Learn about the latest industry trends
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. Apative 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.
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.
At 23, I walked into BlackRock‘s New York office fresh out of Wesleyan University, ready to conquer Wall Street. By 28, I had traded my corporate badge for a ring light and a mission to empower women through content creation. Along the way, I learned that the biggest impact doesn’t always come from the biggest institutions. 
If you‘ve ever wondered why B2B email marketing still dominates as a revenue-driving channel in 2025, you’re not alone. Despite the rise of new marketing platforms and AI-powered tools, B2B email marketing remains one of the most reliable ways to nurture leads, accelerate pipeline, and actually close deals.
Selecting an email marketing automation platform goes far beyond choosing where marketers will send emails. The right tool becomes the backbone of lifecycle marketing — powering personalized workflows and driving revenue. Email marketing automation platforms help businesses send targeted, personalized emails at scale by automating workflows, segmenting audiences, and integrating with CRM and ecommerce tools. 
HubSpot’s 2026 State of Marketing report uncovered some good news: 65% of marketers are meeting or exceeding their performance benchmarks. But that success doesn’t happen by accident. Behind those results are clear priorities, rigorous testing, and a sharp focus on the right metrics.![Download Now: Free State of Marketing Report [Updated for 2025]](https://no-cache.hubspot.com/cta/default/53/db725f24-564c-483b-a28c-2d6ff9986516.png)
“SMASH that like button,” the host says, and your eyes roll back so far you can see your own medulla. “And don’t forget to subscribe!”
HubSpot’s latest State of Marketing data shows that 65% of companies exceeded their goals last year, and 93.7% improved lead quality. Should the industry celebrate and prepare for a relaxed 2026? Barely.
Marketing funnels aren‘t cutting it anymore, and you’ve probably felt it in the form of declining traffic, scattered buyer journeys, and tactics that worked last year falling flat today. That’s why HubSpot introduced loop marketing tactics, a four-stage framework designed to help you adapt and grow in the AI era.
If you‘re familiar with the world of SEO, I probably don’t have to tell you there’s been a serious shift in its landscape. Marketers are no longer just optimizing content for Google‘s traditional blue links; we’re now optimizing for AI.
At its core, an SEO audit is a step-by-step review of your website’s technical health, content quality, and search visibility. An SEO audit identifies technical, on-page, content, and link issues on a website. It helps SEO teams identify, prioritize, and fix the issues that block traffic, rankings, and, importantly, conversions. Businesses and SEO teams should create audits to identify opportunities that advance business goals and growth.
If you‘ve noticed your brand appearing less frequently in ChatGPT answers, you’re not alone. Savvy marketers are using generative engine optimization tools to address this issue. These tools help your content get cited by AI platforms, rather than being buried under competitors.
Like your weird uncle, nobody knows exactly how AI engines choose the sources they cite. But experiments are starting to point to ways you can get on their radar.
I’ll say the hard thing nobody wants to admit: Creating “great content” isn’t enough; it’s time for a change. And that change starts with multi-channel content distribution.
AI search visibility refers to how a brand appears in AI-generated results from tools like ChatGPT and AI-augmented search engines such as Gemini or Perplexity. Unlike traditional SEO, which tracks ranking positions and blue links, AI visibility measures how often your brand is mentioned, how your owned content is cited, and how those mentions are framed in model responses.
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Here’s a tough pill to swallow: The way buyers discover brands has undergone a fundamental change. Thus, answer engine optimization tools have emerged as essential technology for marketers navigating the new era of search, where AI platforms like ChatGPT, Perplexity, and Google AI Overviews deliver direct answers instead of links.
Emerging trends in answer engine optimization are reshaping how brands earn visibility, trust, and demand in AI-powered search. Answer engines like ChatGPT, Google AI Overviews, Perplexity, and Gemini now deliver fully synthesized answers directly to users, compressing the traditional customer journey. According to HubSpot’s Consumer Trends Report, 72% of consumers plan to use AI-powered search for shopping more frequently.
Search has changed faster than most teams have adapted. For years, visibility meant ranking — climbing search pages through backlinks, keywords, and authority signals. Now, customers open ChatGPT or Gemini, type a question, and receive a synthesized answer drawn from multiple sources.
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If you’re starting off the year with a bunch of execs demanding explosive growth in 2026, you’ll like this creator’s refreshing take: “Your brand doesn’t need to be loved by everyone. Even if you’ve captured just 3% of the market, your brand can stay alive.”
The marketing efficiency ratio (MER) measures how much revenue marketing generates for every dollar spent. MER is calculated by dividing total revenue by total marketing spend for a defined period. Unlike ROAS, which focuses on the return of specific ad campaigns, MER gives a blended, executive-level view of overall marketing effectiveness across all channels. A higher MER indicates more efficient marketing performance, although what counts as “good” depends on margins, customer behavior, and business model.
Search no longer rewards keywords alone — it rewards clarity. Large language models now read, reason, and restate information, deciding which brands to quote when they answer. An AI search strategy adapts content for that shift, focusing on being understood and cited, not just ranked and clicked.
Entity-based SEO is a content optimization strategy built around concepts, relationships, and context rather than isolated keyword phrases. Search engines identify entities — distinct concepts, people, places, or things — and connect them through the Knowledge Graph to interpret meaning and determine topical authority.
When I first joined HubSpot’s Conversational Marketing team, most of our website chat volume was handled by humans. We had a global team of more than a hundred live sales agents — Inbound Success Coaches (ISCs) qualifying leads, booking meetings, and routing conversations to sales reps. It worked, but it didn’t scale.
Automated email segmentation uses dynamic rules and real-time data to group contacts automatically, eliminating manual list updates while boosting campaign relevance.
As a marketer and consumer, few can explain the impact of AI personalization quite like yours truly.
AI workflow automation tools connect apps, data, and departments to execute tasks automatically — reducing manual work and improving efficiency across organizations. Unlike traditional rule-based automation, these tools use artificial intelligence to predict next steps, learn from outcomes, and continuously optimize processes.
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.
When I joined HubSpot, I stepped into a rare position. I had already spent years as a customer, learning how to build systems creatively with the tools I had access to. Then, I joined the company with the responsibility of modernizing a long-standing customer reference system that had served many teams well but was now struggling to meet new expectations, complexity, and scale.
One of the most satisfying things you can achieve as a business or personality is instant brand recognition.