How To Maintain Brand Visibility And Thrive In This Evolving Search Landscape

SEO

By Chris Barnhart Last updated Aug 26, 2024

0

Share

As of July 2024, ChatGPT had approximately 2.9 billion monthly visits, compared to Google’s 130.1 billion, Facebook’s 13.2 Billion, X’s 4.1 billion, and Amazon’s 3.2 billion.

While ChatGPT’s monthly visits might seem like peanuts in comparison, it has built a strong user base in months and will likely continue to dominate as AI search gains popularity.

Similarly, we’re seeing these major search engines and social media platforms incorporate generative AI into the user experience.

What does this mean for your customers and prospects? Consumers can use new and existing platforms to interact with your content in a more natural conversation style.

They can ask questions, build on ideas, and get answers without leaving the interface.

So, how can brands maintain their visibility on these platforms and control how their content is understood in the face of generative AI? The answer boils down to three things:

• Investing in great content.
• Developing a content knowledge graph.
• Having a growth mindset.

Together, these three pillars will ensure that people and machines understand your brand and content, enabling your team to thrive in this new world of generative AI search.

Let’s start with content.

Investing In Great Content

Over the last two years, we’ve seen Google place heavy emphasis on “Helpful, reliable, people-first content.”

This means creating helpful, reliable content that focuses primarily on your audience’s needs – not the search engines.

While this seems logical, it’s a big shift from the old way of developing website content for search engines.

Your content should seek to provide a comprehensive answer to your audience’s questions, address any additional information they might need to know, and demonstrate your brand’s first-hand expertise or experience in the topic.

I love how people-first content brings us back to content as a service. Your content answers questions, helps make decisions, points people in the right direction, and delights them.

For brands to thrive in this new age of AI, they must continue to invest in great content. This requires your team to take the time to understand your audience and their changing needs, find gaps in your current content strategy, and iterate on existing content to continue delighting your audience.

Apart from investing and evolving your website content to delight your audience, you must also ensure that search engines, AI, and other machines can easily understand your content and infer answers from your data.

You can do this by implementing advanced schema markup on your site to develop a content knowledge graph.

Developing A Content Knowledge Graph

Earlier this year, Gartner published its research on the 30 Emerging Technologies That Will Guide Your Business Decisions in 2024.

It identified generative AI and knowledge graphs as two emerging technologies organizations should start investing in to be ready to utilize when they mature. While generative AI has gained widespread popularity through its productivity potential, knowledge graphs remain less well-known.

A knowledge graph is a collection of relationships between things defined using a standardized vocabulary, from which new knowledge can be gained through inferencing.

In fact, Google and Microsoft have been using knowledge graphs to generate knowledge panels and infer answers in search since 2010.

Many research papers, including the article Unifying Large Language Models and Knowledge Graphs: A Roadmap, explain that knowledge graphs “can enhance LLMs by providing external knowledge for inference and interpretability.” Hence reducing the risk of hallucinations in LLMs.

Content knowledge graphs, similar to a knowledge graph, are collections of relationships between entities on your website. Many digital marketing organizations have invested in building content knowledge graphs for their web data by implementing advanced schema markup (aka structured data).

Schema markup, also known as structured data, is machine-readable data that helps search engines understand the content on a page and show the content as a rich result on the search engine result page. However, the value of schema markup goes beyond that.

Your website content is filled with entities about your business – for example, your location, your employees, your products, etc.