This week’s Ask an SEO question comes from Rachel P., who wants to find the middle ground between conversion-focused pages and authority-building content: “How do I balance content that converts with content that builds brand authority? It feels like my CRO pages don’t rank well, and my blog posts don’t convert.” It’s hard not to think of your marketing in parts. There’s the part of the strategy that focuses on brand awareness, while another aspect focuses on conversions or whatever key performance indicator. That might be how you’ve been taught to do marketing, but that’s not how marketing actually works, in my opinion. I know that’s a contentious statement. I’ll do my best to back it up. Marketing Is One Song All of your marketing should work together to present a unified process that supports itself at each step of the way. Everything should work together harmoniously. The question here almost assumes they don’t. We have efforts, or in this case, content meant to build authority and content that’s meant to convert, etc. What if we just had content? Instead of siloing all of our efforts, what if we looked at it all as being about “generating momentum”? Producing a certain level of brand inertia and energy that could be captured or bottled up. What if we looked at it as a process across multiple touchpoints, pages, and platforms (many of which are offline) of deepening the connection between our brands and our audience or consumer? In that framework, it’s more about ensuring you give your audience the opportunity to move further down the rabbit hole than it is about “ranking your conversion” pages. To me, the notion of “getting our conversion pages to rank” is more aligned with how you work and far less aligned with how your audience works. You want to give your audience “access” to convert or reinforcement to convert as they feel connected and engaged with you. The connection and sense of engagement are what drive conversion. To paraphrase baseball legend Yogi Berra, conversions are 90% about connection; the other half is product or service awareness. In simple terms, I would focus more on how to build yourself up and engage an audience than on worrying about how to balance conversion rate-optimized content and informational content. If your audience is engaged with your informational content and no one cares about your landing pages, who cares if the latter ranks well? Use the blog to reinforce your offering. If that’s where people want to engage you, then engage them there. Throw a banner up on the side of the blog. Include a call to action here or there. Add screenshots and tie the content into your product (naturally), etc. Meet your audience where they are engaged and connected to you, and guide them to details on your offering from there. This means I wouldn’t worry about balancing content and ranking. I’d worry about, “How do I engage my audience and remind them at the right time of my offering? How do I ensure that if they are engaged and want to move things forward, they have the access they need to be able to do that?” What Does This Mean Practically? Instead of building out two separate sets of pages in this case, think of them as one thing. Authority and trust create a connection. Connection is the straw that mixes the drink. It’s what takes what might be a sterile statement about your brand’s offering and makes it intriguing. Often, I find marketers think of this in reverse order: “My landing pages will rank or whatever, and then the consumer will see my informational content and be reassured. This reassurance will enable them to convert.” It’s the opposite. In whatever way, whether it be via social, informational content, or company advocates, people form a connection with you. This connection emotionally enables them to even consider opening their wallets or recommending your offering, etc. (i.e., conversions). In my opinion, what you want to do is simply remind and reinforce. In those moments of connection, you want to remind the consumer of your offering, reinforce its value, and ensure they have easy access to it. YouTubers sometimes do a great job of this. They offer informational value that creates a connection with their audience. Then, they ask you to subscribe (which in and of itself is a conversion). They will reinforce that connection with additional content, and then, at some point, will mention their product, service, or whatever it is they offer. They’ll tell you to check out the link in the description (because as I mentioned, you need to offer easy entry points), and take it from there. I feel it’s more important to engage your audience and ensure that the access to the material you want them to convert with is accessible than worrying about various sets of content with various intents and how they perform. If your audience is really engaged with your social media content, make sure links are included in your profile and post about your offering. (I like the 80/20 rule here: 80% value-driven content, 20% promotional. I often go 90/10.) My point is, it’s not about page types. It’s about engaging and connecting with your audience and properly utilizing that connection to make your audience aware of your offering and to make it as frictionless as possible thereafter. Subscribe for Daily Search Insights AI, PPC, and digital marketing news distilled to fuel success. Join the other 75k marketers! New Ways For A New Web This sort of dichotomy between areas of marketing and aspects of your marketing strategy works for what I call the “old web.” To be honest, it didn’t work as well as we all bragged about on the “old web” either. Regardless, I see the “new web” as being about success by refinement. In this era of the web, having a consistent message and presence that creates a strong and demarcated identity matters most. We’re in a web environment where there has to be a strong connection to

