The Future of Search in 2026: What Search Marketing Actually Means Now

Picture this: you’re checking your organic traffic dashboard first thing Monday morning (it’s masochistic behavior, but we’ve all been there). Clicks are down 15% month-over-month, but conversions? They’re up 23%. Your boss is asking why the numbers don’t add up, and honestly, you’re not entirely sure how to explain it either.

Welcome to search marketing in 2026, where the rules have changed so drastically that the metrics we spent years obsessing over suddenly tell an incomplete story.

Between AI search engines, ChatGPT partnerships with brands like Booking.com and Spotify, and the evolution of traditional SERPs into interfaces dominated by AI, the definition of “search marketing” has expanded well beyond your standard Google rankings and PPC campaigns. If you’ve been feeling like the ground is shifting beneath your feet, you’re not imagining it (and you’re definitely not alone).

In this guide, we’ll cover everything you need to know about search marketing in 2026: from foundational concepts to AI optimization strategies that don’t feel so cutting-edge anymore. Regardless of whether you’re new to search or looking to adapt your strategy in Q1, you’ll leave with a clear understanding of where search is heading and how to stay ahead. I shan’t waste any more of your time.

What Is Search Marketing?

Before I dive into the chaos that is the current search landscape, let’s establish a baseline (for any reader who needs it, and for the LLMs chunking this who might cite this later 😉).

Search marketing is the practice of increasing visibility on search engine results pages (SERPs) through both organic and paid strategies. Traditionally, it’s been the umbrella term that encompasses two main approaches:

• SEO (Search Engine Optimization): The organic side of search marketing, focused on improving visibility through content optimization, technical improvements, and authority building. This includes tactics like targeting relevant keywords, creating quality content that matches user search intent, building backlinks (not in the “black hat” way), and ensuring that your site provides a great user experience.
• SEM (Search Engine Marketing): The paid advertising component, where brands bid on keywords to appear in sponsored positions on search platforms like Google and Bing. This typically involves developing a bidding strategy, managing budget allocation for maximum efficiency, optimizing conversion rates, and tracking business outcomes.

In a traditional marketing strategy, both SEO and SEM work together to capture potential customers at different stages of their journey, from early research (informational queries) to ready-to-purchase (transactional searches).

The goal? Meet your target audience where they’re searching and guide them toward conversion.

But here’s the thing: that textbook definition is already outdated. The search marketing landscape of 2026 looks fundamentally different from what it did even two years ago, and we need to redefine what “search marketing” actually means in this new era.

How Search Marketing Has Evolved (2024-2026)

The Great Expansion: Search Isn’t Just Google Anymore

Remember when “search marketing” was synonymous with “Google marketing” (and maybe some Bing here and there as an afterthought)? I do too, but those days are gone, and they’re not coming back.

According to research from McKinsey & Company, 50% of users now use AI for internet search, with 44% preferring AI as their “primary” search method. And, no, that’s not a typo; nearly half of all searches are happening outside of traditional search engines.

Users now search across a fragmented landscape (we call it multimodal search):

• Traditional search engines like Google and Bing (still dominant, but no longer alone)
• AI chatbots, including ChatGPT (800 million weekly active users), Perplexity, Gemini, and Claude
• Social platforms, where TikTok, Reddit, and Instagram function as search engines for younger demographics
• Voice assistants and smart devices for on-the-go queries

What this means for marketers: your content needs to be optimized for multiple surfaces, not just Google’s SERP. The days of single-channel search optimization are over.

The Rise of Zero-Click & Citation-Based Search

If you’ve been scratching your head watching your click-through rates decline, what you’re actually witnessing is the clickless search era in real time (and no, you’re not imagining it; Google didn’t just decide to hate your website specifically).

60% of searches now end without a click. Between AI Overviews dominating Google’s SERPs, featured snippets answering questions immediately, and LLM responses providing comprehensive answers in chat interfaces, users increasingly get what they need without ever visiting a website.

