DeepSeek R1 vs. OpenAI O1: The Open-Source Underdog Takes on the AI Giant
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DeepSeek R1 vs. OpenAI O1: The Open-Source Underdog Takes on the AI Giant
(And Why This Battle Matters for the Future of AI)
The AI world is buzzing with the release of DeepSeek R1, a new open-source language model that’s challenging OpenAI’s flagship O1 in performance—but at a fraction of the cost. Think of it as a David vs. Goliath story, but with neural networks and math benchmarks instead of slingshots. Let’s unpack why this rivalry is reshaping the AI landscape.
The Contenders: Meet the Models
DeepSeek R1 (GitHub) is the brainchild of Chinese AI startup DeepSeek, built on their earlier DeepSeek-V3 architecture. Unlike traditional models that rely heavily on supervised fine-tuning (SFT), R1 was trained using large-scale reinforcement learning (RL) with minimal human-labeled data. This approach allowed it to “self-evolve” reasoning capabilities, like solving complex math problems through trial and error28.
OpenAI O1, on the other hand, is a proprietary model optimized for reasoning tasks. It uses a hybrid approach combining SFT and RL, backed by OpenAI’s massive resources. While exact details are scarce (it is closed-source, after all), O1 has set high benchmarks in coding, math, and general knowledge tasks16.
Head-to-Head: Performance & Cost
Let’s cut to the chase: How do they stack up? Here’s a snapshot of their benchmark scores and costs:
Benchmark | DeepSeek R1 | OpenAI O1 | Winner |
---|---|---|---|
AIME 2024 (Math) | 79.8% | 79.2% | DeepSeek R1 |
MATH-500 (Reasoning) | 97.3% | 96.4% | DeepSeek R1 |
Codeforces (Coding) | 96.3%ile | 96.6%ile | OpenAI O1 |
MMLU (General Knowledge) | 90.8% | 91.8% | OpenAI O1 |
Cost per 1M tokens | $0.55 (input) | $15 (input) | DeepSeek R1 (95% cheaper) |
R1 shines in math and software engineering, while O1 edges ahead in coding competitions and general knowledge. But the real kicker? R1’s API costs just 5% of O1’s—a game-changer for startups and researchers8.
Why Open-Source Matters
DeepSeek R1 isn’t just a model—it’s a statement. By open-sourcing R1 under an MIT license, DeepSeek invites developers to tweak, refine, and build upon its architecture. Need a smaller, faster version? They’ve already distilled R1 into six variants (like Qwen-32B and Llama-70B) that outperform even GPT-4o in niche tasks28.
Compare this to OpenAI’s “walled garden” approach. While O1 offers polished performance, its closed nature limits customization and transparency. For example, DeepSeek R1’s training pipeline—revealed in its technical report—shows how RL can replace costly SFT data, a breakthrough for resource-strapped teams68.
The Bigger Picture: What This Means for AI
- Democratizing AI Innovation:
R1’s affordability and accessibility lower the barrier to entry. A solo developer can now experiment with a model rivaling O1’s capabilities—something unheard of in the billion-dollar AI race810. - Ethical Trade-Offs:
Open-source models like R1 raise concerns about misuse (e.g., generating harmful content), but they also enable scrutiny. Proprietary models, while “safer,” operate in opacity510. - The Efficiency Revolution:
DeepSeek trained R1 on a $6 million budget—a fraction of what OpenAI likely spent. This proves that smart resource allocation (like RL-driven training) can rival Big Tech’s brute-force spending16.
Should You Switch to DeepSeek R1?
- For math/logic-heavy tasks: Yes. R1’s Chain-of-Thought reasoning excels here.
- For general-purpose chatbots: OpenAI O1 still leads, but R1’s distilled models are catching up.
- For budget-conscious projects: R1 is a no-brainer. At 95% lower costs, it’s ideal for prototyping18.
Try R1 yourself on DeepSeek’s chat platform (look for the “DeepThink” mode) or via its Hugging Face integration.

Personal Experience With R1: A Human Touch in AI Writing?
(Spoiler: I’m stealing this paragraph for my productivity newsletter)
I’ve been stress-testing DeepSeek R1 for the past few hours – coding Python scripts, drafting research summaries, and yes, even writing this blog section. What surprised me most wasn’t its math chops (though those are stellar), but how human its SEO copywriting felt.
When generating article drafts, most AI models make me feel like an editor battling robotic phrasing (“In conclusion, this revolutionary technology synergizes paradigm shifts!”). With R1, I simply added:
“Ensure the content is concise, flows naturally, and feels like an easy, relatable read.”
The result? Paragraphs that sounded like a colleague wrote them, not ChatGPT’s overly enthusiastic cousin. For coding tasks, it aced Python error debugging with clearer explanations than I’d get from Stack Overflow.
Why this matters: R1’s ability to grasp nuanced writing styles with minimal prompting (see their style guide tips) suggests open-source models are closing the “personality gap” that kept many businesses wary of AI content.
Final Thoughts
The DeepSeek R1 vs. OpenAI O1 rivalry isn’t just about benchmarks—it’s a clash of philosophies. Will open-source, community-driven AI overtake proprietary giants? Early signs suggest yes. As one researcher put it: “R1 proves innovation thrives when knowledge is shared, not siloed.”

