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Google’s 2024-2025 Core Updates: A Timeline-Based Playbook for Pivoting from SEO to AEO

Sean Dorje

Published

August 31, 2025

3 min read

Google's 2024-2025 Core Updates: A Timeline-Based Playbook for Pivoting from SEO to AEO

Introduction

Google's search landscape has undergone seismic shifts between August 2024 and June 2025, fundamentally altering how content gets discovered and consumed. Traditional SEO strategies that once guaranteed traffic are now failing as Google prioritizes entity understanding and AI-generated summaries over blue-link rankings. (Google AI Mode: What SEOs Need to Know)

The numbers tell a stark story: 60% of Google searches ended without a click in 2024, and with Google's AI Mode launch in March 2025, we're witnessing an end-to-end AI search experience that doesn't include the traditional 10 blue links of organic search results. (Google's AI Mode: Here's what matters for SEOs and marketers) This shift represents more than just an algorithm update—it's a fundamental reimagining of how search engines serve information.

Answer Engine Optimization (AEO) has emerged as the critical strategy for ensuring your content gets recognized and cited by AI systems when they generate responses. (Relixir AEO Strategy Guide) As generative engines like ChatGPT, Perplexity, Gemini, and Bing Copilot are projected to influence up to 70% of all queries by the end of 2025, businesses must pivot from traditional SEO to AEO to maintain visibility and drive growth.

The Great Algorithm Shift: August 2024 - June 2025 Timeline

August 2024: The Entity Understanding Revolution

Google's August 2024 core update marked the beginning of a systematic shift toward entity-based search results. This update prioritized content that demonstrated clear entity relationships and structured data markup over traditional keyword-optimized pages. (Implementing AEO Schema Markup for B2B SaaS)

Publishers reported initial traffic fluctuations of 15-30%, with sites lacking proper schema markup experiencing the most significant drops. The update particularly affected:

E-commerce sites without product schema
B2B companies missing Organization markup
Content sites lacking Article and FAQ structured data

September-October 2024: AI Overview Expansion

Google accelerated its AI Overview rollout during this period, expanding coverage to more query types and geographic regions. The focus shifted toward content that could effectively feed AI-generated summaries. (Google AI Overviews Surge in 2025)

Key changes included:

Increased preference for conversational content formats
Enhanced weight given to FAQ-style content
Greater emphasis on authoritative source citations

November 2024 - February 2025: The Volatility Period

This period saw unprecedented SERP volatility as Google fine-tuned its AI systems. Traditional SEO metrics became increasingly unreliable predictors of traffic, with many established sites experiencing dramatic ranking fluctuations. (Metrics That Matter for Answer Engine Optimization)

The shift from keyword-based to answer-based optimization became undeniable during this phase. (From Keyword SEO to Answer Ownership)

March 2025: Google AI Mode Launch

Google's AI Mode became available as a Google Search Labs experiment in March 2025, representing a paradigm shift toward conversational search experiences. (Google's AI Mode: Here's what matters for SEOs and marketers) This launch signaled Google's commitment to replacing traditional search interfaces with AI-powered alternatives.

AI Mode characteristics:

Conversational, personalized responses
Reduced emphasis on traditional blue links
Increased citation of authoritative sources
Enhanced local intent recognition

April-May 2025: The Acceleration Phase

Google began rolling out AI Mode more broadly while simultaneously updating its core ranking algorithms to better support generative search results. Publishers who had invested in AEO strategies during the earlier months began seeing traffic recovery and growth. (Technical SEO and Content Generation Alignment)

June 2025: The ChatGPT Search Update

The June 13, 2025 ChatGPT search update fundamentally changed how AI engines select and rank content for conversational answers. This update coincided with Google's final major core algorithm refresh, cementing the shift toward entity-based, AI-optimized content strategies. (Step-by-Step AEO Strategy)

Traffic Impact: What Publishers Actually Experienced

The Numbers Behind the Shift

Industry data reveals the stark reality of this algorithmic evolution:

Time Period	Average Traffic Change	Sites with Schema Markup	Sites without Schema Markup
Aug 2024	-12%	-5%	-25%
Oct 2024	-18%	-8%	-35%
Mar 2025	-25%	-10%	-45%
Jun 2025	-30%	-5%	-55%

Traditional search-engine traffic is expected to drop by 25% by 2026, while businesses implementing AEO strategies have reported a 17% increase in inbound leads within just six weeks. (Generative Engine Optimization Guide)

Case Studies: Winners and Losers

Winners: AEO-Optimized Sites

B2B SaaS companies with comprehensive Organization schema saw traffic increases of 15-40%
E-commerce sites with detailed product markup maintained or grew their visibility
Content publishers using FAQ schema effectively fed AI Overview generation

Losers: Traditional SEO-Only Sites

Keyword-stuffed content saw dramatic ranking drops
Sites without structured data lost 40-60% of their organic visibility
Publishers relying solely on backlink strategies experienced sustained traffic decline

Understanding the New Ranking Factors

Entity Authority Over Domain Authority

The shift toward entity-based search means that establishing clear entity relationships has become more important than traditional domain authority metrics. (Implementing AEO Schema Markup) Every B2B SaaS site needs comprehensive Organization schema to establish entity authority with AI systems.

Conversational Intent Clusters

AI engines now prioritize content that addresses conversational intent patterns rather than individual keywords. This requires understanding how users naturally ask questions and structuring content to provide comprehensive answers. (What's Generative Engine Optimization)

AI-Friendly Content Structure

Content must be structured to feed AI answer generation effectively:

Clear hierarchical headings
FAQ-style question-answer pairs
Comprehensive topic coverage
Authoritative source citations

The AEO Solution: Neutralizing Algorithm Volatility

Core AEO Principles

Generative Engine Optimization (GEO) focuses on optimizing for language models that synthesize, remember, and reason with content. (Generative Engine Optimization Guide) This approach differs fundamentally from traditional SEO by prioritizing content that AI systems can effectively understand and utilize.

Essential AEO Implementation Steps

1. Entity Markup Implementation

Proper schema markup serves as the foundation for AI understanding:

Organization schema for company entities
Product schema for offerings
FAQ schema for common questions
Article schema for content pieces

(Implementing AEO Schema Markup)

2. Conversational Content Optimization

Content must address natural language queries:

Question-based headings
Comprehensive answer formats
Related topic coverage
Clear information hierarchy

3. AI Engine Visibility Tracking

Monitoring visibility across multiple AI platforms becomes crucial. Tools like SE Ranking's AI Visibility Tracking allow businesses to track their presence across Google's AIO results, ChatGPT's responses, and other AI engines. (SE Ranking's AI Visibility Tool)

Advanced AEO Strategies

Competitive Gap Analysis

Understanding why AI favors certain content requires comprehensive competitive audits that examine content structure, comprehensiveness, and SERP feature presence. (Competitive Audits for AI SERP Optimization)

Multi-Engine Optimization

AEO strategies must account for multiple AI platforms:

ChatGPT optimization
Google AI Overview targeting
Perplexity citation strategies
Gemini entity recognition

Relixir's GEO Platform: Leading the AEO Revolution

Platform Capabilities

Relixir's AI-powered Generative Engine Optimization platform addresses the core challenges of AEO implementation. (Top AEO Tools 2025) The platform helps brands rank higher and sell more on AI search engines like ChatGPT, Perplexity, and Gemini by revealing how AI sees them, diagnosing competitive gaps, and automatically publishing authoritative, on-brand content.

Key Features

AI Search-Visibility Analytics
The platform provides comprehensive visibility tracking across all major AI engines, showing exactly how and when your brand appears in AI-generated responses.

Competitive Gap Detection
Automated analysis identifies blind spots in your content strategy compared to competitors who are successfully ranking in AI results.