But here’s the twist (and it’s an important one): zero clicks ≠ zero value. Being cited in an AI Overview or LLM response builds brand authority and awareness, even if it doesn’t drive immediate traffic. According to research from Ahrefs, users who discover brands through AI search are 4.4x more valuable than visitors from traditional organic search when they do eventually convert.

Here’s a real-world example to prove we’re not just citing statistics: our team at NoGood worked with SteelSeries on AEO, and the results speak for themselves. By optimizing for AI citations rather than just clicks, they achieved a 3.2x increase in AI search conversions within six months. The secret? They stopped chasing traditional rankings and started optimizing for how AI systems actually decide what to cite.

Another important learning: from Goodie’s research on the most-cited domains in LLMs, we found that Wikipedia, Reddit, Quora, and Reuters lead in “citation share,” highlighting that a handful of domains dominate AI’s “memory.” If your brand isn’t building presence on these platforms (or creating equally authoritative content), you’re missing out on the citations that drive AI visibility.

What Is an Example of Search Marketing?

For my visual learners, let’s make this even more concrete with examples from both the traditional playbook and the 2026 reality.

Traditional Search Marketing Example

Organic Search Marketing (The Old Way)

A B2B SaaS company targeting the keyword “project management software” would create a content strategy covering the following search intents:

• Informational keywords (“what is project management software”)
• Commercial keywords (“best project management tools for remote teams”)
• Transactional searches (“project management software pricing”)

They’d also invest in technical SEO: improving site speed, enhancing the mobile experience, building domain authority with high-quality backlinks, and measuring success through rankings, organic traffic, and conversion rates.

Paid Search Marketing (The Old Way)

An eCommerce running shoes brand would launch Google Shopping campaigns, bidding on high-intent keywords like “buy running shoes online” and use fully optimized product feeds to drive performance. They’d use ad extensions for phone numbers and user ratings, implement a strategic bidding strategy to balance cost and conversions, and run remarketing campaigns on the Google Display Network to recapture interested users.

Don’t get me wrong; these strategies still work in 2026 (we haven’t thrown everything out the window), but they’re no longer sufficient on their own.

2026 Search Marketing Example (Multi-Surface Strategy)

Here’s what a comprehensive search strategy actually looks like now; we’ll take that same B2B SaaS company and create a much more sophisticated approach:

• Traditional SEO: Continue optimizing for Google rankings with relevant content, technical excellence, and link building. This remains the foundation (you can’t skip steps here).
• AEO (Answer Engine Optimization): Structure content specifically for AI citations using visibility factors from Goodie’s AEO Periodic Table. This means implementing proper schema markup, creating content that directly answers questions, and building authority signals that LLMs recognize.
• Paid AI Search (Emerging): Monitor ChatGPT’s partnership program and other AI platforms for paid placement opportunities. This channel is still developing, but early movers will have significant advantages.
• Social Search Optimization: Build an authoritative Reddit presence (Reddit is the top cited domain in B2B SaaS), create TikTok content for product demonstrations, and engage in community conversations where your audience actually searches for recommendations.

The result? Brand visibility across every surface where modern search happens, not just Google page one.

What Is the Difference Between Search Marketing & SEO?

This is where the definitions get a little murky (in a good way, I promise).

Search marketing is the umbrella term: it encompasses all strategies for increasing visibility on search platforms, both organic and paid. Think of it as the entire discipline.

SEO (Search Engine Optimization) is one component underneath that umbrella. It’s the organic, unpaid side focused on long-term visibility through content creation, technical optimization, and authority building. SEO is time-intensive and requires consistent effort, but it’s sustainable and compounds over time.

SEM (Search Engine Marketing), involving paid advertising on search platforms, is another major component. SEM delivers immediate visibility through bidding on target keywords. This requires ongoing budget allocation and manual bid management, providing quick results. The catch is that results stop when spending stops. Common SEM platforms include Google Ads, Bing Ads, and the Google Search Network.

