After years of working alongside CRM administrators, I’ve learned the single biggest difference between CRM platforms that drive revenue and ones that collect digital dust. The difference isn’t the software nor the budget, but the quality of the administration behind it.
If a brand is not visible in answer engines, it’s missing critical early-stage influence. According to McKinsey, 50% of consumers now use answer engines, and more than 70% rely on it to ask questions and gather information. That means a growing share of discovery occurs within AI tools and before users click through to websites.
A CRM is like a teenager’s journal – full of sensitive information. But instead of school stories and secrets, it holds contact records, purchase history, support conversations, and for some, health information or payment data, too.
As AI search reshapes how customers discover and evaluate brands, tools like Profound are gaining attention for helping marketers measure visibility within AI-generated answers. But, as budgets tighten, new AI visibility features emerge, and integration demands increase, many teams are actively seeking alternatives to Profound AI.
If you want to know how to get indexed by ChatGPT, I’ll show you, but first, I want to clarify: Other articles on this topic conflate “getting indexed by” with “showing up in” ChatGPT — and they are not the same thing. Getting indexed by ChatGPT means OpenAI’s search crawler discovered your page and stored it in OpenAI’s proprietary index (about which very little is publicly known). Showing up in ChatGPT means your content appeared in an answer, which can happen via that index or via a live web fetch triggered by a user’s query.
AI search interfaces are reshaping how content gets surfaced and cited. Pew Research data from 2025 found that around one in five Google searches produced an AI-generated summary, with 88% of those summaries citing three or more sources. Bain’s 2025 research found that roughly 80% of consumers rely on zero-click results in at least 40% of their searches.
Marketers are turning to AI-powered tools to scale relevance without increasing manual effort as inbox competition increases and performance expectations rise. AI email marketing tools are rapidly reshaping how teams execute and measure email campaigns. AI advances now support everything from subject line creation and personalization to send-time optimization and revenue attribution.
Schema markup for AEO helps answer engines understand a website. Schema is readable by AI crawlers because it’s added to a site’s HTML. It allows SEO professionals to add additional context and map entities without overwhelming the website’s front end or users. This additional context provided by schema reduces ambiguity and increases the likelihood that the web content can be accurately cited in AI-generated answers.
Keyword research for AEO can feel overwhelming because audiences are searching for almost everything in AI search, and queries are nuanced and personalized.
Customer relationship management (CRM) systems have become foundational to effective email marketing. For teams learning how to use a CRM for email marketing, the key is connecting contact data, segmentation, automation, and measurement into a single, cohesive workflow.
It seems like every brand is scrambling to get a piece of the pie in this new answer engine optimization (AEO) world. But what if you could get ahead of the curve by knowing the best on-page content formats for AI as verified by research? I pored over results from the new HubSpot State of AEO 2026 report and Wix Studio’s AI Search Lab research on most-cited content types to find out.
There’s a widening gap between what the market says about AI and what we actually hear from customers. The media, the VCs, the AI labs, and influencers have all talked about AI replacing humans, ripping out trusted software, and token-maxxing as ends worth pursuing. But the leaders running real businesses are increasingly asking the right questions. How do I make my people better with AI? Which systems can I trust? How can I measure the ROI of this spend? We hear these questions every day.
AI search behavior may be causing a dip in your traffic, but it’s also sending higher-quality leads your way. For marketers, that second part is a massive win. AI search was the number one predictor of purchase intent for CRM software buyers, according to HubSpot’s State of AEO 2026 report. And there are more findings from the report that every go-to-market team needs to know.
For years, the SEO playbook was straightforward: earn backlinks, climb rankings, capture clicks. But as AI reshapes how traditional SEO works, a different mechanism is determining which content gets seen — and it’s not backlinks. It’s citations. The role of citations in AEO is fundamentally different from link-building: instead of other publishers vouching for your page, AI answer engines are selecting your content as the direct source behind their generated answers.