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Generative Engine Optimization: What It Is and Why It Matters for Your Strategy in 2025
Have you noticed how AI search tools are changing the way we find information online? In recent years, tools like ChatGPT and Google’s new search experience have reshaped our approach to finding answers, and a new technique called Generative Engine Optimization (GEO) is quickly making its mark. If you’re running a business, a blog, or an online store, it’s time to check out GEO and see how it can slide into your overall plan—kind of like that unexpected bonus in your paycheck.
In this post, we’re going to cover several important topics:
- What is GEO?
- Is GEO replacing traditional SEO?
- How can you optimize for generative AI searches?
- What are the key differences between SEO and GEO?
I’ll also share some practical steps you can implement today, along with a personal story that shows how diversifying your content can help you compete even against sites with a much higher domain authority. So, grab a cup of coffee, and let’s get rolling!
What Is Generative Engine Optimization (GEO)?
Generative Engine Optimization is all about making sure your content is structured and written so that AI-powered search engines pick it up and use it to answer users’ questions. Unlike traditional SEO—where you focus on ranking among a list of search results—GEO is designed to have your content included as part of a generated answer when someone asks a question. Think of it as giving the AI a cheat sheet that highlights your best bits.
When someone types a query into an AI search tool or speaks to a voice assistant, the response often comes as a friendly, conversational answer rather than a list of links. GEO means adjusting your content so that it’s clear, organized, and useful for these smart systems. For example, if your site explains how to fix a leaky faucet, the AI might grab that explanation and show it directly to the user without the extra step of clicking through. If you’re curious about how these systems work, check out Google’s SGE guidelines for a peek under the hood.
Here is an example comparing the same search term, but using traditional a Search Engine and AI powered search.
Traditional Search

AI Powered Search Engine

At its core, GEO means:
- Writing in a clear, conversational tone.
- Breaking your content into sections with descriptive headings.
- Answering specific questions directly on the page.
- Using structured data (schema markup) to help the AI understand your content.
The goal here is to have your page recognized as the best source for answering a particular question. When an AI sees that your article clearly explains “What is generative engine optimization?” or “How do I optimize for AI searches?”, it might include your content as part of its answer. This doesn’t mean you lose all the benefits of traditional SEO—instead, GEO adds another shiny channel to your overall visibility toolbox.
Is GEO Replacing Traditional SEO?
Not at all. Traditional SEO is still the bread and butter of online visibility. You still need to keep your site well-structured, fast, and packed with valuable content. GEO simply offers an extra avenue to get your content seen—especially by those increasingly chatty AI-powered search engines.
Consider this: Traditional SEO is all about ranking high on search engine results pages (SERPs), where users click through a list of links. GEO, on the other hand, is about ensuring that your content is chosen by AI as the answer to a query. With AI providing conversational responses, your content might be delivered directly to the user, even if they never click through. While this may mean fewer clicks from classic search, your brand still gets prime exposure.
For a deeper look into how this shift is changing traffic patterns, check out this analysis of AI search impact. Research shows that even if click-through rates dip, being part of the AI’s answer can boost trust and brand recognition. So, GEO isn’t replacing SEO—it’s just adding a fresh twist to how you connect with your audience. And yes, even your mom will notice your brand’s name in those friendly AI responses!
How to Optimize for Generative AI Searches
Alright, let’s roll up our sleeves and get into the nitty-gritty. Here are some practical, no-nonsense steps you can start using today to prepare your content for the brave new world of AI-driven search.
1. Write Clear and Direct Content
When writing, aim for clarity and simplicity. Use headings that clearly mark the sections, and keep your paragraphs short and sweet. This helps AI systems quickly pick up your main ideas. For example, if your article answers a specific question, include that direct answer right at the start—kind of like the TL;DR of your page.
2. Use Structured Data
Structured data is a way to tell search engines exactly what your content is about. Adding schema markup (like FAQPage or Article schema) makes it easier for AI to find the key information. If you’re curious about how to do this, check out Google’s schema guidelines. This is especially useful if you run a local business or an online store where details like opening hours, product specs, and reviews need to be crystal clear.
3. Include Q&A Sections
Since many users now ask questions directly to AI search tools, having a dedicated Q&A or FAQ section on your page can be a real game-changer. Answer common questions in a clear, conversational tone, and you increase your chances of being featured as the answer. For instance, if you have an article titled “How to Fix a Leaky Faucet,” add a section with questions like “What tools do I need?” and “How do I locate the leak?” along with concise answers. The more directly you answer, the better your odds.
4. Make Your Content Easy to Scan
Use bullet points, numbered lists, and short paragraphs to break up your content. Not only does this help human readers, but it also allows AI to quickly extract the key points. Here’s a quick table to show how different content elements help with GEO:
Content Element | Purpose for GEO |
---|---|
Headings & Subheadings | Signal the main topics and organize your content |
Bullet Points | Break down important steps or lists into digestible bits |
FAQ Sections | Directly answer common questions that AI might use |
Structured Data | Provide clear signals about the content to AI systems |
5. Focus on Long-Tail Questions
Long-tail queries are those specific, detailed questions that users might ask an AI. They tend to be less competitive and can help you attract a niche audience. Instead of targeting a broad term like “SEO tips,” try something like “how to improve AI search visibility for small business blogs.” These longer queries might not bring a flood of traffic, but they can attract quality visitors who are looking for exactly what you offer.
I have already experimented with this and it works very well. I was recently typing a long-tail query into ChatGPT— “how to use deepseek r1 to write seo content that ranks”—and, one of my articles popped up as a top result. This happened even though a website with a much higher domain authority was also in the mix. That moment taught me that diversifying your content and optimizing for GEO can help you punch above your weight. Who knew that even a small fish can sometimes outswim a shark if it’s got the right moves?