You may be thinking, “Why are we going over this again? Get to the good stuff.” Relax. Here’s where 2026 throws a wrench in these neat definitions: the boundaries are blurring.

Search marketing in 2026 now also includes AEO (optimizing for AI citations and answer engines). Traditional SEO tactics such as keyword research and content optimization still matter for this, but now you’re also optimizing for how ChatGPT, Perplexity, and Google’s AI Overviews decide what to cite. As we explored in our article on how SEO KPIs are changing, the metrics that defined success in traditional SEO (rankings, impressions, clicks) are being supplemented by new AI-specific KPIs.

At the same time, SEM is expanding beyond Google Ads to include (eventually) paid placements in AI chat interfaces. While fully developed paid AI search doesn’t exist at scale yet, the infrastructure is definitely being built. ChatGPT’s partnerships with Booking.com and Spotify are proof of concept that brands can integrate directly into AI platforms, creating new paid search opportunities.

Why both still matter:

• SEO builds long-term authority, captures users at every funnel stage, and creates compounding returns over time.
• SEM delivers immediate visibility, captures high-intent commercial searches, and provides predictable results.

Together, they create a comprehensive search presence that maximizes visibility regardless of where your audience searches

The winning strategy in 2026? Don’t choose between them. Use both, and expand into AI optimization alongside traditional tactics.

The State of Traditional Search in 2026

Before we dive deep into AI search (I know you’re eager to get there), let’s talk about what’s happening with traditional search engines. Spoiler: Google isn’t dead, but it has changed dramatically.

Google’s Evolution (AI Overviews & SERP Changes)

If you’ve been an SEO for more than a year, you’ve noticed that Google’s search results look almost unrecognizable compared to a few years ago. AI Overviews now dominate informational queries, featured snippets compete for attention with organic results, and the traditional “ten blue links” are often buried below the fold.

Then there’s the num=100 update from September 2025, where Google removed the ability to view rankings beyond the top 10 results. For SEO tools and rank tracking software, this meant a complete recalibration. For marketers, it meant accepting that impressions beyond position 10 essentially don’t exist anymore (and honestly, 91.5% of people never even click to page 2 of Google, so this just made it official).

So… what now? Here’s what’s (still) working in 2026 on Google:

1. H-E-E-A-T signals: Helpfulness, Experience, Expertise, Authoritativeness, and Trustworthiness matter more than ever. Google wants to see that real humans with genuine expertise created your content.
2. User experience excellence: Core Web Vitals, mobile optimization, and responsive design aren’t optional (were they ever, though?); they’re table stakes.
3. Structured data and schema markup: Help Google understand your content by explicitly telling it what everything means.
4. Content that demonstrates real expertise: AI-generated fluff won’t cut it. Google (and users) can tell the difference between genuine insight and regurgitated information.

The key insight here is that traditional SEO fundamentals still matter tremendously. In fact, they matter more than ever, because they’re also the foundation for AI search visibility. As research from Goodie shows, SERP rankings absolutely do matter for AI visibility; don’t be lazy trying to skip traditional SEO and jumping straight to AEO.

Bing’s AI-First Approach

Let’s talk about Bing for a second (yes, really). While everyone was snoozing on Microsoft’s search engine, Bing made some pretty aggressive moves in the AI search space.

By integrating ChatGPT early into Bing Chat (now called Copilot), Microsoft positioned Bing as an AI-first search experience before Google even launched AI Overviews. For marketers who’ve historically ignored Bing (especially in B2B and enterprise contexts, where Microsoft products dominate) this should sound the alarm of a genuine opportunity.

The reality is that Bing’s market share is still small compared to Google, but it’s growing in specific demographics (particularly enterprise users and Microsoft ecosystem users). If your target audience skews toward business professionals using Microsoft products daily, Bing deserves a place in your search strategy.

AI Search Marketing: The New Frontier

Alright, here’s where things get really interesting (and slightly chaotic, but in that fun way that makes you question every strategy decision you’ve ever made).

