-based digital whiteboard.

User Interaction:
  - Log into a Jam Session:
    - Method: Via the Jamboard device itself or companion iOS and Android apps.
    - Requirements: G Suite account for initiating sessions.

  - Start a Jam Session:
    - Initiator: Any user with a G Suite account.
    - Action: Click on the screen to begin.
    - Invitation: Initiator can invite others to join.

  - Join a Jam Session:
    - Active Participants: Users with Jamboard companion apps (iOS/Android) can join and make edits.
    - Remote Participants (with app): Can add content to the Jamboard, with quick updates.
    - View-Only Participants (without app): Can view the session passively, without editing permissions.

Platform Support:
  - Primary Device: Google Jamboard (55" 4K touchscreen).
  - Companion Apps: iOS, Android.
  - Limitations: No Microsoft companion app available.

Key Features:
  - Identifies up to 16 touch points.
  - Dedicated stylus for control (passive, plug-and-play).
  - Finger can be used to erase content.
  - Shape and handwriting recognition.
  - Integration with Google Hangout for remote collaboration.

Use Cases:
  - Business meetings, corporate discussions, presentations.
  - Educational sector collaboration.

Pricing:
  - Device Cost: $4,999
  - Yearly Support Fee: $600
```

--------------------------------

### Webpro.in Prefetching Configuration

Source: https://www.webpro.in/user-experience-as-a-ranking-factor-for-search-engines-google-bing-and-beyond/

JSON configuration object specifying prefetching strategies for the webpro.in website. It defines resources to be prefetched based on document source, href matches, and exclusion rules for specific paths and elements.

```json
{"prefetch":[{"source":"document","where":{"and":[{"href_matches":"\/\*"},{"not":{"href_matches":["\/wp-*.php","\/wp-admin\/\*","\/wp-content\/uploads\/\*","\/wp-content\/\*","\/wp-content\/plugins\/\*","\/wp-content\/themes\/ark\/\*","\/\*\\?(.+)"]}},{"not":{"selector_matches":"a[rel~=\"nofollow\"]"}},{"not":{"selector_matches":".no-prefetch, .no-prefetch a"}}]},"eagerness":"conservative"}]}
```