6. Diversify Your Content Formats
It’s not just about text. Think about incorporating videos, infographics, and even podcasts into your mix. For example, a video that explains a process can be accompanied by a transcript or a detailed summary on your page. This extra bit of context makes it easier for AI to pick up the important details from your multimedia content.
One of my own videos did just that. I made sure it had a clear, engaging transcript on the page, and guess what? It started ranking well for a long-tail query—even outperforming a competitor with a way higher domain authority. This goes to show that when you offer a mix of content types and make each piece GEO-friendly, you can stand out in a big pond.
7. Keep Your Content Updated
AI systems love fresh content. Make it a habit to review and update your pages regularly to reflect the latest information, stats, and trends. Regular updates signal to both search engines and AI that your content is reliable and current. Think of it as giving your content a little spa day—everyone likes to feel refreshed now and then.
8. Build and Use a Consistent Brand Voice
A relaxed and conversational tone can help both your human readers and AI systems understand your content better. Write as if you’re chatting with a friend—simple, honest, and maybe even a tad cheeky. Avoid the overly technical jargon unless it’s absolutely necessary. Remember, your personality is your secret sauce, and it can help set you apart from the big guys.
9. Monitor Your Results
Keep an eye on your analytics to see how your content is performing. Look at where your traffic is coming from and how users interact with your pages. Some new tools even show you how often your content is featured in AI-generated answers. Use this data to tweak your strategy over time—after all, even the best chefs taste their dishes before serving them.
For more detailed tips on these tactics, you might want to check out this guide on SEO best practices, which is now evolving to include GEO factors.
Differences Between SEO and GEO
While both SEO and GEO aim to get your content seen by the right audience, they operate in slightly different realms. Here’s a quick breakdown of the key differences:
Aspect | Traditional SEO | Generative Engine Optimization (GEO) |
---|---|---|
Primary Goal | Ranking high on search engine results pages | Being chosen as the answer in AI-generated responses |
User Interaction | Users click on a list of links | Users receive a conversational answer without necessarily clicking |
Content Format | Detailed, keyword-rich pages | Clear, direct answers with structured content |
Measurement Metrics | Click-through rates and ranking position | Visibility within AI answers and share of voice in generated responses |
Optimization Techniques | Keyword research, link building, on-page tweaks | Structured data, FAQ sections, long-tail question targeting, and clear formatting |
This table shows how traditional SEO and GEO serve different purposes. Traditional SEO remains essential for overall visibility, but GEO specifically helps you capture those users who rely on AI to get their answers—making your content part of the conversation.
Actionable Advice for Boosting Your GEO
Let’s wrap up the actionable bits you can implement right now to boost your GEO:
- Audit Your Existing Content:
Go through your top pages and check if they answer common questions directly. Enhance or add FAQ sections and break up long paragraphs into shorter, easier-to-digest bits. - Implement Structured Data:
If you haven’t done so already, add schema markup to your pages. This helps AI systems quickly understand your content. Use tools like Google’s Rich Results Test to ensure everything’s working as it should. - Create Content for Long-Tail Queries:
Identify the detailed questions your target audience is asking. Write content that gives clear, direct answers. Long-tail keywords might not bring in a flood of traffic, but they deliver quality visitors who are looking for exactly what you offer. - Diversify Your Content Formats:
Mix up your content types—if you usually write articles, try adding videos, infographics, or podcasts. And don’t forget to include a text summary or transcript for each format. This not only helps with GEO but also caters to different learning styles. - Keep Your Brand Voice Consistent:
Write in a friendly, relaxed tone that reflects your personality. A little bit of humor goes a long way—like a wink in text form. It makes your content more engaging and memorable. - Monitor Your Performance:
Use analytics tools to track which pages are being picked up by AI systems. Keep an eye on changes in traffic patterns and user engagement. Adjust your strategy based on the data you gather, so your content always hits the mark. - Stay Updated:
The search landscape is constantly changing. Follow updates from Google’s Search Central or trusted industry blogs to keep your GEO strategy current.

A Personal Story: When Small Content Outranked the Big Guys
I have had experience with ranking for GEO and this particular case will show you how important GEO and Content Diversification is. A while back, I decided to test the waters with a long-tail query in ChatGPT: “How to use DeepSeek R1 To write SEO content that will rank?"I wasn’t expecting much. To my surprise, one of my videos popped up as a top result—even beating out a website with a much higher domain authority! As of the time of this recording, this site is sitting at a domain authority of 9 (it's still new), the competitor was at around 39.
This experience taught me three key lessons:
- Diversifying Your Content Works:
By offering a mix of videos, blog posts, and infographics, you give AI multiple pieces of your work to choose from. Even if one piece isn’t perfect, another might just hit the bullseye. - Quality and Clarity Win the Day:
My video did well because it was straightforward and answered the question clearly. I had spent time breaking down the topic into bite-sized, easy-to-understand sections, which turned out to be a real win in the AI-driven search world. - Small Can Outperform Big:
Even if you’re a small fish in a big pond, a well-optimized, focused piece of content can sometimes outswim the sharks. That day, it proved that diversifying your content and tailoring it for GEO can level the playing field. Who knew that with a bit of effort, you could make the big guys sweat?
This personal insight shows that GEO isn’t just a fancy buzzword—it’s a practical approach you can implement right away. With a few tweaks, even a small site can start competing with the industry giants.