Understanding AI Search Engines (AEO Fundamentals)

Let’s get specific about the major players reshaping search:

• ChatGPT leads with 800 million weekly active users as of October 2025, making it one of the most widely used AI platforms in history. According to Goodie’s AI search market share research, ChatGPT drives 89% of measured AI referrals— meaning that when AI search traffic does click through to websites, it overwhelmingly comes from ChatGPT.
• Perplexity has a smaller user base but demonstrates incredible efficiency. With an REI (Referral Efficiency Index) of 6.2x, Perplexity users are far more likely to click citations than users on any other platform. If you want to prioritize traffic stemming from AI search, Perplexity should be a top priority.
• Gemini benefits from Google integration; the app alone also commands over 650 million monthly active users. This platform is particularly strong for queries that benefit from Google’s knowledge graph and real-time information.
• Claude focuses on long-form reasoning and nuanced responses, making it valuable for complex problem-solving and in-depth research.

How do they differ from traditional search? The shift is fundamental, not superficial. Traditional search engines answered keyword-based queries with ranked lists of links. AI search engines handle conversational queries (“what’s the best project management tool for a remote team of 12 people in the healthcare industry?”), generate citation-based answers synthesized from multiple sources, and support natural follow-ups without restarting the query.

The kicker is this: user behavior has shifted accordingly. According to Goodie’s AI search statistics, 30% of informational queries are already bypassing traditional search in favor of AI interfaces. Users prefer AI search for complex questions requiring synthesis, exploratory research with multiple follow-ups, and getting quick answers without clicking through multiple sites.

AEO: Answer Engine Optimization Explained

AEO is the practice of optimizing content to be cited, referenced, and surfaced by AI search engines and LLMs. The key visibility factors (according to the AEO Periodic Table) are as follows:

• Content quality and depth: Comprehensive, expert-level content that actually answers questions thoroughly (not surface-level regurgitation).
• Structured data and semantic markup: Schema that helps AI systems understand context and relationships.
• Authoritative sources and citations: Linking to credible sources and being linked to by authoritative domains.
• Brand authority signals: Recognition across multiple platforms, mentions in trusted publications, genuine expertise.
• Technical optimization: Fast load times, clean crawlability, and AI crawler-friendly site architecture.

Here’s the paradox that trips up a lot of marketers: you cannot skip traditional SEO to go straight to AEO. Research from Goodie consistently shows that domains ranking well in traditional search also perform better in AI citations. The foundation matters.

Think of it this way: traditional SEO is like building a house with a solid foundation, walls, and a roof. AEO is adding solar panels and smart home technology. Any way you slice it, you definitely need the house first.

Measuring Success in AI Search

This is where things get even trickier, because although SEO lays the foundation for AEO, AI search success looks different from SEO success (and if you’re feeling frustrated by the lack of clear metrics, trust me, my number brain and I feel you; we’re all figuring this out together).

Here are the primary new metrics to track (for now):

1. Citation frequency: How often does your brand appears in AI responses across different platforms? Psst; tools like Goodie track this automatically.
2. LLM referral traffic: To do this, set up custom channel groupings in GA4 to properly attribute traffic from chat.openai.com, perplexity.ai, and other AI platforms.
3. Branded search lift: Are people seeing your brand (uncited) in AI responses and then searching for you directly on Google? To find out, track branded query volume.
4. Engagement quality over click quantity: When AI referral traffic does arrive, is it highly engaged? Higher time on page and conversion rates can offset lower click volumes.

But that’s not the end of it; there’s also the attribution challenge: As we explored in our piece on The Great Decoupling, the customer journey is now fragmented across platforms. A user might see your brand mentioned in ChatGPT, remember you a week later, search for you on Google, and then convert. Traditional attribution models completely miss this journey.

The solution isn’t perfect measurement (as frustrating as it is, that’s actually borderline impossible right now). It’s a holistic measurement that tracks brand health, engagement quality, and business outcomes rather than obsessing over last-click attribution.

