How Rtings.com Ranks High on Google with Programmatic SEO

This article is sponsored by Semrush.

Let’s be real here. AI search has completely flipped the script because most old methods just don’t work in this new environment. The main culprit is Google’s AI Mode and AI Overviews.

They answer questions fully right there on the results page, which naturally drives down the click-through rate for everyone else. It is not just Google, either.

Platforms like ChatGPT, Gemini, and Perplexity are equally greedy for user attention and want to keep you on their sites rather than sending you elsewhere.

But if you think this means SEO is dead, you are looking at the wrong data. The market tells a completely different story. Just look at 2025, where two massive acquisitions paint a clear picture:

• Positive acquired SurferSEO.
• Adobe acquired Semrush for a staggering 1.9 billion dollars.

Investors do not drop crazy money like that on a sinking ship. It is actually the opposite. SEO is growing, but it demands that we adapt to these updated methods. In fact, White Hat SEO is becoming even more powerful for those who move fast and learn from the winners.

This is where Rtings.com shines. They are a perfect example of mixing programmatic SEO with human-written content. Why does this approach work?

Because manually writing thousands of reviews requires a huge team that most can’t afford. Rtings proves that in the era of AI automation, creating high-quality content at scale is a survival requirement.

Unmiss.com data

If you read this study to the end, you will learn exactly how to apply these strategies to your own projects.

Interlinking and Simple Structure Improve UX

I pay a lot of attention to UX because Google analyzes all the important parameters:

• Time on site
• Bounce rate
• Dwell time (the time between clicking your result and going back to check other URLs)
• The number of opened pages
• Scrolling behavior

Satisfying user intent is the most important element in modern SEO. Users have plenty of other choices for consuming content. If your page is hard to understand or irrelevant to their intent, nobody stays. Leaving and never coming back is just regular behavior now.

Rtings is the king of the right interlinking strategy because they put these links everywhere, from the drop-down menu to the search bar.

You can see that all these links do not confuse users, simply because there is enough free space between them. Once you tap on a specific option in the menu, you get access to a lot more links, all organized in a suitable structure that just works.

You can get a lot more internal links just by scrolling down to their user-friendly sitemap. This is a perfect example of how to save time for your users. It lets them find any content they need in just a few clicks.

If you open any page or category, you will find a lot more links confirming that this website does an excellent job with interlinking.

This is still a massive issue for many projects. They pump out tons of new content but fail to interlink it into a suitable structure. The good news is that unlike backlinks from other sites, you have 100% control over this type of link building.

How to Create the Right Interlinking Structure

I personally use Gemini 3 for this. This AI model has a massive context window and a better connection with Google’s ecosystem, allowing it to provide superior tips on semantic relevance and interlinking optimization. Instead of just guessing, I use this specific prompt to let the AI do the heavy lifting:

“Act as a content architecture consultant. Given my new pillar post on [Pillar URL/Topic], analyze my 15 most relevant existing articles on [site:yourdomain.com]. Create a 10-point internal linking schema. Specify the anchor text, the source URL, and the target URL, optimizing for topical authority.”

Think of this prompt as a laser-focused alternative to tools like Sitebulb, Screaming Frog, and Link Whisper. Those tools are still essential for managing big projects at scale, but for specific URLs that have high traffic potential, this AI approach helps you build topical authority much faster.

Most Meta Tags Titles and Descriptions Are Long

Rtings borrows a page right out of the Amazon playbook here by generating incredibly long titles and descriptions.

You might wonder why they do this if Google just cuts off these snippets in the search results. The answer lies in the algorithm. Even if the user cannot see the full text, Google reads it all to better understand user intent. This helps the page rank for a wider variety of long-tail keywords that a short, snappy title might miss.

The data supports this aggressive strategy. The Unmiss website audit found that Rtings has 5.87 times more long titles than short ones. The gap for descriptions is even more massive, with 125.28 times more long descriptions than short ones. This is not an accident. It is a calculated move to feed the search engine as much context as possible.

Think of this method as giving Google a better menu to choose from. By generating these longer meta descriptions, you effectively help the search engine pick out the exact snippet of text that matches what the user is actually looking for.

Google ranks these pages high by frequently cutting the second part of the title and swapping in a relevant chunk of the description, ensuring the result always feels tailored to the specific query.

It automatically cuts the second half of the title and pulls in a specific section of the description to better match the query.

This is dynamic SEO in action. By providing “oversized” meta tags, Rtings gives Google the flexibility to rewrite the search result on the fly, ensuring it looks relevant to the user’s specific question.

Google is not just relying on your pre-written meta tags; it is actively scanning your page for better answers. In fact, a May 2025 study by Seer Interactive found that Google rewrites meta descriptions for 70% of queries.