A few weeks ago, I wrote about our vision for the agent era: agents should be able to run on HubSpot, and to run HubSpot. I want to go a level deeper on what “run HubSpot” actually means, and our latest step in bringing this vision to life.
Walk down a suburban street, and you might stumble across a following sign. It’s probably messy with poor formatting and inconsistent font size. Here’s one that I saw in Houston.
If you’re worried about what AI Overviews mean for SEO, let me remind you of the panic over featured snippets circa 2017. Remember how that turned out? At first, bloggers and SEOs bristled over these quick-glance summaries at the top of the Google SERPs, fearing they’d steal all our traffic. Eventually, however, we adapted and started optimizing content to get mentioned in them. I believe the same will be true of AI Overviews. I mean, it’s already happening: The internet is now filled with the latest advice on how to get cited in AI Overviews (including this article).
Google AI Overviews appear in Google Search results for a growing share of queries, and if your content isn’t structured to earn a citation, you’re losing visibility to competitors who’ve already adapted. Unfortunately, the challenge isn’t awareness. Most SEO leaders know AI Overviews exist. The challenge is execution: translating Google’s deliberately vague guidance into repeatable content workflows, measuring whether your AI website optimizations are actually earning citations, and proving business impact when traditional metrics like rank position and CTR no longer tell the full story. This playbook closes that gap.
Growing up, the only “top 10” I cared about was MTV’s Total Request Live (TRL). When I started working, that became the top 10 results in the Google SERP. Now, my eyes are set even higher as we marketers explore how to rank in AI Overviews.
I’ve spent the last year watching marketing teams scramble to understand why their organic traffic reports tell one story while their pipeline tells another. The missing link is almost always a need for AI search analytics tools.
The brand tracking dashboard says awareness is up. Social listening tools show steady mention volume. The PR platform logged a dozen media hits last quarter. But, none of those tools show how a brand shows up when a buyer asks ChatGPT, Perplexity, or Gemini for a recommendation.
Brand mentions aren’t a new concept, but answer engine optimization (AEO) is giving them a different weight. Brand mentions are any online reference to your brand, product, spokesperson, or company name; right now, they’re happening in more places than most teams can track.
Digital marketing optimization plays a major role in whether a marketing program grows or remains stagnant. Most teams are running campaigns, tracking metrics, and still scratching their heads, wondering why the pipeline isn’t moving. Honestly? The problem usually comes down to process, not effort.
In 2007, Coulter and Coulter showed two advertisements to two random groups of customers. Each advertised £10 discounts on flights to Turkey. One listed the tickets at £188. The other showed a higher price: £233.
Brand visibility determines whether your business gets found or gets passed over — in search results, on social feeds, and increasingly, in AI-generated answers. It’s one of the highest-leverage investments a marketing team can make, and also one of the most commonly mismanaged.
Product SEO is one of the highest-leveraged — and most overlooked — strategies in B2B and SaaS marketing. While most teams pour resources into top-of-funnel content, the pages that actually drive pipeline decisions, such as feature pages, comparison pages, and pricing pages, often go unoptimized and underperform.
For years, HubSpot invested in making our platform the best place for marketing, sales, and service teams to do their work. With AI, we’ve been building it to do the work for them – through agents that qualify leads, resolve tickets, save deals, and drive outcomes across the business. That’s why we call HubSpot an agentic customer platform.
As a content writer with over 7 years of SEO experience, I can confidently say that keyword clustering is a critical technique—even in a world where the SEO landscape has changed significantly.
You already track and analyze your SEO strategy — keyword rankings, organic traffic, SERP positions. But when a prospect asks ChatGPT, Perplexity, or Google AI Overviews a buying question and your brand doesn’t appear in the answer, traditional rank tracking can’t tell you that. AEO prompt tracking helps you measure brand visibility within AI-generated answers by monitoring whether (and how) your brand gets cited when real AI prompts are run across the engines your audience is actually using. For marketing leaders, SEO managers, and demand gen teams, it’s the measurement layer that closes the gap between “we publish great content” and “we can prove AI search drives pipeline.”