Wrapping It All Up
Generative Engine Optimization is a fresh twist on traditional search strategies. While SEO remains crucial, GEO helps you get a spot in the answers that AI tools deliver directly to users. Whether you’re a local business, a blogger, or run an online store, adding GEO to your strategy can boost your visibility in today’s search environment.
To recap:
- GEO is about making your content friendly for AI search engines, ensuring that it’s picked as the answer when users ask questions.
- It doesn’t replace traditional SEO—it adds another way for your audience to find you.
- Optimizing for AI searches involves clear writing, structured data, dedicated FAQ sections, and targeting long-tail queries.
- A mix of content formats and a relaxed, conversational tone (with a sprinkle of humor) can help your content stand out.
- Real-world experience shows that even a smaller site can compete with larger ones if you diversify your content and optimize smartly.
By taking the actionable steps mentioned above, you can start seeing improvements in how your content is picked up by AI tools. Remember, it’s not just about chasing clicks—it’s about building trust and recognition in an AI-driven world.For those looking for additional tips on how to refine your approach, check out this guide on optimizing content for AI. It’s packed with useful insights and examples to help you get started.So, if you haven’t started considering GEO in your strategy yet, now’s the time. Try out some of these tips on your next piece of content and see how your visibility improves.
And hey, if you're feeling overwhelmed with GEO and SEO, consider joining our online community, the AI Ranking SKOOL. We help you simplify SEO and maximize it with AI and automations. Happy optimizing—and may your content always be the one that gets picked by the AI!

Generative Engine Optimization: What It Is and Why It Matters for 2025

Unlocking the Power of OpenAI’s Deep Research: A Comprehensive Guide
If you’re a small business owner or marketer looking to supercharge your SEO strategy, you might have heard about OpenAI’s new Deep Research feature. It promises to transform the way we perform online research, making it possible to generate in-depth, citation-rich reports that once took hours – or even days – to compile. In this post, we’ll break down exactly what Deep Research is, how it works, and address all the FAQs so you know how to leverage this innovative tool to elevate your content game.
What Is Deep Research?
In a nutshell, OpenAI’s Deep Research is a powerful extension of ChatGPT designed for autonomous, multi-step research tasks. Unlike standard queries where you get a quick answer, Deep Research dives deep into the public web, gathering, analyzing, and synthesizing information from hundreds of sources. It then delivers a detailed report complete with citations, effectively serving as your digital research assistant.
You can think of it as moving from a simple Google search to having a personal research analyst at your fingertips. Whether you’re looking to understand a niche topic or compile market data, Deep Research can handle the heavy lifting so you can focus on strategy and execution.
How Does Deep Research Work?
The Process
- Getting Started
Using Deep Research is straightforward. In the ChatGPT interface, you simply select the “Deep Research” option when composing your query. For instance, you might ask: “Give me a comprehensive analysis of the top marketing strategies for a new online boutique.”
Learn more about how to start your query.

- Setting the Parameters
Once your query is submitted, Deep Research may prompt you for some follow-up details to better focus the research. This ensures that the AI knows exactly what information you’re after. - Autonomous Research
After the initial setup, the AI embarks on its research journey. Over the course of 5 to 30 minutes, it sifts through numerous webpages, studies documents (including PDFs and images), and compiles a comprehensive report complete with hyperlinks to the original sources.
Discover more about the research process. - Presentation of Results
When the research is complete, you receive a detailed report with all the necessary information, including relevant citations. This report is ideal for content creation, competitive analysis, or even refreshing existing articles with the latest data.
Frequently Asked Questions About Deep Research
Let’s dive into the most commonly asked questions about Deep Research, addressing the concerns and curiosities that small business owners and marketers typically have.What Exactly Is Deep Research?Deep Research is a specialized tool within ChatGPT that performs in-depth, autonomous research by combing through publicly available information online. It’s designed to generate a comprehensive, well-cited report on any given topic. Whether you need detailed market analysis or a deep dive into a trending topic, this tool is built to handle complex research tasks that would otherwise require extensive manual effort.
Read about the tool’s capabilities on OpenAI’s site.
Who Can Use Deep Research, and Are There Any Limits?
As of now, Deep Research is available exclusively to ChatGPT Pro subscribers in eligible regions. Users in the UK, Switzerland, and the EEA might experience a delayed rollout, but the feature is expected to become more widely available over time. Pro users enjoy up to 100 Deep Research tasks per month, making it a scalable solution for businesses that need regular, in-depth research without the overhead of a dedicated research team.
Check out the latest subscription details.
How Do I Use Deep Research in ChatGPT?
Using Deep Research is as simple as choosing the option in the ChatGPT interface and entering your research query. You can provide extra context by attaching files or images, which the AI will then consider as part of its research. For example, if you need insights on “DIY marketing for small businesses in 2025,” you simply enter the query, set any parameters, and let Deep Research do its work.
Get started with Deep Research here.
How Is Deep Research Different from a Normal ChatGPT Query or Standard Search?
There’s a significant difference between Deep Research and the typical quick responses you get from a standard ChatGPT query. The normal mode is designed for immediate answers or simple fact-checking, drawing from a limited set of sources. In contrast, Deep Research is built for thoroughness. It searches through a vast number of sources to compile a detailed, multi-layered report with citations, making it invaluable for content that requires deep insights and extensive data validation.
Compare standard search vs. Deep Research.
How Long Does a Deep Research Task Take?
A Deep Research task can take anywhere from 5 to 30 minutes, depending on the complexity of the query. This delay is by design – the AI is working methodically, reading, and analyzing the content across multiple sources to ensure a comprehensive result. During this time, you can continue to work on other tasks, as the research process runs in the background. Once the task is complete, you’re notified, and your detailed report is ready for review. As an example, we used Deep Research to help us write this blog and it took around 4 minutes to provide us with in-depth research on this. Keep in mind this is a relatviely easy topic to search, more complex tasks might take 30 min.

