With SearchGPT transforming the landscape of search engines by combining powerful generative AI with traditional search, digital marketers must rethink their SEO strategies. Unlike traditional keyword-based search engines, SearchGPT emphasizes natural language processing (NLP) and conversational content. To optimize for SearchGPT, your content must clearly answer complete questions, adopt a conversational tone, and be technically structured for AI crawlers. This involves prioritizing comprehensive answers, clear metadata, structured data (schema.org markup), fast website performance, and ensuring easy crawler accessibility.

Let's dive deeper into how to effectively optimize your content specifically for SearchGPT.

Understanding SearchGPT and its SEO Requirements

SearchGPT is OpenAI’s innovative search engine designed to deliver direct, conversational answers using generative AI technologies. Traditional keyword-based SEO alone won’t work here—you’ll need strategies tailored specifically for conversational search.

Essential SEO Practices for SearchGPT

Create Conversational, Comprehensive Content

SearchGPT understands context, natural language, and user intent better than traditional search engines. To rank well, your content needs to align closely with natural conversational patterns.

Best practices:

• Structure content around full questions and complete answers.
• Integrate conversational keywords and phrases.
• Create detailed, authoritative answers that directly address user intent.

For example, instead of targeting "SEO tips," optimize for phrases like "How can I optimize content for SearchGPT?" or "What's the best way to rank content on SearchGPT?"

Personal Insight:

In my experience, diversifying your content formats significantly improves SEO outcomes. Rather than relying solely on written blogs, incorporating videos, podcasts, or infographics ensures broader appeal and higher engagement, aligning perfectly with the conversational nature of SearchGPT.

Technical Optimization for AI Crawlers

SearchGPT relies heavily on technical structure, as its AI crawlers differ from traditional bots.

Key technical SEO factors include:

• Clean, structured HTML or Markdown: SearchGPT has limited JavaScript crawling capabilities, so a logical HTML structure ensures complete indexing.
• Metadata: Clear titles, descriptions, and publication dates help SearchGPT quickly evaluate content relevance.
• Optimized response times: Ensure your website loads quickly—AI crawlers have strict timeout constraints (usually 1-5 seconds).

Structured Data and Metadata

Implementing schema.org markup helps SearchGPT precisely interpret content, improving its ability to serve your content directly to users.

Recommended structured data includes:

• Article markup (title, author, publication date)
• FAQs markup (clearly marking questions and concise answers)
• Product or service details (price, availability, reviews)

Building Authority Through Backlinks

Backlinks remain essential, signaling credibility to SearchGPT’s AI-driven algorithms.

Effective link-building strategies include:

• Creating exceptional, shareable content.
• Establishing collaborations and partnerships with authoritative sites.
• Actively seeking editorial links from reputable sources.

FAQs: Optimizing for AI and Traditional Search

How to rank on Bing search engine?

Since SearchGPT reportedly uses Bing’s index, optimizing for Bing can significantly enhance your SearchGPT visibility:

• Prioritize strong domain authority and quality backlinks.
• Optimize content with clearly structured metadata and schema markup.
• Focus on user experience metrics like page load speed and user engagement signals.

How to rank on ChatGPT?

ChatGPT prioritizes direct answers from credible, structured sources:

• Provide concise, direct answers to common user queries.
• Include Q&A structures explicitly.
• Ensure your content is easily summarized by AI models.

How to optimise for SearchGPT?

• Create conversational, Q&A-style content.
• Ensure fast load times and structured HTML.
• Implement schema.org markup to clarify content type.
• Provide transparent and verifiable source citations.

Future-Proofing SEO Strategies for AI Search

AI-driven search engines like SearchGPT will continue evolving rapidly. Traditional metrics like keyword rankings will become less relevant. Instead, monitor engagement metrics such as session duration, direct engagement with content, and your site’s ability to clearly answer user queries.

Actions for continuous optimization:

• Regularly update your content based on performance metrics.
• Stay informed about AI search trends and algorithm updates.
• Adopt a test-and-learn approach, continuously adjusting your strategy.

Final Thoughts

Optimizing for SearchGPT requires thoughtful adjustments from traditional SEO, emphasizing conversational content, technical excellence, and structured data implementation. As SearchGPT continues to evolve, adopting flexible and AI-aligned SEO strategies ensures your content remains visible and valuable—effectively meeting both AI algorithms’ expectations and your users’ evolving needs.