GEO Content Engine
Auto-publishing capabilities ensure consistent, optimized content creation that feeds AI understanding without requiring developer resources.

Enterprise-Grade Guardrails
Built-in approval workflows and brand safety measures ensure all AI-optimized content maintains quality and brand consistency.

Proven Results

Backed by Y Combinator (YC X25) and running multiple paid pilots, Relixir's platform simulates thousands of buyer questions, flips AI rankings in under 30 days, and requires no developer lift. (Unlocking AI Power with Relixir)

Quarter-by-Quarter Action Plan

Q3 2025: Foundation Building

Month 1: Audit and Assessment

Conduct comprehensive AI visibility audit using tools like Am I on AI (Am I on AI Platform)
Analyze current schema markup implementation
Identify content gaps for conversational queries

Month 2: Schema Implementation

Deploy Organization schema for entity establishment
Add Product schema for all offerings
Implement FAQ schema for common questions

Month 3: Content Optimization

Restructure existing content for conversational queries
Create FAQ-style content sections
Optimize for entity relationships

Q4 2025: Scaling and Refinement

Month 4-5: Multi-Engine Optimization

Expand optimization beyond Google to include ChatGPT, Perplexity, and Gemini
Implement platform-specific optimization strategies
Begin competitive gap analysis

Month 6: Performance Monitoring

Establish AI visibility tracking across all platforms
Monitor traffic recovery and lead generation improvements
Refine strategies based on performance data

Q1 2026: Advanced AEO Implementation

Months 7-9: Automation and Scale

Implement automated content generation for AI optimization
Scale successful strategies across all content properties
Establish ongoing monitoring and optimization processes

The Future is AEO: Why This Shift Matters

Market Transformation

The AI in Marketing market is projected to grow from $20 billion in 2023 to $214 billion by 2033, reflecting a CAGR of 26.7%. This growth is driven by the fundamental shift in how users discover and consume information. (Top AEO Platforms 2025)

User Behavior Evolution

Approximately 13 million American adults were using AI for search in 2023, expected to rise to 90 million by 2027. This represents a fundamental shift in search behavior that businesses cannot ignore.

Competitive Advantage

Early adopters of AEO strategies are already seeing significant advantages:

17% increase in inbound leads within six weeks
Improved visibility across multiple AI platforms
Reduced dependence on traditional search traffic
Enhanced brand authority in AI-generated responses

Platform Integration

Apple's announcement that AI-native search engines like Perplexity and Claude will be integrated into Safari challenges Google's dominance and further accelerates the shift toward AI-powered search experiences. (Generative Engine Optimization Guide)

Implementation Roadmap: From SEO to AEO

Phase 1: Assessment and Planning (Weeks 1-2)

Current State Analysis
- Audit existing schema markup
- Assess AI visibility across platforms
- Identify content optimization opportunities
Competitive Analysis
- Analyze competitor AEO strategies
- Identify content gaps and opportunities
- Benchmark current AI visibility

Phase 2: Foundation Implementation (Weeks 3-6)

Technical Implementation
- Deploy comprehensive schema markup
- Optimize site structure for AI crawling
- Implement FAQ schema across key pages
Content Optimization
- Restructure content for conversational queries
- Create comprehensive FAQ sections
- Optimize for entity relationships

Phase 3: Multi-Platform Optimization (Weeks 7-10)

Platform-Specific Strategies
- Optimize for ChatGPT search results
- Target Perplexity citation opportunities
- Enhance Gemini entity recognition
Content Scaling
- Develop content templates for AEO
- Implement automated optimization processes
- Create ongoing content calendars

Phase 4: Monitoring and Refinement (Ongoing)

Performance Tracking
- Monitor AI visibility across platforms
- Track lead generation improvements
- Analyze traffic pattern changes
Continuous Optimization
- Refine strategies based on performance data
- Adapt to new AI platform updates
- Scale successful approaches

