New Update on AI-based Search Engine Algorithm: What is Semantic Search?

By Anupam Chatterjee, Digital Marketing Professional

In the ever-evolving world of digital marketing, search engines are rapidly shifting from keyword-based matching to understanding the intent and context behind queries.

This transformation is driven by semantic search, a cutting-edge technology that uses artificial intelligence (AI) to improve search relevance and accuracy.

Let's dig deep into semantic search and why it’s a game-changer.

What is Semantic Search?

Semantic search is a process where search engines use AI to understand the meaning of a query, considering factors like user intent, query context, and relationships between words. Unlike traditional keyword-based searches, which rely on literal matches, semantic search delivers results that answer the "why" behind a user's question.

For example, when you type, “Best way to reduce screen time for kids,” semantic search looks beyond the keywords and understands that you’re seeking actionable tips for improving children's habits, not just generic information about screens.

How Does Semantic Search Work?

Semantic search algorithms are powered by technologies like:

• Natural Language Processing (NLP): Helps search engines interpret conversational language.
• Knowledge Graphs: Networks of interconnected data points to provide factually rich answers. Google’s Knowledge Graph, for instance, contains over 500 billion facts about 5 billion entities. Machine Learning (ML) Continuously improves the system's understanding of user behavior and intent.

Why is Semantic Search Important?

The modern user expects accurate, context-driven results instantly.

With over 8.5 billion Google searches daily, semantic search ensures that users are matched with the most relevant content, improving satisfaction and trust in search engines.

Semantic Search in Action!

1. Voice Search: Queries like “Who’s the president of the US?” or “What’s his age?” asked consecutively will yield relevant answers because semantic search understands "his" refers to the previous query’s subject.
2. E-commerce Recommendations: Searching for “affordable ergonomic chairs” on Amazon triggers semantic search, which filters results by cost and comfort without explicitly specifying these as separate filters.

Impact on Digital Marketing

For professionals like us, semantic search has made optimization more challenging yet rewarding. Here’s how to adapt:

• Focus on Content Depth: Writing contextually rich, value-driven content is key.
• Use Structured Data Markup: This helps search engines understand the relationships within your site.
• Analyze User Intent: Tools like Google Analytics or SEMrush help you discover what users really seek.

Quick Facts and Future Insights

• Semantic search contributes significantly to Google's AI-based updates like BERT (2019) and MUM (2021), which enhanced its ability to understand the nuances of language.
• In 2023, Google introduced SGE (Search Generative Experience), blending semantic search with AI-generated summaries for faster insights.
• By 2026, global businesses using AI in search optimization are projected to save up to $3 billion annually in operational costs.

**The Semantic search bridges the gap between user expectations and machine capabilities. For marketers, this means creating empathetic, audience-centric strategies that resonate not just with algorithms but with people.

Are you optimizing for semantic search? If not, now is the time to realign your strategies and stay ahead of the curve.