Learn more about task timing.
Does Deep Research Provide Sources, and How Accurate Is It?
Yes, every Deep Research report comes with clearly cited sources. This is a game changer for verifying facts and building content that’s not only informative but also credible. However, while the AI strives for accuracy, it’s not infallible. There are instances where the tool might misinterpret data or combine information in unexpected ways. The citations allow you to verify the information directly from the source, ensuring that you can trust and cross-check the findings.
What Are the Limitations or Concerns?
Despite its many benefits, Deep Research does have some limitations:
- Public Data Only: The tool only accesses public information. It can’t retrieve data from private databases or subscription-based services unless you provide the data yourself.
- Time Factor: The research process is intentionally slower than a standard query because it’s gathering information from a wide array of sources.
- Potential for Inaccuracies: Like any AI, it might occasionally present incorrect or outdated information, which is why it’s important to review the citations and verify critical facts.
- Use Case Specificity: While fantastic for comprehensive reports and content research, it’s not designed for quick, on-the-spot queries during live discussions or meetings.
Explore known limitations here.
Practical Use Cases: Maximizing SEO and Content Creation With Deep Research
For small business owners and marketers, the practical applications of Deep Research are as exciting as they are numerous. Here’s how you can put this tool to work for your SEO and content strategy (It's also how I did research for this blog post .
Comprehensive Topic Research & Content Ideation
The Challenge: Crafting unique, authoritative content often requires extensive background research on a topic.
The Deep Research Solution: Instead of spending countless hours browsing multiple sites and pulling together data, use Deep Research to compile a detailed report on your topic. For example, if you’re creating content about “sustainable packaging for e-commerce,” you can instruct the tool to gather statistics, industry trends, expert opinions, and more. This comprehensive background will help you:
- Identify unique angles or insights that set your content apart.
- Ensure that your blog post or video script is well-supported by data.
- Enhance the overall quality and depth of your content, which is crucial for SEO.
See how deep research boosts content ideation.
SEO Content Planning and Keyword Research
The Challenge: Understanding what your target audience is searching for can be overwhelming without the right tools.
The Deep Research Solution: Use Deep Research to conduct advanced keyword and question research. Ask the tool to find common queries and topics that small business owners are interested in, such as “DIY marketing strategies for 2025” or “how to improve local SEO on a budget.” This approach not only gives you a list of high-potential keywords but also the context behind them – the actual questions and pain points your audience is expressing online. The result is a content plan built around real-world search queries, ensuring that your articles, videos, and FAQs address exactly what your audience wants to know. One thing to keep in mind is that OpenAI's Deep Research does not have direct access to keyword data like, monthly search volume, keyword difficulty etc, so you might want to combine the research provided with SEO Keyword Research tools like our own free tool or others from ahrefs, semrush etc.

Writing Data-Backed, Authoritative Content
The Challenge: Writing long-form content, like ultimate guides or whitepapers, can be daunting without thorough, reliable research.
The Deep Research Solution: Leverage Deep Research as your content research assistant. Suppose you’re working on “The Complete Guide to Email Marketing for Nonprofits.” Instead of manually scouring the internet for studies, expert quotes, and case studies, let Deep Research compile a report for you. This report will include:
- Data-backed insights.
- Relevant statistics and trends.
- Expert opinions with links to the original sources.
With this detailed research in hand, you can craft a more authoritative and persuasive piece that not only resonates with readers but also meets Google’s E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness) standards for SEO.
Competitor Analysis and Market Research
The Challenge: Keeping tabs on your competitors and market trends is essential but time-consuming.
The Deep Research Solution: Ask Deep Research to analyze your competitor’s content strategy or gather market insights. For example, you could query: “Analyze the online content strategy of [Competitor X] and compile customer feedback on their product.” The AI will gather information from news articles, reviews, and their published content, giving you a comprehensive overview of:
- What topics your competitor is focusing on.
- Their strengths and weaknesses.
- Opportunities for you to fill gaps in the market with your own content.
This kind of analysis can guide your strategy, helping you to craft content that addresses unmet needs and differentiates your brand in the competitive landscape.
Learn more about market research with AI.
Content Refresh & Fact-Checking
The Challenge: Keeping content up-to-date is critical for maintaining high search rankings and audience trust.
The Deep Research Solution: Use Deep Research as a periodic check-up tool for your existing content. If you have an older blog post, ask the AI to “Check the latest data on [your topic] since 2022.” It will compile recent findings and statistics, enabling you to refresh your content with new, accurate information. This approach not only helps maintain the authority of your site but also signals to search engines that your content is continually updated and relevant.
Understand how to refresh your content effectively.
Integrating Deep Research into Your Workflow
So, you might be wondering how to fit Deep Research into your daily routine without it becoming a time sink. Here are a few tips for seamless integration:
Prioritize High-Impact Projects
Focus on using Deep Research for projects where the depth of insight can make the biggest difference – such as cornerstone content, detailed market analysis, or comprehensive competitor studies. For day-to-day queries or quick facts, the regular ChatGPT mode or a standard search might be more efficient.
Combine AI with Human Oversight
While Deep Research provides an excellent starting point, it’s important to review and verify the information it provides. Use the citations to cross-check critical details, and add your own expertise and insights to polish the final output. Think of it as a collaborative process between AI and human creativity.
Experiment and Iterate
Like any new tool, there might be a learning curve with Deep Research. Experiment with different types of queries and parameters to see what yields the best results for your content needs. Over time, you’ll develop a sense of when to use Deep Research versus other tools in your content creation arsenal.
Looking Ahead: The Future of Deep Research in Content Creation
As AI continues to evolve, tools like Deep Research are poised to revolutionize how we approach content creation and SEO. For small business owners and marketers, this means:
- More Efficient Research: Spending less time gathering data and more time crafting compelling, value-driven content.
- Enhanced Content Quality: With comprehensive, data-backed research, your content will naturally become more authoritative and engaging.
- Competitive Advantage: Leveraging advanced AI research can give you insights that are hard for competitors to match, setting your brand apart in a crowded digital landscape.
There is no doubt that Deep Research is not a silver bullet. Its current limitations – such as only accessing public data and requiring a bit more time for results – mean that it works best as a supplement to your overall strategy. However, as it continues to improve and become more widely available, its role in transforming content marketing will only grow.
Let's Wrap this up
OpenAI’s Deep Research is a groundbreaking tool that offers an exciting glimpse into the future of AI-driven content creation. For those who need detailed, well-cited research in a fraction of the time it would take manually, it’s a game changer. By understanding how it works, knowing its limitations, and learning how to integrate it effectively into your workflow, you can unlock a new level of efficiency and creativity in your marketing efforts.Whether you’re using it to brainstorm fresh content ideas, conduct competitive analysis, or simply verify that your data is up-to-date, Deep Research is designed to be a trusted partner in your content strategy. Remember, while the AI does the heavy lifting, your expertise in interpreting and refining the results is what ultimately makes your content shine.
P.S For a look into how to use Deep Research to write very high quality seo blog posts, take a look at our video below