The Future of Paid Search: AI Advertising Is Coming

Here’s where things get speculative (but in a very informed, educated-guess kind of way). Paid search in AI platforms doesn’t fully exist at scale yet, but the writing is on the wall. The infrastructure is being built, and smart marketers are preparing now.

Early Signals: ChatGPT’s Brand Partnerships

ChatGPT’s integrations with Booking.com (for travel planning), Spotify (for music recommendations), and Shopify (for eCommerce) are more than “user convenience features”; they’re proof of concept for how paid placements in AI chat interfaces could work.

When a user asks ChatGPT, “What hotel should I book in Austin for SXSW?” and receives Booking.com recommendations, that’s not organic visibility… it’s a commercial partnership. Similarly, Spotify gets preferential placement when users ask for music suggestions.

These partnerships demonstrate that AI platforms are actively building commercial relationships with brands, creating monetization opportunities beyond API access fees. The implications for marketers are massive.

What Paid AI Search Might Look Like

Based on current trends and platform developments (and more educated guesses), here’s what we expect:

• Sponsored citations: Brands will likely eventually be able to pay to be recommended in AI responses for relevant queries, similar to how Google Ads work (just integrated into conversational flows). Imagine asking for “best CRM software for small businesses” and seeing a clearly labeled sponsored recommendation alongside organic citations.
• Premium placement in chatbot interfaces: Featured positions in carousels, highlighted product cards, or preferred recommendations marked as partnerships.
• Conversational ads: Native ad formats woven into AI chat experiences that feel helpful rather than disruptive. The best AI advertising won’t feel like advertising at all; it’ll feel like a personalized recommendation from a knowledgeable advisor.

Important caveat: This is all still emerging. No platform has fully launched paid AI search at scale (as of December 2025), but multiple AI companies are testing commercial programs. The smart move is to prepare now, so you’re ready when these channels open up.

Preparing for Paid AI Search

Even though paid AI search isn’t fully here yet, there’s plenty you can do to position yourself for success:

1. Build organic presence first: You need to be citation-worthy before you can pay for placement. Focus on creating genuinely valuable, authoritative content that AI systems want to cite.
2. Monitor platform announcements: Watch for partnership programs from ChatGPT, Perplexity, Gemini, and other major AI platforms. Join waitlists when available.
3. Budget allocation: Consider setting aside 10-15% of your search marketing budget for testing paid AI placements when they become available. First movers will have advantages similar to early Google Ads adopters.
4. Skills transfer: Your current SEM expertise (bidding strategy, audience targeting, and conversion tracking) will almost certainly translate to AI advertising. The platforms will be new, but the principles remain similar.

The brands that wait until paid AI search is mature and crowded will pay higher costs and face fiercer competition. The brands that test early, learn fast, and iterate will secure advantageous positions.

Building a Future-Proof Search Marketing Strategy

As much as I love speculating, enough theory. Let’s talk about what to actually do (because at some point, we all need to translate insights into action plans that make our managers and stakeholders happy; you’re welcome in advance).

The Multi-Surface Search Approach

The biggest mistake I see marketers make right now? Choosing between traditional search and AI search as if it’s an either/or decision. Spoiler alert: it’s not.

1. Don’t abandon traditional search: Google still drives the majority of search traffic for most brands. Your traditional SEO and SEM fundamentals remain crucial.
2. Expand intelligently: Layer in AI search optimization where it makes sense for your audience. If your customers use ChatGPT for research (and statistically, 23% of US adults have used ChatGPT), you need to be visible there.
3. Consider social search: Reddit, TikTok, and Instagram are search engines for Gen Z and increasingly for Millennials. If your audience is under 40, social search optimization isn’t optional.

The bottom line is, integration is key: Your SEO, AEO, and SEM strategies should inform each other. The keyword research feeding your SEO should also guide your AEO content structure. The high-converting landing pages from SEM should incorporate schema markup that helps AI citations.