For over two decades, Google has been the search engine that most people use for everyday searches, product research, and staying up to date on the latest news. Because of this market dominance, Google has also been the main search engine of focus for SEO and marketing professionals. However, following the introduction of ChatGPT and Bing Chat, Google founders Larry Page and Sergey Brin reportedly returned to take an active role in Google’s plans to add chatbot features to Google Search. Shortly after that, around May 2023, Google introduced the chatbot Bard (later renamed Gemini), and after a year, rolled out “AI Overviews” on May 14, 2024, to U.S.-based searchers. OpenAI followed with ChatGPT search in late 2024, transforming the former SearchGPT prototype into a fully integrated search feature within ChatGPT. Google does still hold the majority market share, but there are several alternative search engines that offer distinct advantages over Google, such as enhanced privacy, specialized content, unique algorithms, and tailored user experiences. Here are 25 of the best alternative search engines you can try. List of Alternative Search Engines AI-Powered Search Engines Where search engines include AI chatbots based on large language models, they become prone to errors and hallucinations. Always verify critical information you get from AI-based search engines, such as medical, financial, legal, safety, etc., using authoritative sources. 1. ChatGPT Search Monthly Traffic To Domain: 5.84 billion OpenAI’s ChatGPT search, officially launched in October 2024, is an evolution from its earlier SearchGPT prototype. This feature leverages live web data and AI to deliver relevant answers with clear citations. The service launched as a paid offering but is now available to all users. Key Features Since its launch, OpenAI has continued to refine the feature, adding improved context handling and more comprehensive citation methods to address initial concerns about attribution accuracy. 2. Google AI Mode AI Mode is Google’s newest experiment in AI-enhanced search. Launched in early 2025, this feature builds upon Google’s AI Overviews by adding more advanced reasoning capabilities and interactive conversation. The experience is designed for queries requiring deeper exploration, reasoning, or comparisons. Unlike standard Google Search, AI Mode enables users to: AI Mode appears as an opt-in experience in Google Search for eligible users in supported regions in multiple languages and countries. 3. Perplexity.ai Monthly traffic to domain: 179.5 million Perplexity.ai, founded in 2022, is an innovative alternative to Google that provides contextually rich answers. Unlike traditional search engines that primarily link to webpages, Perplexity.ai is a chatbot that directly answers questions by citing sources from which it fetches information, with an option to ask follow-up questions. This feature allows users to delve deeper into their initial queries by asking subsequent, related questions. This interactive approach mimics a conversational style, making it easier for users to refine their search and get more precise answers. This evolving, dialog-based search experience positions Perplexity.ai as a compelling choice for users seeking a more intuitive and responsive search tool. However, since it uses LLMs for answer extraction, it can hallucinate, leading to incorrect or misleading answers. 4. You.com Monthly visits to domain: 1.54 million You.com is an AI-powered search engine founded by Richard Socher, a prominent natural language processing (NLP) researcher and former chief scientist of Salesforce. The site operates in two modes: a personal mode and a private mode. In personal mode, users can configure their source preferences.  While in private mode, they enjoy a completely untraceable experience; no telemetry data is recorded. The company also offers a Chrome extension and AI-powered image generation. The open search platform encourages developers to build apps and contribute to a more open and collaborative internet. A Revenue-Sharing Search Engine 5. Yep.com Monthly traffic to domain: 152,092 Yep.com (by Ahrefs) promotes itself as a search engine with a difference. It emphasizes user privacy by not tracking users or selling their data. It monitors the frequency of specific word searches and the popularity of certain links in terms of clicks. However, it doesn’t compile a personal profile for targeted advertising. It is designed to directly reward and compensate content creators by using a 90/10 revenue share business model. This means that 90% of all advertising revenue goes directly to the creators of content, allowing them to earn money for their work. In addition, this business model allows users to directly support their favorite content creators and ensures that content creators are fairly compensated. A Copyright-Free Search Engine 6. Openverse Monthly traffic to domain: 270,413 Openverse should be your first stop on the hunt for nearly any type of copyright-free content. While Google provides a broader range of search results, Openverse stands out with its focus on a vast, searchable collection of open-source media, including images, audio, and videos. This search engine is perfect if you need music for a video, an image for a blog post, or anything else, without worrying about angry artists coming after you for ripping off their work. Mainstream Search Engines Mainstream search engines are the Google alternatives that have maintained a modest market share over the past several years. 7. Bing.com Monthly traffic to domain: 3.4 billion As of December 2025, Microsoft Bing sites handled 9.63% of all search queries in the United States. One could argue that Bing outperforms Google in certain respects. For starters, Bing has a rewards program that allows one to accumulate points while searching. These points are redeemable at the Microsoft and Windows stores, which is a nice perk. In my view, the Bing visual search API is superior to its rivals and much more intuitive. Bing carries that same clean user experience to video, making it the go-to source for video searches without a YouTube bias. On Feb. 7, 2023, Bing announced an all-new, AI-powered version of its search engine called “Bing Chat,” which is now called Copilot. The stated goal is to “deliver better search, more complete answers, a new chat experience, and the ability to generate content.” Additionally, Microsoft announced an enhancement of Bing search with a combination of large and small language models for more precise results. According to Satya Nadella, chairman and CEO of Microsoft, there are 10 billion search queries a day, but approximately half of those go unanswered. Bing is looking to fill that void. How