The takeaway? Focus on user value, structure for clarity, and adapt continuously to maintain SEO success in the age of AI-powered search.

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The Truth About Backlinks in 2025: What Actually Works

Backlinking seems to be this black art in SEO that everybody either doesn't understand or is suspiciously quiet about. The truth is that backlinks are still very relevant in today's SEO strategy – and they absolutely should be.

Why Backlinks Still Matter

Fundamentally, backlinks are Google's way to verify whether you're trustworthy. When other websites link to yours, they're essentially vouching for you. This makes perfect sense as an important ranking metric – the more sites that trust you, the better your content probably is, so the higher you should rank. In competitive niches, if you don't have a clear backlinking strategy, good luck getting anywhere.

The Reality of Google's Stance

Google states they don't condone buying backlinks, which sounds nice on paper, but reality tells a different story. If buying backlinks didn't work, the backlinking industry wouldn't be worth billions of dollars. Services like The Hoth, Get Me Links, Rhino Rank, plus thousands of Fiverr gigs wouldn't exist. Backlinks work, and buying them (if you know what you're doing) absolutely works too.

How to Actually Get Backlinks in 2025

The "Write Great Content" Myth

Google likes to sound like a Boy Scout by saying "just write valuable content and the links will come." Sometimes this works, but mostly it's bullshit. Great content alone rarely attracts backlinks naturally.

Manual Outreach

One legitimate approach is manually reaching out to websites, saying: "Hey, I noticed you discuss X topic. I've written a detailed post about that – linking to my article would add value to your readers." This is how Google wants you to do it, but it rarely works well and requires massive manpower to implement effectively.

Featured.com and Expert Platforms

A quicker solution without spending money is using sites like Featured.com. These platforms connect publications with subject matter experts. Featured.com lets you browse questions from publishers looking for expert answers. If you provide great answers, you'll be rewarded with a backlink to your website. The free tier allows three questions monthly, though only one or two might get published due to competition.

Create Interactive Content

Building fun, useful content can attract backlinks naturally. Free tools are particularly effective. On our website, we have a free keyword research tool created specifically to drive traffic and generate backlinks. Yours doesn't need to be as sophisticated – if you sell jewelry, a simple ring size calculator could work. These tools can bring in high-quality backlinks with minimal effort.

Buying Backlinks

You can simply buy backlinks through services like The Hoth or Rhino Rank. But you need to know what you're doing – specifically how to analyze what makes a good versus bad backlink:

• Is it contextually relevant? A dog training website getting links from computer gear sites makes little sense.
• Do you want a guest post or link insertion?
• What about domain authority?

Speaking of domain authority, this metric is somewhat made up. Yes, Google has its own internal domain ranking system, but we don't know it. The domain authority scores from Ahrefs or SEMrush are their own metrics that may not match Google's evaluation.

Generally, look for websites with consistent backlink growth and organic traffic increases rather than fixating on a specific domain authority number. If they've had relatively steady growth and have a higher domain authority than yours (despite what I just said about these metrics), it's probably a decent backlink.

What If You're Clueless But Need Backlinks?

If you don't know what you're doing but need backlinks and lack time, I personally recommend GetMeLinks. Full disclosure: I know these guys and have worked with them extensively.

Unlike The Hoth or RhinoRank, Get Me Links offers human interaction without requiring huge budgets. You can schedule a 15-minute call to discuss strategy, making it a collaborative process. They provide monthly reports showing what backlinks they've secured, and regular meetings keep you involved in the strategy.

Do You Actually Need a Backlinking Strategy?

It depends on your niche's competitiveness. In the wedding industry in Sydney, Australia? You'll need serious backlinks to rank well in such a competitive space with established players. Your options are spending on backlinks or Google Ads – either way, your wallet will feel it.

But if you're a dog trainer in a small Idaho town with only one competitor, you can probably rank without an extensive backlink strategy.

I hope this has been valuable. If you want a full video tutorial on building backlinks yourself, check out my recent guide linked below.

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Leveraging AI for Keyword Research in 2025: A Smart Approach

I think by now, you probably know or feel that if you're not using AI to leverage nearly every aspect of your work, you're really missing out. And keyword research is no exception. In fact, I'd take it a step further and say that using AI for keyword research can really give you the edge and is something you should be doing today.