Every company’s competitors are showing up in AI-generated answers, but do marketers know which ones, for which queries, and why? That’s exactly what AEO competitor analysis is designed to tell teams.
When tracking share of voice for marketing teams, it’s often assumed to be a vanity metric — a number executives like to include in board decks but one that rarely influences strategy. In practice, that assumption doesn’t hold up.
I’ve spent considerable time testing free answer engine optimization tools across dozens of brand audits, and the verdict is clear: you don’t need a five-figure tech stack to get meaningful AEO data.
When I first started auditing content for answer engine visibility, I assumed the keyword research process was roughly the same as traditional SEO — just with a few tweaks. I was wrong.
Your competitors are adjusting pricing, launching new ad creative, publishing content that outranks yours, and showing up in AI answers you didn’t know existed — often all in the same week. Competitor monitoring tools exist to catch those moves early, but most teams end up with fragmented data scattered across platforms, and by the time they’ve pieced it together, the window to respond has closed.
This is part two of a three-part series on how HubSpot transformed with AI. Part one covers how we build with AI. Part three is how we operate as an AI-first company.
This is part one of a three-part series on how HubSpot transformed with AI. Part two covers how we grow with Agent-first GTM. Part three is how we operate as an AI-first company.
This is part three of a three-part series on how HubSpot transformed with AI. Part one covers how we build with AI. Part two covers how we grow with Agent-first GTM.
The AEO benefits that matter most to marketing leaders have shifted from theoretical to measurable. As AI-powered search engines like ChatGPT, Google AI Overviews, and Perplexity handle a growing share of how buyers discover brands, the rise of AI-powered search results increases brand visibility; the teams investing now are seeing real returns in conversion quality, pipeline influence, and long-term authority.
Your brand’s AI visibility score covers the part of the search landscape that traditional SEO rank tracking can’t see. Tracking it is becoming as essential as monitoring Google rankings — and a lot harder to pin down.
Search behavior has changed dramatically, and teams need to learn answer engine optimization (AEO) best practices to keep up. While traditional search engines still dominate, people increasingly turn to AI tools like ChatGPT to answer their questions. Heck, with 79% of those who already use AI for search believing it offers a better experience, even Google has introduced AI overviews to stay competitive.
A lot is going on in search today. Google still reigns supreme, but the competition and evolution coming from AI alternatives have many marketers wondering how to optimize for ChatGPT.
AI search engine citation tracking helps measure brand visibility and authority in AI-powered search results. As AI-powered search experiences reshape how people discover information, evaluate vendors, and build shortlists, visibility inside AI answers is no longer a vanity metric. If AI engines aren’t citing your brand, you’re missing influence at the exact moment buyers are forming opinions.
Generative AI is changing how people discover brands, products, and information. Because it disrupts the buyer journey, it requires new metrics, specifically GEO KPIs, that accurately reflect performance within these AI engines.
AEO metrics every marketer should track in 2026
Answer engine optimization (AEO) is a marketing strategy designed to help brands appear more consistently and accurately within AI-driven answer engines such as ChatGPT, Perplexity, and Copilot.
Research shows that 32% of buyers discover new B2B vendors using generative AI chatbots. This is why an answer engine optimization (AEO) strategy for B2B businesses is essential. AI-driven answer engines help buyers discover, evaluate, and shortlist vendors. The same research found that buyers start with an average of 7.6 potential vendors and narrow this to 3.5 before making their final decision.
GEO — or, as HubSpot refers to it, AEO — has found its place in the search landscape, and it’s reasonable to think that the future of generative engine optimization is guaranteed. According to Datos’s State of Search report, Q4-2025 saw some interesting changes. For the first time, AI tools had a consistent 1.31% to 1.34% of visits in the U.S. In previous quarters and reports, traffic to AI tools was growing. This stability in traffic suggests that AI search tools may have found their place in the wider search landscape.