OpenAI’s Deep Research: A Comprehensive Guide

SEO (Search Engine Optimization) can be tedious and time-consuming, but it doesn’t have to be. With the right strategy, you can automate a large portion of your SEO processes and harness the power of AI to lighten the load. In this post, we’ll explore which parts of SEO can (and should) be automated, what tools you’ll need, and how to strategically incorporate AI for data-driven decisions. We’ll also discuss how to keep your content high-quality so Google doesn’t penalize you and—most importantly—how to supercharge your content output without losing your unique voice and expertise.
Whether you’re new to automation or a seasoned marketer looking to refine your workflow, this guide will walk you through the essentials, step by step. Let’s dive in.
Why Automate Your SEO (and What Not to Automate)
We all know SEO can sometimes feel overwhelming. From keyword research and competitor analysis to backlink building and content creation, it’s easy to get bogged down in repetitive tasks. That’s why automation is so powerful: it frees you up from mundane “busy work” and lets you focus on creativity, strategy, and big-picture thinking.
However, not all SEO tasks should be automated. Some areas, like refining your brand voice or adding your personal expertise to the content, are best done by a human hand. Google continues to value content that reflects real-life experience, in-depth knowledge, and genuine insight—attributes that automated systems alone can’t fully replicate.
So the guiding principle here is: Automate the time-consuming parts, and keep the human element where it truly matters.
Key Tools and Platforms For SEO Automations
Before we get into the specifics of automations, it’s important to get your toolkit in order. Below are the key platforms and tools you’ll likely need.
Automation Platforms