New research paper about creating a dataset for training deep research AI agents (SAGE) provides insights into how this kind of search works. SEJ STAFFRoger Montti Google published a research paper about creating a challenging dataset for training AI agents for deep research. The paper offers insights into how agentic AI deep research works, which implies insights for optimizing content. The acronym SAGE stands for Steerable Agentic Data Generation for Deep Search with Execution Feedback. Synthetic Question And Answer Pairs The researchers noted that the previous state of the art AI training datasets (like Musique and HotpotQA) required no more than four reasoning steps in order to answer the questions. On the number of searches needed to answer a question, Musique averages 2.7 searches per question and HotpotQA averaged 2.1 searches. Another commonly used dataset named Natural Questions (NQ) only required an average of 1.3 searches per question. These datasets that are used to train AI agents created a training gap for deep search tasks that required more reasoning steps and a greater number of searches. How can you train an AI agent for complex real-world deep search tasks if the AI agents haven’t been trained to tackle genuinely difficult questions. The researchers created a system called SAGE that automatically generates high-quality, complex question-answer pairs for training AI search agents. SAGE is a “dual-agent” system where one AI writes a question and a second “search agent” AI tries to solve it, providing feedback on the complexity of the question. The key to SAGE is that if the second AI solves the question too easily or gets it wrong, the specific steps and documents it found (the execution trace) is fed back to the first AI. This feedback enables the first AI to identify one of four shortcuts that enable the second AI to solve the question in fewer steps. It’s these shortcuts that provide insights into how to rank better for deep research tasks. Four Ways That Deep Research Was Avoided The goal of the paper was to create a set of question and answer pairs that were so difficult that it took the AI agent multiple steps to solve. The feedback showed four ways that made it less necessary for the AI agent to do additional searches to find an answer. Four Reasons Deep Research Was Unnecessary The researchers found that some questions look hard but are actually relatively easy because the information is “co-located” in one document. If an agent can answer a 4-hop question in 1 hop because one website was comprehensive enough to have all the answers, that data point is considered a failure for training the agent for reasoning but it’s still something that can happen in real-life and the agent will take advantage of finding all the information on one page. SEO Takeaways It’s possible to gain some insights into what kinds of content satisfies the deep research. While these aren’t necessarily tactics for ranking better in agentic AI deep search, these insights do show what kinds of scenarios caused the AI agents to find all or most of the answers in one web page. “Information Co-location” Could Be An SEO WinThe researchers found that when multiple pieces of information required to answer a question occur in the same document, it reduces the number of search steps needed. For a publisher, this means consolidating “scattered” facts into one page prevents an AI agent from having to “hop” to a competitor’s site to find the rest of the answer. Triggering “Multi-query Collapse”The authors identified a phenomenon where information from different documents can be retrieved using a single query. By structuring content to answer several sub-questions at once, you enable the agent to find the full solution on your page faster, effectively “short-circuiting” the long reasoning chain the agent was prepared to undertake. Eliminating “Shortcuts” (The Reasoning Gap)The research paper notes that the data generator fails when it accidentally creates a “shortcut” to the answer. As an SEO, your goal is to be that shortcut—providing the specific data points like calculations, dates, or names that allow the agent to reach the final answer without further exploration. Subscribe for Daily Search Insights AI, PPC, and digital marketing news distilled to fuel success. Join the other 75k marketers! The Goal Is Still To Rank In Classic Search For an SEO and a publisher, these shortcuts underline the value of creating a comprehensive document because it will remove the need for an AI agent from getting triggered to hop somewhere else. This doesn’t mean it will be helpful to add all the information in one page. If it makes sense for a user it may be useful to link out from one page to another page for related information. The reason I say that is because the AI agent is conducting classic search looking for answers, so the goal remains to optimize a web page for classic search. Furthermore, in this research, the AI agent is pulling from the top three ranked web pages for each query that it’s executing. I don’t know if this is how agentic AI search works in a live environment, but this is something to consider. In fact, one of the tests that the researchers did was conducted using the Serper API to extract search results from Google. So when it comes to ranking in agentic AI search, consider these takeaways: It could be that agentic AI search will consider pulling from more than the top three in classic search. But it may be helpful to set the goal of ranking for the top 3 in classic search and to focus on ranking other pages that may be a part of the multi-hop deep research.