Why We Need Keyword Research

First off, let's understand why keyword research is fundamental. There are a few key problems that proper keyword research solves for us:

Finding the Right Keywords

Keyword research facilitates choosing the correct terms to focus on.

For example, we might think our audience is looking for "Professional dog training services," but when we do a little keyword research, we discover golden opportunities like "canine training services," which has nearly the same search volume but significantly lower competition. This allows us to get more bang for our buck with the work we do.

Matching User Intent

We need to ensure that the keywords on our pages actually match what users are searching for.

Consider this: if we're a SaaS company offering project management software, we might use terms like "project management software" or "professional SaaS project management software" on our page. But users might actually be searching for "office work task manager" or "office work task tracker tool."

These might seem like odd keyword choices, but if that's how your audience searches, you need to understand that through keyword research. It's all about how your potential audience is searching for your products or services.

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Maximizing Keyword Research with AI

I hear this question a lot:

"Can I do keyword research with ChatGPT?" Or "Can you do keyword research with any AI tool?"

The answer is yes and no. You can do keyword research, or better yet, you can do keyword idea research with ChatGPT. We need to understand that fundamentally, GPT, Claude, and Gemini don't have access to keyword research data such as search volume, keyword difficulty, cost per click, and other metrics—so they won't give you that data.

What these models will give you is a really good idea of potential keywords to explore, which you can then verify have sufficient search volume. I prefer to use large language models as a way to organize keyword research into an easy-to-follow, step-by-step strategy.

The Problem with Traditional Keyword Research

Many people get stuck at the data collection stage. They're happy they purchased Ahrefs or SEMrush, they do loads of keyword research, and then... what next? That's where they get stuck.

How do you implement keyword research into a strategy? That's where large language models come into play.

A Practical Approach to AI-Powered Keyword Research

Step 1: Use AI Models to Generate Keyword Ideas

Before diving into data collection, start with AI to brainstorm potential keywords. This is where models like ChatGPT, Claude, or Gemini shine. You can prompt them with questions like:

"What keywords might someone use when looking for [your product/service]?""Generate alternative ways to describe [your offering]""What are niche-specific terms related to [your industry]?"

These models have been trained on vast amounts of internet content and can suggest terminology you might not have considered. For example, if you run a fitness studio, beyond obvious terms like "gym" or "fitness center," an AI might suggest "functional training space," "boutique workout studio," or "group exercise classes near me."

The key here is to cast a wide net and collect as many potential keyword ideas as possible without worrying about metrics yet.

Step 2: Gather Data to Validate Your Keywords

Now that you have a robust list of potential keywords, it's time to validate them with actual data.

You can use tools like Ahrefs, but lately, I'm preferring Data for SEO's API because they make things more affordable while maintaining high quality. I'll show you a video below where I demonstrate an automation that gets all the keyword research you need absolutely free, as Data for SEO is giving everyone (or at least my followers) $5 of free API credit, which is more than enough for what you need.

This step is crucial because it tells you which of your AI-generated keyword ideas actually have search volume, how competitive they are, and what their potential value might be.

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Step 3: Make Sense of the Data

Once you have your data set, you need to make sense of it all. This is where large reasoning models come into play.

By giving the model background on what it's supposed to do with the keywords, it can transform the keyword "mumbo jumbo numbers" into actionable insights. Here's how:

1. Give the large language model an understanding and background of the business it's working for (context)
2. Provide it with your keyword research
3. Ask it to tell you how to implement these keywords on your website

You can then have a productive back-and-forth conversation with the model. It might tell you how to better optimize your on-page SEO by integrating one keyword instead of another, because it now has the correct data to make a data-driven approach.

Summary: The AI Keyword Research Process

So fundamentally, we're using AI for three key purposes:

1. Generate keyword ideas: Use large language models to brainstorm potential keywords without worrying about metrics
2. Get data for those keywords: Use tools like Data for SEO to validate these keywords with actual search volumes, difficulty scores, and other metrics
3. Organize and interpret the data: Feed that data back to reasoning models like OpenAI's GPT-4.5 or Claude 3.7 to organize and make sense of it all

Let the AI do the heavy lifting for you. That's the best way to do keyword research with AI in 2025.

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