Make
Make (formerly Integromat) is a no-code automation platform with a drag-and-drop interface that simplifies the creation of complex workflows. You can connect it to various services—like your SEO data provider or Google Sheets—and build sequences that take data from one place to another, trigger actions, and manipulate the data as needed.
n8n
This is a newer automation tool that is open-source and can be more cost-effective. Although it’s powerful, we haven’t used it extensively, so we’ll mostly focus on Make in our examples. However, if you’re comfortable experimenting with new platforms, n8n might be worth exploring.
High-Quality SEO Data
A lot of folks gravitate toward big-name tools like Ahrefs and SEMrush. While these services are great, they can be extremely expensive once you try to use their APIs. In many cases, you have to be on their highest-tier or enterprise-level plan to get API access.
Enter DataForSEO. This is a budget-friendly yet robust data provider that offers:
• Backlink data
• Keyword research data
• Google My Business data
• SERP data, and more
For a fraction of the cost of the better-known platforms, you get high-quality SEO data you can integrate directly into your automations. As a bonus, if you sign up through certain referral links (*hint* the one we have for you here), you might get a free credit (like $5) to get started. That’s enough to test the service without committing big money up front.
Storage and Collaboration (Google Sheets)
When it comes to storing and analyzing data, Google Sheets is your friend. It’s free, widely accessible, and easy to integrate with Make (and many other automation tools). You can create multiple Sheets:
• One for raw keyword data
• One for competitor insights
• One for backlink tracking
• And so on
By keeping your data in Sheets, you ensure that it’s neatly organized and readily available for your next steps, whether that’s feeding it to an AI model or conducting manual reviews.
#1: Automating Keyword Research
Generating Keyword Suggestions
Keyword research is often the first major step in any SEO campaign. You need to figure out what people are searching for and how competitive those terms are.
Using DataForSEO, you can automate the process of discovering:
• Keyword suggestions related to a root keyword (e.g., “learn SEO”).
• Search volume for each suggested keyword.
• Competition metrics (to gauge difficulty).
• Cost per click (CPC) if you’re also running ads.
• Search intent (where available).
A typical workflow might look like this:
1. Input your main keyword in a Google Sheet (e.g., “learn SEO”).
2. Use Make to send this keyword to Data for SEO’s Keyword Research API.
3. Retrieve a list of related keywords, along with monthly search volumes, competition, and CPC.
4. Populate a new tab in your Sheet with these findings.
This sets you up with a powerful data set you can then analyse or feed into AI models. If you want to detailed step-by-step guide on an automation that covers most of this, check out the video below, just remember to take it slowly at first, it can be overwhelming at first but the benefits are well worth it... (that's what she said)
Scraping SERP Data
Once you have your list of potential keywords, it’s time to look at the SERPs (Search Engine Results Pages). With Data for SEO, you can also pull in the top organic search results for each keyword. This tells you:
• Which domains are ranking in the top 10 results
• How many backlinks these domains have
• An estimate of their monthly organic traffic
• Other relevant metrics that help you gauge the difficulty of ranking
Automated SERP scraping gives you a data-driven snapshot of the competition. You’ll know exactly who you’re going up against and can spot patterns (e.g., smaller sites ranking for certain terms that you might be able to outrank).
Leveraging AI to Discover Keyword Opportunities
One of the best ways to take your keyword research to the next level is to feed your data to an AI model, such as GPT 4o or a smarter reasoning model like o1 and even DeepSeek R1, which is a free model that is *nearly* as smart as o1.
Why is this helpful? Because:
• You’re not just asking an AI to “come up with random keywords.”
• You’re giving it actual, context-rich data (like search volumes, competitor difficulty, and more).
For instance:
1. Collect your newly scraped data (keywords, volumes, competitor info) in a Google Sheet.
2. Send this data to an AI model through an automation in Make.
3. Instruct the AI model to propose additional keyword opportunities that align with your overall strategy, factoring in your domain’s current authority and resource constraints.
This approach produces more targeted keyword suggestions that match your real-world data, rather than a generic list that may or may not align with your site’s strengths.
Finding Frequently Asked Questions and Reddit Q&A
Adding a FAQ section to your content or creating blog posts answering specific questions can set you up as an authority. Tools like Answer the Public or Also Ask can help you find questions people type into search engines. But there’s another hidden gem: Reddit. You might be thinking that Reddit is absolutely terrible to navigate for FAQs, and you would be right, but there a solution to help you filter through the internets hay to find the golden needle... (strange metaphor, I know)
• RedditInsights.ai is a tool that lets you input a specific subreddit and pulls all the frequently asked questions or topics people are discussing there.
• Because Reddit content isn’t always fully indexed by Google, you can spot questions that might not appear in standard keyword tools.
• Writing a blog post that addresses these Reddit-specific questions can position you as the first to answer a query that might later gain traction in search results.
This can be an absolute goldmine for long-tail keywords and “fresh” content ideas. By the time others catch on, you’ll already have a well-established page on that topic.
You can take RedditInsights a step further an join it with Machined.ai for quick and effective strategy that will help you write unique content in minutes. You can learn how to do the entire flow with the video below.
#2: SEO Competitor Analysis Automation
Why Competitor Analysis Is Essential
You’ve probably heard someone say, “I’m doing the exact same thing as that competitor, but they rank, and I don’t. Why does Google hate me?”
Often, it’s not that Google hates you—there are under-the-hood factors at play:
• Your competitor might have a larger backlink profile.
• They may be ranking for more total keywords.
• They could have a better site structure or more user engagement signals.
In short, appearances can be deceiving. You need to dive deep to understand what’s really going on.
How to Automate Competitor Backlink and Ranking Checks
Here’s how automation can help:
1. List Your Competitors: Start with a spreadsheet that includes the URLs of your top competitors.
2. Create a Workflow in Make:
• Connect to Data for SEO’s backlinks API.
• For each competitor, pull data on:
• Number of domains linking to them
• Number of total backlinks
• Anchor text distribution (optional)
• Also pull data on how many keywords each competitor ranks for, and in which positions (1, 2–3, 4–10, etc.).
3. Populate the Data in Google Sheets:
• Each competitor gets its own row or tab, which updates automatically whenever you trigger the workflow or set it to run on a schedule.
By the end, you’ll have a rich data set showing exactly how your competitors stack up in terms of links, domain authority, and organic rankings.
Combining Competitor Data with AI Insights
As with keyword research, you can feed competitor data to an AI model to get a second opinion on what it all means. For instance:
• Ask the AI to compare your backlink profile with your competitor’s and see if there are any glaring gaps.
• Let it suggest new link-building opportunities or content angles based on competitor strategies.
When you combine raw data with AI’s pattern-recognition capabilities, you get a more comprehensive picture than data alone could provide. It's a great way for those who are allergic to numbers (like me), to digest and understand the why, what, and how of the raw data.
Once again, like all the other sections in this blog, if you want a complete tutorial on how to create a powerful competitor analysis automation, check out the video below.
#3: SEO Content Generation Automation (and the Role of AI)
Why You Shouldn’t Automate Everything
Now we get to the most popular form of SEO automation: content generation. Tools like GPT4o, Claude, Jasper.ai and Machined.ai can produce articles in seconds. It’s tempting to let the machine run wild and churn out hundreds of blog posts. However, you risk:
• Publishing low-quality or repetitive content
• Missing your own unique expertise or “human touch”
• Getting penalized by Google if the content reads like spam or fails to provide real value
We firmly believe AI should assist in content creation, not replace you entirely.
(Don't write content for the sake of just writing content, this will just feed the 'dead internet theory'...If you don't want to be pessimistic about where the future of the internet is going, maybe don't look into that one)
Staying on Google’s Good Side: Quality Control
Google doesn’t have a specific policy that says, “We ban all AI-written content.” Their actual stance is that they value high-quality content, regardless of how it’s produced. If you use AI in a way that leads to:
• Comprehensive coverage of a topic
• Accurate, well-researched information
• Clear value-add for your audience
…then you shouldn’t worry about penalties. If, however, you’re just generating fluff for the sake of publishing more articles, expect trouble.
Using AI Tools to Speed Up Content Creation
A practical approach looks like this:
1. Outline Your Post: Decide what the main headings (H2, H3) are going to be, and the key points you want to cover.
2. Generate the First Draft with AI: Use a tool like Machined.AI (or OpenAI’s GPT models) to flesh out the sections. You can write 20, 30, or even 40 articles in the time it used to take to do just one.
3. Human Review: This is crucial. Read through the AI-generated text thoroughly:
• Add anecdotes and examples from your own experience.
• Insert brand-specific info or personal stories that make the content unique.
• Fact-check any data that might be out-of-date or incorrect.
4. Final Edit: Add images, tables, supporting illustrations (Napkin.ai is awesome for that).
This method ensures you’re combining AI’s speed with your expertise, maintaining a high level of quality and uniqueness. We have tried this many times with Machined.AI and get great results, you can check out how to do the whole process below.
Repurposing Content Across Platforms
Automation doesn’t stop once you hit “Publish” on your blog. You can also repurpose content for:
• LinkedIn updates
• Facebook posts
• Pinterest pins
• Twitter threads
• Email newsletters
However, keep in mind that every platform is different. LinkedIn, for example, often penalizes posts that drive users away with external links. It’s better to share the gist of your post directly on LinkedIn, providing real value so your audience doesn’t have to click away just to learn something. If they see the full value in your LinkedIn post, they might be more inclined to visit your site out of genuine interest, rather than an obligatory click.
Automation tip: You can set up a workflow where once a blog post is published (tracked by your RSS feed or a webhook), Make grabs the text, modifies it to fit another platform’s character limit or style, and then posts it automatically. Just ensure that the repurposed content is truly adapted—don’t just copy-paste a few lines and a “Read more” link.
Three Fundamental Skills for Successful SEO Automation
If you want to excel at automating your SEO processes, focus on these three core competencies:
Deep Understanding of SEO
You need to know what you’re doing when it comes to keyword research, competitor analysis, and content strategy. Automation can’t fix fundamental misunderstandings about SEO best practices.
Solid Knowledge of AI Models
Know how to work with large language models and specialized AI tools. Even just understanding how to get an API key from OpenAI’s playground can open a world of opportunities. It won't hurt to learn how to craft a decent prompt, this can go a long way.
Basic Understanding of Automation Software
Platforms like Make let you build complex workflows without coding knowledge. Still, you need to grasp the basics—like triggers, data mapping, and error handling—to ensure your automations run smoothly.