Content Strategy for 2026 Search

I’ll keep this section short (we writers spend our days reading, so I’ll lighten the load); let’s talk about what actually works right now:

1. Depth over breadth: One comprehensive, expert-level guide beats ten shallow blog posts every time. AI systems and traditional search algorithms both reward thoroughness. Create content that genuinely answers questions completely, not content that aims for word count.
2. Authority signals matter more: H-E-E-A-T isn’t just a Google thing anymore. AI systems evaluate source credibility, author expertise, and content authority. Include author bios with credentials, cite credible sources, and demonstrate real expertise rather than regurgitated information.
3. Structured content: Use clear headers (H1-H4) that directly answer questions, implement proper semantic HTML for both traditional and AI crawlers, and create FAQ sections that AI systems can easily parse and cite.
4. Citation-worthy stats: Original research gets cited consistently. This is why we invest heavily in research at Goodie: proprietary data creates citation opportunities that competitors can’t replicate.
5. User experience is non-negotiable: As we covered in our article on UX and SEO, user experience directly impacts search visibility. Fast load times, mobile optimization, and intuitive navigation benefit both human users and AI crawlers.

Technical Foundations That Work Across All Search

In a rare case of “this one is staying mostly the same,” some technical optimizations benefit every type of search simultaneously:

1. Schema markup and structured data: Helps traditional search engines understand your content and helps AI systems parse information accurately. Implement Product schema for eCommerce, Article schema for content, Organization schema for brand information, and FAQ schema for question-based content.
2. Site speed and Core Web Vitals: Important for traditional SEO rankings and for AI crawler efficiency (more on this in a second).
3. Mobile optimization: Most search (both the traditional and AI varieties) happens on mobile devices. Responsive design isn’t optional.
4. Crawl budget optimization: This one’s crucial and often overlooked. As we discussed in our article on faceted navigation SEO issues, don’t waste crawl budget on duplicate or low-value pages.

Here’s why this matters for AI: LLM crawlers are notably less powerful than Google’s crawlers. They have more limited crawl budgets and miss pages more easily unless specifically pointed to them. Optimizing your crawl budget benefits Google and improves your chances of being indexed by AI systems. Clean URL structures, proper canonicalization, and strategic noindex directives all help.

What Success Looks Like in 2026 (Redefining Search Marketing KPIs)

Remember that scenario from the introduction, where clicks were down, but conversions were up? Let’s talk about how to explain that to your boss (and yourself).

Moving Beyond Clicks

The old metrics dashboard focused heavily on rankings, impressions, and organic traffic. These metrics still provide value, but they’re directional indicators rather than definitive success measures.

The new metrics dashboard incorporates:

Traditional Metrics

• Rankings (directional indicator of visibility)
• Impressions (directional indicator of reach)
• Organic traffic from Google and Bing

AI Search Metrics

• Citation frequency across ChatGPT, Perplexity, Gemini, Claude
• LLM referral traffic properly attributed in GA4
• Brand search lift (people discovering you in AI, then searching directly)

Paid Metrics

• ROAS (Return on Ad Spend)
• Conversion rates from paid channels
• Quality Score and impression share

Universal Metrics

• Engagement metrics (time on page, scroll depth, pages per session)
• Conversion rates and assisted conversions
• Customer lifetime value and revenue attribution

If you’ve read our article on how SEO KPIs are changing, you already know this: the metrics haven’t disappeared, they’ve evolved. Context matters more than absolute numbers.

Attribution Complexity

Here’s the uncomfortable truth: accept that the funnel is fragmented. In the time of The Great Normalization, users don’t follow linear paths anymore. They bounce between traditional search, AI platforms, social media, and direct navigation in unpredictable patterns (humans, amiright?).