Google’s John Mueller was asked how many megabytes of HTML Googlebot crawls per page. The question was whether Googlebot indexes two megabytes (MB) or fifteen megabytes of data. Mueller’s answer minimized the technical aspect of the question and went straight to the heart of the issue, which is really about how much content is indexed. GoogleBot And Other Bots In the middle of an ongoing discussion in Bluesky someone revived the question about whether Googlebot crawls and indexes 2 or 15 megabytes of data. They posted: “Hope you got whatever made you run 🙂 It would be super useful to have more precisions, and real-life examples like “My page is X Mb long, it gets cut after X Mb, it also loads resource A: 15Kb, resource B: 3Mb, resource B is not fully loaded, but resource A is because 15Kb < 2Mb”.” Panic About 2 Megabyte Limit Is Overblown Mueller said that it’s not necessary to weigh bytes and implied that what’s ultimately important isn’t about constraining how many bytes are on a page but rather whether or not important passages are indexed. Furthermore, Mueller said that it is rare that a site exceeds two megabytes of HTML, dismissing the idea that it’s possible that a website’s content might not get indexed because it’s too big. He also said that Googlebot isn’t the only bot that crawls a web page, apparently to explain why 2 megabytes and 15 megabytes aren’t limiting factors. Google publishes a list of all the crawlers they use for various purposes. How To Check If Content Passages Are Indexed Lastly, Mueller’s response confirmed a simple way to check whether or not important passages are indexed. Mueller answered: “Google has a lot of crawlers, which is why we split it. It’s extremely rare that sites run into issues in this regard, 2MB of HTML (for those focusing on Googlebot) is quite a bit. The way I usually check is to search for an important quote further down on a page – usually no need to weigh bytes.” Passages For Ranking People have short attention spans except when they’re reading about a topic that they are passionate about. That’s when a comprehensive article may come in handy for those readers who really want to take a deep dive to learn more. From an SEO perspective, I can understand why some may feel that a comprehensive article might not be ideal for ranking if a document provides deep coverage of multiple topics, any one of which could be a standalone article. A publisher or an SEO needs to step back and assess whether a user is satisfied with deep coverage of a topic or whether a deeper treatment of it is needed by users. There are also different levels of comprehensiveness, one with granular details and another with an overview-level of coverage of details, with links to deeper coverage. In other words, sometimes users require a view of the forest and sometimes they require a view of the trees. Google has long been able to rank document passages with their passage ranking algorithms. Ultimately, in my opinion, it really comes down to what is useful to users and is likely to result in a higher level of user satisfaction. If comprehensive topic coverage excites people and makes them passionate enough about to share it with other people then that is a win. If comprehensive coverage isn’t useful for that specific topic then it may be better to split the content into shorter coverage that better aligns with the reasons why people are coming to that page to read about that topic. Takeaways While most of these takeaways aren’t represented in Mueller’s response, they do in my opinion represent good practices for SEO. Concern over how many megabytes are a hard crawl limit for Googlebot reflect uncertainty about whether important content in a long document is being indexed and is available to rank in search. Focusing on megabytes shifts attention away from the real issues SEOs should be focusing on, which is whether the topic coverage depth best serves a user’s needs. Mueller’s response reinforces the point that web pages that are too big to be indexed are uncommon, and fixed byte limits are not a constraint that SEOs should be concerned about. In my opinion, SEOs and publishers will probably have better search coverage by shifting their focus away from optimizing for assumed crawl limits and instead focus on user content consumption limits. But if a publisher or SEO is concerned about whether a passage near the end of a document is indexed, there is an easy way to check the status by simply doing a search for an exact match for that passage. Comprehensive topic coverage is not automatically a ranking problem, and it not always the best (or worst) approach. HTML size is not really a concern unless it starts impacting page speed. What matters is whether content is clear, relevant, and useful to the intended audience at the precise levels of granularity that serves the user’s purposes.