While many are still skeptical, the global creator economy is expected to reach $1.18 trillion USD by 2032. And for minority creators and entrepreneurs from underrepresented groups, this moment is especially significant.
Marketers use AEO and GEO interchangeably, but there is a difference, and that’s what will be defined and explained in this article. In brief, AEO optimizes content for answer boxes and voice search results, while GEO targets AI chatbot citations and generated summaries.
Today, more and more buyers are beginning their journey with an AI-search. They may ask ChatGPT to compare products or use an AI-powered platform like Perplexity. Or, they're just Googling an offering and reading the AI Overview, all without clicking a link.
HubSpot realized that our buyers were moving from search engines to answer engines like ChatGPT, Gemini, and Perplexity — but we had no reliable way to measure AI visibility and understand whether our AEO plays were working.
If you’re asking yourself, “How can I measure AEO success?”, AEO rank trackers should be your next investment. They gauge your brand visibility in AI-generated answers, considering metrics like citations, mentions, share of voice, and sentiment.
By now, you know that everyone’s buzzing over answer engine optimization (AEO). So, just what is AEO in marketing? It’s a new way of ensuring your brand shows up in the places your prospects are using more and more: AI tools like Gemini, Perplexity, and ChatGPT. These AEO insights will catch you up on the most crucial information to get started now.
There’s a lot of conjecture out there about how to show up in ChatGPT results, but if you want advice from a practitioner who’s actually done it, keep reading.
Most marketing teams I talk to are doing genuinely good SEO, and yet when they open ChatGPT or Perplexity and type in the prompts their buyers are actually using, their brand is nowhere to be found. This is the exact problem the FSA Framework was built to solve.
An AEO strategy for SaaS won’t stray too far away from a good SEO strategy, but some tactics benefit AI search more than others, and it helps to know what these are. We all know that AI has shifted how brands earn visibility, and how visibility doesn’t equal clicks. But for SaaS, the way buyers conduct discovery and evaluation has changed disproportionately.
Two-thirds of marketers say that marketing has changed more in the past three years than in the past 50. Understanding Loop Marketing versus traditional marketing has become essential for marketers in 2026. The two frameworks differ fundamentally in how brands reach, engage, and retain customers in an AI-driven world.
A marketing forecast estimates future marketing results, such as leads, pipeline, and revenue, using historical data and conversion assumptions. Marketing forecasting connects planned activity to expected outcomes, helping teams understand what performance is likely to look like before campaigns are executed. This approach supports clearer planning, more predictable growth, and stronger alignment between marketing inputs and revenue targets.
Maybe you’ve opened ChatGPT a handful of times, gotten subpar results, and moved on. Maybe you’ve sat through an AI training or two and thought, “Cool, but how does this actually apply to my job?” Or maybe you’ve bookmarked a dozen AI tools you saw recommended on LinkedIn and haven’t tried a single one.
Search results used to be a doorway. You ranked, someone clicked, and they landed on your site. But today, that model is eroding faster than most marketing teams are equipped to move.
AI-referred traffic has increased by 600% since January 2025, and marketers are racing to understand what that means for brand discovery. For teams seeking clarity on how AI impacts brand and pipeline means investing in new tools like Profound or Athena AI for Answer Engine Optimization (AEO).
Email personalization drives measurable revenue impact. According to HubSpot’s 2026 State of Marketing report, 93.2% of marketers say personalized or segmented experiences generate more leads and purchases, and nearly half are exploring AI to scale those efforts.
Every few years, marketing headlines announce the demise of one foundational strategy or another. First, email; then blogging; then search engines. Now, with the rise of AI comes the question, “Is AI killing web traffic?” — But the curiosity is actually warranted.
Workflow automation tools automate repetitive business tasks across systems using defined triggers and logic. These platforms link apps, CRM data, and communication channels to execute multi-step processes without manual handoffs — routing a new lead through email nurture, scoring it, and assigning it to a rep in a single automated sequence.