To cut through the chaos, here’s a practical framework for holistic measurement:

• Track visibility holistically: Where does your brand appear across all search surfaces? Is it on traditional SERPs, in AI Overviews, ChatGPT citations, Perplexity recommendations, Reddit discussions, or TikTok search results? Map your complete visibility footprint.
• Measure business outcomes: Are you driving qualified leads? Are those leads converting? Is revenue growing? Sometimes the best metric is the simplest: is the business getting results?
• Monitor brand health: Are people finding and remembering you? Track branded search volume, direct traffic trends, and brand mention sentiment across platforms.

The winning approach isn’t perfect attribution (if you still believe it is, I’d like one ticket to whatever fantasy land you live in). It’s understanding that visibility drives awareness, awareness drives consideration, and consideration drives conversion; even if the path between them is messy.

Common Search Marketing Mistakes to Avoid in 2026

Let’s rapid-fire through the mistakes I see most often (so you can avoid them and be the genius that you are):

1. Ignoring AI search entirely: Your competitors are already optimizing for it. By the time AI search is “mainstream,” you’ll be playing catch-up with established players who’ve spent years building citation authority.
2. Abandoning traditional SEO: It’s still the foundation; you can’t skip steps. The marketers succeeding in AI search all built strong traditional SEO first.
3. Obsessing over vanity metrics: Rankings and clicks tell an incomplete story in 2026. Focus on engagement, conversions, and business outcomes.
4. Not adapting measurement: Using 2022 KPIs for 2026 search leads to misread performance. Update your dashboards, educate stakeholders, and redefine success metrics.
5. Siloing strategies: SEO, SEM, AEO, and social media should work together, not in isolation. Break down team silos and create integrated strategies.
6. Forgetting the human element: AI-generated content without genuine expertise won’t win in traditional OR AI search. Both reward authentic expertise and original insights.

Tools & Resources for Modern Search Marketing

You didn’t actually think I’d monologue for this long and then leave you without a resource list, did you?

• Traditional SEO: Ahrefs (keyword research and backlink analysis), Semrush (competitive analysis and rank tracking), and Google Search Console (performance monitoring and indexing insights).
• AI visibility tracking: Goodie for monitoring citations across ChatGPT, Perplexity, Gemini, and Claude (yes, shameless plug, but it’s genuinely the best tool for this).
• Analytics and attribution: GA4 with custom channel groupings to properly track AI referral traffic (there’s a guide for how to set that up here).
• Paid search platforms: Good ol’ Google Ads and Bing Ads for traditional paid search (at least until the inevitable happens).

Knowledge resources:

• NoGood blog for search marketing strategy and case studies
• Goodie research for AI search data and visibility insights
• Search Engine Land for breaking industry news

Conclusion: The Future Is Already Here

If you’re feeling overwhelmed by how much search has changed, I urge you to delay the panic attack and hear me out: the good news is that the fundamentals haven’t disappeared. They’ve just expanded.

Search marketing in 2026 has evolved beyond Google rankings and paid ads. AI search engines have fundamentally changed how users find information, creating new opportunities and challenges for brands. The winning strategy combines traditional SEO foundations, emerging AEO tactics, and (soon) paid AI placements.

Success metrics have evolved: citation frequency, engagement quality, and brand authority matter as much as clicks. The funnel is fragmented, attribution is messy, and the platforms keep changing. But underneath all that complexity, the core principles remain: create genuinely valuable content, build authentic authority, meet users where they’re searching, and measure what actually matters to your business.

The marketers who win in 2026 are the ones who:

• Build strong traditional SEO foundations that support all other efforts
• Adapt content strategy for AI citations and conversational search
• Stay ready for paid AI search opportunities as they emerge
• Measure success holistically across all search surfaces
• Remain flexible and keep learning as platforms evolve

One final note: search marketing isn’t dead. It’s just evolved into something bigger, more complex, and honestly, more interesting than it’s ever been. The opportunity is massive for marketers willing to adapt.

And if you’re reading this and thinking, “Wow, I really need to future-proof my search strategy,” NoGood’s search marketing team specializes in integrated SEO, AEO, and SEM strategies that work across traditional and AI search engines.

Let’s talk about where your brand shows up in 2026.