Why? Because it wants to match the specific intent of the user.

For example, if you look at the Rtings comparison between the Astro A50 and Sony Pulse 3D, Google often ignores the generic description. Instead, it pulls text directly from the “Verdict” section on the page.

It knows that users searching for a comparison want the bottom line – which product is better and why – so it grabs the specific details about comfort, build quality, and microphone performance right from the body content.

Google effectively “remixes” the search result: it cuts the second half of the title and injects a highly relevant snippet from the page description to create the perfect answer for that specific searcher.

Rtings often uses this template for comparison pages, but it is not a rigid rule like the automatic meta tags you might see on a Wise.com case study. In fact, many of their pages rely on a completely different structure.

Content Touches All Stages of the Sales Funnel

Data from Semrush shows that informational keywords only account for 34.3% of their traffic. The rest is heavily concentrated at the bottom of the funnel, targeting users who are actually ready to spend money.

Rtings dominates the search results for massive one-word keywords like “headphone”, “asus”, “laptop”, and “refrigerator”. In the SEO world, ranking for these “head terms” is usually considered impossible for most sites because the competition is so fierce.

If you want to see exactly which keywords your competitors are winning with, you can run a similar analysis using Semrush One. You can try it for free using this link (full disclosure: I earn a small commission if you sign up, at no extra cost to you).

What really surprised me is that Rtings captures traffic for massive one-word keywords like “headphone,” “Asus,” “laptop,” or “refrigerator” using bottom-funnel content.

You might expect these broad terms to trigger simple, wiki-style “What is a laptop?” pages. Instead, Google ranks pages that drive decisions: best product lists, brand reviews, comparison charts, and catalogs.

This isn’t a fluke. Data from Search Engine Land confirms that these bottom-funnel pages now capture the highest visibility in AI search.

Why Top-Funnel Content is Losing Power This example is a wake-up call for SEOs who still think writing generic top-funnel guides is the only way to build “topical authority.” It is not.

• Old Strategy: Define the product (“What is a refrigerator?”).
• New Reality: Help the user choose (“Which refrigerator should I buy?”).

In the AI era, users (and LLMs) already know what a product is. The value and the traffic lies in helping them find the right one.

AI Generates High-Quality Technical Content

Rtings generates a massive amount of content using AI, and for good reason: humans simply cannot write thousands of technical descriptions for every single model attribute without burning out.

This works because their target audience isn’t browsing for “cute pink laptops” or surface-level aesthetics. They are hunting for raw performance data and deep technical specs. AI excels at this kind of structured, data-heavy writing because it never gets tired of details.

For example, check out the content on this page:

To confirm this, I ran the text through the Unmiss AI detector using our free Chrome extension. The result? 100% AI-generated content.

It sounds extreme, but for a tech specs page, it is actually brilliant. The review is packed with hard data – processor models like the AMD Ryzen AI MAX+ 390, distinct GPU specs, and exact port configurations. A human writer would find this tedious and prone to error, but an AI handles this structured data perfectly, ensuring every spec is accurate and formatted for easy reading.

To be clear, this example doesn’t mean every page on Rtings is AI-generated. Some are fully written by humans, while others use a strategic hybrid approach.

But here is the thing: if experts manage the process with the right prompts and strict editing, LLMs bring real value to the customer. This aligns perfectly with E-E-A-T because it is clear who is responsible for the content, regardless of who (or what) wrote the first draft.

Let’s break down the pages that get the most traffic according to Semrush data:

Out of the top 11 most popular pages (excluding the homepage), 10 contain the word “best” or are dedicated to lists of top products.

When analyzing the content, the AI detector shows a mix: 25% human-written and 75% AI-generated.

But let’s be honest about that 25%. I suspect this “human” portion is largely coming from the user comments section. The actual body content – the part that ranks and drives traffic – is likely fully generated by AI.

So, if you operate in a similar niche and need to replicate this level of precision, start with this prompt on Gemini 3. I prefer this model because it has a superior connection with Google’s ecosystem and excels at analyzing and mimicking high-level content structures.

Role: You are a senior technical writer and audio engineer for yourdomain(.)com You are famous for your objective, data-driven reviews, neutral tone, and heavy reliance on comparative analysis.

Task: Write a “Best Product” segment for a “Best Wireless Earbuds” roundup article based on the specific product I provide.