Email deliverability is cumulative, and AI email deliverability optimization works by reinforcing the sending behaviors that mailbox providers already measure over time. Mailbox providers evaluate authentication alignment, complaint rates, engagement patterns, and unsubscribe behavior across domains. In 2024, Gmail and Yahoo formalized stricter requirements for bulk senders, reinforcing a core principle: inbox placement depends on authentication, permission, and recipient behavior working together.
Being a content marketer isn’t easy.
You need to be a writer, designer, and editor; have knowledge of user experience, project management, analytics, your industry, and much more. With so many things to juggle, even the best teams are only as effective as the content marketing tools they have at their disposal.
When I first started working in content and weaving SEO into my strategy, I treated Page Authority like a report card: the higher the score, the better I was doing. It took a few humbling ranking losses to a competitor with a lower PA score to make me reconsider.
I've spent most of the last 10 years writing, managing, and improving content to reach internet audiences. But even for an ol' marketer like me, AI content optimization was hard at first. Thankfully, I’ve done a lot of the work, so it doesn't have to be for you.
Consistency is key to achieving any goal.
Want to learn to play the piano? Practice consistently. Trying to get in shape for a sibling's wedding? Exercise and eat healthily consistently. Want your brand to be seen and positioned as the premier choice in its industry by both your target audience and AI? Enter brand optimization.
Every successful content strategy starts with a short list of simple words. Before I ever open a keyword research tool, I write down a handful of phrases that describe what my business does or what my audience searches for. Those phrases are seed keywords, and they do more work than most marketers realize.
AI search is already influencing how buyers discover brands — and the results are measurable. According to the 2026 HubSpot State of Marketing report, 58% of marketers say visitors referred by AI tools convert at higher rates than traditional organic traffic. As platforms like ChatGPT, Perplexity, and Gemini increasingly shape buying decisions, visibility inside AI-generated answers is quickly becoming a competitive advantage.
Whether I’m looking for a new car, email marketing software, or pair of shoes, sometimes I wish I had a personal shopper — Someone to share a second opinion, make suggestions when I’m indecisive, and help find the best deal. In recent years, ChatGPT product recommendations and its Shopping Research feature have become this for many.
We trust simple promises more than long lists. When brands focus on one clear benefit, it feels more believable than trying to do everything at once. Take it from Google.
Community marketing is a growth strategy centered on participation. It brings customers together to share knowledge, solve problems, and build trust. In the process, it drives advocacy, retention, and lower customer acquisition costs.
Competitor analysis tools are software platforms that help marketing teams monitor and compare competitor strategies across SEO, social, PPC, and market intelligence. Think of them as marketer’s best friend: they expedite the competitor analysis process, so you can see where your competition is making moves (and where the gaps are wide open). The best tools work passively, updating in the background while you focus on moving the needle for your business.
An enterprise SEO audit is a comprehensive evaluation of a large-scale website's search engine performance, technical health, and content alignment. This process identifies growth opportunities across thousands or millions of pages, requiring coordination between marketing, engineering, and product teams. Successful execution ensures that complex site architectures remain crawlable and competitive in high-volume search landscapes.
Artificial intelligence (AI) is rewriting the playbook of so much of our lives — how we interact, how we learn, how we complete daily tasks, and sometimes even what we eat for dinner. So, of course, AI and the future of SEO are no different.
Over the past year, I‘ve had hundreds of conversations with business leaders about AI. The pattern is always the same. They’re not short on tools or ambition. They're struggling with where to get started and how to get value.
“What’s better: Claude or ChatGPT?” is the mind-boggling question every marketer is asking right now. As AI tools become essential to content workflows, understanding the differences between Claude and ChatGPT for marketing can mean the difference between a streamlined operation and a frustrating bottleneck.
Marketing is set for its most transformative year in decades, according to major AI predictions for 2026. Currently, marketers struggle with fragmented customer journeys, declining attention spans, rising acquisition costs, and failed campaigns. Using AI in marketing will redefine how brands connect with consumers by using real-time data processing and predictive analytics.