Bringing It All Together: Step-by-Step SEO Automation Workflow
Let’s outline a sample workflow that integrates all these automations into a cohesive process:
1. Keyword Brainstorm
• You add a “seed” keyword to Google Sheets (e.g., “learn SEO”).
• Make triggers an automation:
1. Calls Data for SEO to gather related keywords.
2. Pulls SERP data for each of these keywords.
3. Stores all the results in your Sheets.
2. AI-Enhanced Keyword Recommendations
• Make sends the new data to an AI model along with a prompt asking for further keyword suggestions (especially long-tail queries) based on search volume and difficulty.
• AI returns a refined list, possibly with suggestions you hadn’t considered.
3. Competitor Snapshot
• You maintain a list of competitor domains in another Sheet.
• On a weekly or monthly schedule, Make retrieves:
• Their backlink counts, ranking keywords, domain authority, etc., from Data for SEO.
• Each competitor’s top 10 performing keywords.
• This data updates in the same Sheet, creating a dynamic “competitor analysis” dashboard.
4. Content Creation
• You identify high-potential keywords from Steps 1 and 2.
• Use an AI writing tool to draft articles for each keyword.
• Human edit: Add your expertise, insights, and unique angles.
• Finalize the post and publish on your site.
5. Repurposing and Distribution
• When new articles go live, Make picks it up from your RSS feed or a WordPress webhook.
• The workflow automatically creates platform-specific drafts:
• One version for LinkedIn with a more discussion-oriented or story-telling angle.
• A short snippet for Facebook that highlights a key insight.
• You quickly review these drafts (to ensure the formatting and voice are right) and then schedule or post them.
6. Performance Tracking and Feedback Loop
• Another workflow runs weekly or monthly to check your newly published content’s ranking progress.
• If certain articles underperform, you feed that performance data back into your AI model, asking it to suggest improvements or identify missing subtopics.
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Final Thoughts and Next Steps
SEO is part art, part science. Automation and AI let you handle the “science” side—collecting data, analyzing trends, and producing initial drafts—while you bring the “art” by adding personal insights, creativity, and human nuance.
If you’re serious about leveling up your SEO with automation and AI, keep the following in mind:
• Start Small: Pick one process (like keyword research), automate that, and then gradually expand.
• Stay Human: Even as you scale up content production, always review and refine. Don’t let your brand voice get lost in machine-generated text.
• Join a Community: If you need a place to learn the ins and outs of SEO automation—complete with how-to guides, real-time support, and like-minded people—check out our AI Ranking Skool community. It’s a space where you can ask questions, get support, share workflows, and get feedback on your automation setups.
Automation is a marathon, not a sprint. But once you get the hang of it, you’ll find that your SEO processes become both more efficient and more effective. By leveraging AI in tandem with automation platforms, you can spend less time on tedious tasks and more time on high-value strategic decisions—like figuring out what your audience really wants and how you can deliver it better than anyone else.
Ready to take the next step? Open up Google Sheets, sign up for DataForSEO, and start tinkering with Make. As you build these workflows and see the results, you’ll realize that SEO automation isn’t just a trend—it’s the future of online marketing. And best of all, you’ll be freeing yourself from repetitive work so you can focus on what you do best: growing your business and delivering real value to your audience.
Good luck, and happy automating!

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