Format Requirements:

1. Heading: The Award Category (e.g., Best Mid-Range Wireless Earbuds) followed by the Product Name.
2. Score Box: A visual representation of the scores (use text representation like “Travel [8.1]”) for: Travel, Sports And Fitness, Office Work, Noise Isolation – Common Scenarios, Build Quality, and Recording Quality. Estimate realistic scores based on the product’s real-world tier and performance.
3. Link Placeholder: “See all our test results”
4. Paragraph 1 (The Verdict): Start with “The [Product Name] are the [Award Category] that we’ve tested.” Discuss the sound profile (e.g., warm, neutral, bass-heavy), ANC performance (using specific examples like “bus engines” or “office chatter”), battery life (continuous + case), and fit/comfort. Mention features like app support or IP ratings.
5. Paragraph 2 (The Comparison): Compare this product to a close competitor. Use the structure: “The similarly priced [Competitor Name]…” or “If you’re shopping for…” highlighting trade-offs. Discuss nuances like microphone quality, specific codecs (LDAC, aptX), or latency. Use transitional phrases like “That said,” “However,” or “Go toe-to-toe.”

Tone Guidelines:

1. Objective: Avoid marketing fluff. Use “we’ve tested,” “perform amazingly,” “attenuates noise.”
2. Technical: Mention codecs (AAC, SBC, LDAC, aptX), latency, and driver behavior where relevant.
3. Comparative: Always contextualize the product against the market.

Input Data:

1. Product Name: [INSERT PRODUCT NAME HERE]
2. Award Category: [INSERT AWARD CATEGORY HERE, e.g., Best Budget Wireless Earbuds]
3. Primary Competitor: [INSERT COMPETITOR NAME HERE]

This prompt is a powerful starting point for experts who need to scale their content without losing that technical edge.

Real Humans Make Mistakes There is one final way to spot the difference between the AI content and the human element. The Unmiss Chrome extension highlights plenty of grammar mistakes in the comments section – a clear, messy signal that real humans are still running the community discussion.

Real Visuals Win Trust: The Hybrid Secret

Here is the uncomfortable truth: You can fake text, but you can’t easily fake a lab test.

This is where Rtings masters the game. They use a powerful hybrid strategy: AI-generated text mixed with 100% real photos and videos.

While the text might be automated to handle the massive specs and comparisons, the visuals are the “human anchor” that sells it. I looked through their reviews and didn’t find a single stock image or AI-generated graphic. Every photo shows the actual product in their lab, often hooked up to custom testing equipment.

Why This Beats Pure AI AI search engines and chatbots struggle with one major thing: physical reality. They can hallucinate specs or generate generic summaries, but they can’t show you a video of a headphone hinge breaking under stress.

Rtings backs up their data with a massive YouTube channel full of high-quality, hands-on reviews. This visual proof is the ultimate trust signal. It tells both the user and the search algorithms, “We actually touched this product.”

In the AI search era, this is your competitive moat. Projects that combine scalable AI text with undeniable real-world visuals humanize their content better than anything else – and that is exactly why AI tools reference them so often.

Link-Building Is Only Important for Small Projects

Here is a contrarian take: for a giant like Rtings, traditional link-building is practically obsolete.

According to Semrush data, Rtings hit its peak in the middle of 2024, boasting over 54,000 referring domains and a staggering 27 million backlinks. Since that high-water mark, the numbers have actually declined – yet their organic traffic remains dominant.

Why the Decline Doesn’t Matter In the old world of SEO, losing backlinks was a disaster. In the AI era, it is barely a blip.

Why? Because the links falling off are likely from older, stale pages that no longer carry weight. AI search engines and modern algorithms prioritize freshness and relevance. They don’t care about a link from a blog post that hasn’t been updated since 2019. They care about what is being cited right now.

The “Natural” Moat Instead of chasing links, Rtings attracts them naturally. Their new backlink profile is cleaner and arguably more powerful because it comes from high-trust, “link-worthy” sources:

• Wiki websites citing them as a definitive reference.
• Active Forums (like Reddit) where real users verify their arguments with Rtings data.
• Medium.com articles where experts build narratives around their tests.

This is the difference between “building” and “earning.” Small projects need to hustle for links to get noticed. Big, authoritative projects like Rtings focus on content so good that the internet – and AI – has no choice but to cite it.

Conclusion: The Hybrid Future is Already Here

Stop fighting the AI revolution and start riding the wave. Rtings proves that you don’t need to choose between automation and quality – you need both. The winning formula for 2025 is simple: use AI to handle the heavy lifting of technical data and “boring” specs, but use real humans to provide the trust signals that algorithms can’t fake – like hands-on video reviews and genuine community discussions.

If you want to survive the shift to AI search, stop obsessing over top-funnel definitions and start dominating the decision phase. Focus your energy on “best of” lists and direct comparisons where the money actually changes hands. Build a moat with undeniable visual proof, keep your content fresh, and let the AI handle the rest. This isn’t just about ranking anymore; it’s about being the only answer the AI trusts enough to cite.