In times of growth, scaling a marketing team is often the last thing on a company's mind—but that, my friends, is a huge mistake. The lean marketing team that got a business off the ground is not the one that will help it scale. Trust me; as a serial marketing team of one, I’ve experienced the fallout firsthand.
Every reliable tactic marketers now love, from video content to email marketing and blogging, was once a new experiment that early adopters tested and developed. Creating new marketing strategies is foundational to marketing, helping brands reach new customers and gather data that helps facilitate smarter business decisions.
As businesses adjust to the new AEO landscape, marketers are seeing increasing convergence with marketing automation—HubSpot's recent acquisition of Xfunnel signals this shift, bringing AI search optimization directly into the CRM ecosystem where attribution and revenue tracking happen.
Despite what the headlines would have you believe, artificial intelligence (AI) isn’t new. The term and early technology date back to the 1950s, but generative AI (which emerged in the 2010s) is undeniably new terrain.
Sharing content across channels is a top 5 marketing trend in 2026, according to HubSpot’s State of Marketing report. The brands that will do this successfully with the best ROI will focus on amplification, not just copy/paste repurposing.
If you’re managing social media marketing without a social media scheduler, I’ve got one thing to say to you: You’re making your job harder than it needs to be. A social media scheduler eliminates the chaos of logging into multiple platforms, posting in real-time, and hoping you remembered to hit publish at the right moment — freeing you to focus on strategy instead of logistics.
When we hear the word “organic,” we usually think natural, pure, and unadulterated. A delicious juice, perhaps. Well, the same goes for organic marketing — minus the juice part.
In a past work life, I stole search rank positions #1 and zero and even featured snippets from much larger companies, including HubSpot. That’s why I firmly believe bootstrapped small-to-medium-sized businesses (SMB) can compete with big-budget corporations.
Strategies like SEO, social media, and generative engine optimization for small business make it possible.
I never thought I‘d see the day when "Googling" something and sifting through links would become passé. But, like many marketers over the last year, I’m seeing a massive shift in how people find brands, products, and answers online.
An attribution window is the defined time period when a marketing touchpoint — such as an ad click, email open, or page view — can be credited for a conversion. Window length directly affects how conversions are counted, how channels perform, and how budget decisions are made. Platforms use different defaults, and these differences often create mismatches in data across tools.
Marketing tech stacks often expand fast, leading to sprawl. The result is low tool usage. Gartner estimates that only 49% of marketing technology tools are actively used by teams. A marketing operations tech stack audit brings structure back to teams with bloated software.
An AI engine optimization audit evaluates brand visibility, accuracy, and citations in AI-powered search engines. It highlights how a brand appears across ChatGPT, Gemini, Perplexity, and Bing Copilot, and identifies gaps in the facts, descriptions, and links these systems rely on. In contrast, a traditional SEO audit focuses on website rankings and technical health in classic search engines.
Understanding answer engine optimization (AEO) vs. traditional SEO has become mission-critical for content managers and marketing leaders as search shifts toward AI-generated responses, voice results, and zero-click experiences. While page ranking on Google is still important (for now), success increasingly depends on whether a brand stays visible when an AI system summarizes an answer.
The best marketing isn't chiseled in stone. Adaptive marketing is alive, responding to new tools, shifting consumer preferences, trends, and real-time data. Changing with the trends gives brands a competitive edge, if marketing teams handle it correctly.
Here’s a (maybe) mildly spicy hot take: Email marketing reporting is the backbone of any performance-focused email strategy. Without it, you’re sending campaigns into a void, unable to see what’s working, what’s falling flat, and most importantly, what’s driving revenue.
The Gap Between Output and Outcomes
Over the past two years, I've had hundreds of conversations with business leaders about AI. The pattern is always the same: initial excitement about what AI can do, followed by frustration about what it actually delivers.
The way consumers search for answers online has changed over the years. Instead of typing a keyword or query into search engines like Google, people are typing their questions directly into engines like ChatGPT to get direct, no-frills answers.