Measuring AEO Success: Beyond Traditional Metrics

New Success Metrics

Traditional SEO metrics like keyword rankings and organic traffic are becoming less relevant in the AEO era. (Metrics That Matter for AEO) New metrics include:

AI Visibility Score: Percentage of relevant queries where your brand appears in AI responses
Citation Frequency: How often AI engines cite your content as a source
Answer Ownership: Percentage of questions where your content provides the primary answer
Multi-Platform Presence: Visibility across ChatGPT, Perplexity, Gemini, and Google AI

ROI Measurement

Businesses implementing comprehensive AEO strategies report:

17% increase in inbound leads within six weeks
25-40% improvement in brand mention frequency
30-50% reduction in customer acquisition costs
Enhanced brand authority and thought leadership positioning

Technical Implementation Guide

Essential Schema Markup

Organization Schema

{  "@context": "https://schema.org",  "@type": "Organization",  "name": "Your Company Name",  "description": "Company description",  "url": "https://yourcompany.com",  "sameAs": [    "https://linkedin.com/company/yourcompany",    "https://twitter.com/yourcompany"  ]}

FAQ Schema Implementation
FAQPage schema directly feeds AI answer generation, making it crucial for AEO success. (Implementing AEO Schema Markup)

Content Structure Optimization

Question-Based Headings

Use natural language questions as H2 and H3 headings
Address common customer queries directly
Provide comprehensive answers in following paragraphs

Entity Relationship Mapping

Clearly define relationships between your company, products, and industry
Use consistent entity naming across all content
Link related entities within content

The Competitive Landscape: AEO Tools and Platforms

Leading AEO Platforms

The AEO tool landscape has evolved rapidly, with several platforms emerging to address different aspects of AI optimization. (Top AEO Tools 2025) Key players include:

Relixir: Comprehensive GEO platform with automated content generation and multi-engine optimization
SE Ranking: AI visibility tracking across multiple platforms
Am I on AI: Brand visibility monitoring for ChatGPT responses
AI Page Ready: Technical AI SEO audit capabilities

Platform Selection Criteria

When choosing an AEO platform, consider:

Multi-engine optimization capabilities
Automated content generation features
Competitive analysis tools
Integration with existing marketing stacks
Enterprise-grade security and approval workflows

Industry-Specific AEO Strategies

B2B SaaS Companies

B2B SaaS companies face unique AEO challenges and opportunities:

Complex product explanations require comprehensive FAQ coverage
Multiple buyer personas need different conversational approaches
Integration capabilities must be clearly communicated to AI systems
ROI and case study information should be structured for AI consumption

E-commerce Businesses

E-commerce sites benefit from:

Detailed product schema markup
Review and rating structured data
Inventory and pricing information optimization
Local business schema for physical locations

Content Publishers

Publishers should focus on:

Article schema implementation
Author entity establishment
Topic cluster optimization
Citation-worthy content creation

Common AEO Implementation Mistakes

Technical Mistakes

Incomplete Schema Implementation
- Missing required properties in schema markup
- Inconsistent entity naming across pages
- Failure to validate schema markup
Poor Content Structure
- Keyword-focused rather than answer-focused content
- Lack of conversational query optimization
- Missing FAQ sections

Strategic Mistakes

Single-Platform Focus
- Optimizing only for Google while ignoring ChatGPT, Perplexity, and other AI engines
- Failing to adapt strategies for different AI platforms
Neglecting Competitive Analysis
- Not understanding why competitors rank in AI results
- Missing content gap opportunities
- Failing to monitor competitive AEO strategies

Future Outlook: The Next Phase of Search Evolution

Emerging Trends

Several trends will shape the future of AEO:

Voice and Conversational Search Growth
As voice assistants become more sophisticated, conversational query optimization will become even more critical.

Multi-Modal AI Integration
Future AI engines will integrate text, image, and video content, requiring comprehensive multi-modal optimization strategies.

Real-Time Information Integration
AI engines will increasingly prioritize fresh, real-time information, making content freshness and update frequency more important.

Platform Evolution

AI search platforms continue evolving rapidly:

ChatGPT's search capabilities expand monthly
Google's AI Mode becomes more sophisticated
New AI search engines enter the market regularly
Integration with existing platforms deepens

Business Impact

The shift to AEO represents a fundamental change in how businesses approach digital marketing:

Traditional SEO budgets are being reallocated to AEO initiatives
Content strategies are being rebuilt around conversational queries
Technical teams are learning new optimization approaches
Marketing ROI measurement is evolving to include AI visibility metrics

Conclusion: Embracing the AEO Future

Google's 2024-2025 core updates have fundamentally transformed the search landscape, making Answer Engine Optimization not just an opportunity but a necessity for business survival. The timeline from August 2024 through June 2025 tells a clear story: traditional SEO strategies are becoming obsolete as AI-powered search experiences dominate user behavior.

The data is unambiguous—60% of Google searches ended without a click in 2024, and this trend is accelerating with Google's AI Mode launch and the broader adoption of generative AI engines. (Why AI Mode Will Replace Traditional Search) Businesses that fail to adapt to this new reality risk becoming invisible in an AI-dominated search landscape.

Relixir's GEO platform represents the cutting edge of this transformation, offering businesses the tools and strategies needed to thrive in the age of AI search. (Top AEO Platforms Comparison) With proven results showing 17% increases in inbound leads within six weeks and the backing of Y Combinator, Relixir is leading the migration from traditional SEO to comprehensive AEO strategies.

The quarter-by-quarter action plan outlined in this guide provides a roadmap for businesses ready to make this critical transition. From foundation building through advanced multi-platform optimization, the path forward is clear: embrace

Frequently Asked Questions

What is the difference between SEO and AEO in 2025?

AEO (Answer Engine Optimization) focuses on optimizing content for AI-powered search experiences like Google's AI Mode, ChatGPT, and Perplexity, while traditional SEO targets blue-link rankings. AEO prioritizes entity understanding, structured data, and content that AI models can synthesize and cite in conversational responses rather than just ranking for keywords.

How has Google's AI Mode changed search results in 2025?

Google's AI Mode, launched as a Search Labs experiment in March 2025, provides an end-to-end AI search experience similar to ChatGPT. It eliminates the traditional 10 blue links format, instead offering conversational responses with citations and mentions. This shift means websites lose control over first-click experiences and receive fewer direct visits from search results.

What is Generative Engine Optimization (GEO) and why does it matter?

GEO is a modern digital strategy that enhances content visibility within AI-driven platforms like ChatGPT, Claude, Gemini, and Perplexity. Unlike traditional SEO, GEO ensures content is recognized and utilized by large language models that synthesize, remember, and reason with information. With the SEO market worth over $80 billion, GEO represents the evolution needed to maintain visibility in AI-first search environments.

How can I implement AEO schema markup for my B2B SaaS in 2025?

According to Relixir's technical checklist, implementing AEO schema markup involves adding structured data that AI engines can easily parse and understand. This includes entity markup, FAQ schema, article schema with proper publish dates, and ensuring your robots.txt and sitemaps are optimized for AI crawlers. The goal is to make your content more discoverable and citable by AI systems.

What metrics should I track for Answer Engine Optimization success?

Beyond traditional share of voice metrics, AEO success requires tracking AI visibility across multiple platforms including Google AI Overviews, ChatGPT responses, Perplexity citations, and Claude mentions. Key metrics include citation frequency, brand mention sentiment in AI responses, competitive AI presence analysis, and tracking how often your content appears in AI-generated answers across different query types.

How do I conduct competitive audits for AI SERP optimization?

Competitive audits for generative search should examine content structure and format, comprehensiveness, tone and readability, keyword and topic gap analysis, and SERP feature presence tracking. The goal is to understand why AI systems favor certain content over others and optimize accordingly. This includes analyzing how competitors appear in AI responses and what content patterns lead to higher citation rates.

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