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AI SEO | Brand Strategy | SEO Services
December 18, 2025 | Nikki Bisel
The rules of visibility are changing. Technical SEO got you here—but it won't keep you here.
For twenty years, search engine optimization has been a game of reverse engineering. Figure out what Google wants, give it to them, rank higher than the next guy. It was technical. It was measurable. And if you were good at the meta-game, you could win even if your actual business was mediocre.
That era is ending.
AI-powered search—Google's AI Overviews, ChatGPT's web browsing, Perplexity, and whatever comes next—is fundamentally changing how people find and evaluate businesses. And the companies that will struggle most aren't the ones with bad websites. They're the ones with a gap between what their marketing promises and what their customers actually experience.
In other words: AI search is going to punish companies that aren't easy to love.
Let's be honest about what traditional SEO became. It started as a reasonable premise—help search engines understand your content so they can match it with the right queries. But it evolved into something else entirely: a technical discipline where success was measured by rankings, not relationships.
Keywords. Backlinks. Site speed. Schema markup. Domain authority. None of these things require you to actually be good at what you do. They require you to be good at SEO.
And plenty of companies got comfortable there. They invested heavily in the optimization layer while letting the experience layer stagnate. It worked because search engines, for all their sophistication, were still essentially matching keywords to queries and measuring authority through links.
The system rewarded those who played it well, regardless of whether customers loved them or merely tolerated them.
Here's where I need to address something you've probably already heard from other agencies: "GEO is basically the same as SEO."
They're not wrong. Generative engine optimization absolutely requires the fundamentals—clean site architecture, authoritative content, proper structured data, fast load times. If you ignore those basics, you won't show up anywhere, AI-powered or otherwise.
But here's what that answer misses: those are table stakes for being findable. GEO also determines how you're described.
When a large language model synthesizes an answer about your category, it's not just checking whether you exist. It's making decisions about whether to mention you, how to characterize you, and whether to recommend you or your competitor. That decision pulls from sources you don't control: review sentiment, customer language, third-party mentions, forum discussions, social media patterns.
Technical optimization gets you into the consideration set. Reputation and experience alignment determine what the AI says about you once you're there.
Think about that for a moment. The AI isn't just returning your carefully crafted landing page copy. It's synthesizing what other people say about you and presenting that as the answer.
Large language models are trained on massive datasets that include reviews, forums, social media, news coverage, and yes, your website. But unlike traditional search algorithms that weighted your own content heavily, AI synthesis treats third-party signals as primary sources of truth.
Here's what that means practically:
Review sentiment matters more than review volume. A hundred 4-star reviews with recurring complaints about customer service tells a story. The AI reads that story. When someone asks "who's the best [your category] in [your market]," that story influences the answer.
Customer language becomes searchable. How do your customers describe working with you? What words do they use? If there's a gap between your brand messaging and how customers actually talk about you, AI picks up on that dissonance. You might say "white-glove service" while your customers say "they eventually got back to me."
Consistency across touchpoints gets weighted. AI models are getting better at understanding whether a brand's promise matches its delivery. They can cross-reference what you say on your website with what shows up in reviews, social mentions, and forum discussions. Inconsistency reads as a red flag.
Third-party mentions carry more weight. Being mentioned positively in industry publications, podcasts, or expert forums signals authority in a way backlinks never could. The AI understands context—it knows the difference between a paid placement and an organic recommendation.
Here's the uncomfortable truth: most companies have a gap between their marketing and their actual customer experience. Marketing says one thing. Operations delivers something slightly different. Sales promises. Support apologizes.
In the old search paradigm, this gap was manageable. Your website could project whatever image you wanted, and as long as you ranked, you'd get clicks. What happened after the click was a different department's problem.
AI search collapses that separation.
When an AI synthesizes information about your business, it's pulling from the entire customer journey—not just the part you control. It's reading what customers say on G2 and Trustpilot. It's picking up patterns in Reddit threads. It's noticing whether the promises on your homepage match the complaints in your support tickets (yes, some of those end up in training data through various paths).
The gap that used to be hidden is now visible. And visible gaps hurt your AI search presence.
I keep using this phrase—"easy to love"—because it captures something specific. It's not about being perfect. It's not about having the best product in every dimension. It's about alignment.
Companies that are easy to love share a few characteristics:
They know what they are and own it. They don't try to be everything to everyone. They have a clear value proposition and they deliver on it consistently. When customers describe them, the description matches what the company says about itself.
They make customers feel smart for choosing them. This is subtle but important. When someone recommends you, they're putting their own judgment on the line. Easy-to-love companies make their customers look good for recommending them.
They close the loop between promise and experience. What marketing says, sales confirms, operations delivers, and support reinforces. There's no cognitive dissonance in being their customer.
They generate genuine advocacy. Not incentivized reviews or referral bonuses—actual enthusiasm from people who've experienced the full customer journey and want others to have the same experience.
This isn't soft, squishy brand stuff. It's the hard infrastructure that AI search is learning to measure.
This is where brand strategy and customer experience converge with search visibility in ways that weren't true even five years ago.
Your brand makes a promise. Your customer experience either keeps that promise or breaks it. AI search is increasingly measuring the gap between the two.
Companies that have invested in understanding their customer journey—actually mapping the touchpoints, identifying the friction, aligning the experience with the brand—have been building the right signals without even targeting AI search. They were just trying to be better businesses.
Meanwhile, companies that treated marketing and operations as separate kingdoms are accumulating what I'd call "experience debt." Every broken promise, every inconsistent touchpoint, every gap between brand and reality is a liability that's about to show up in their search visibility.
If you're running a B2B company—particularly one in the $10M-$100M range where relationships and reputation matter enormously—this shift should have your attention.
Your buyers are increasingly using AI tools to research vendors. They're asking ChatGPT for recommendations. They're using Perplexity to compare options. They're reading AI-generated summaries before they ever hit your website.
What shows up in those summaries isn't just what you've published. It's what the market says about you. It's what former customers posted on LinkedIn. It's what industry analysts mentioned in podcasts that got transcribed and indexed.
For B2B specifically, a few signals carry outsized weight:
Case studies and results. Not the sanitized versions on your website—the full story that clients share when they're asked "how did that engagement actually go?"
Thought leadership that gets cited. Not content marketing for content marketing's sake, but genuine expertise that other people reference and build upon.
Employee advocacy. How your own people talk about working with clients. What they share publicly. Whether they seem proud of the work or just collecting a paycheck.
Client retention patterns. AI can increasingly infer relationship quality from various signals. Do your clients stick around? Do they expand? Do they refer?
Here's the part that's going to frustrate some people: there's no quick fix for this.
You can't hire an agency to optimize your way out of a customer experience gap. You can't buy backlinks that make customers love you. You can't keyword-stuff your way to genuine advocacy.
The fix isn't technical. It's operational.
If there's a gap between what your brand promises and what your customers experience, the solution starts with understanding exactly where those gaps are. That means actually mapping the journey—not the idealized version, but the real one. The one where things go sideways. The one where customers get frustrated. The one where the handoff between departments creates friction.
Only after you see the gaps can you close them. And only after you close them will the signals start to shift.
If you're reading this and feeling a bit of anxiety about your own experience gaps, good. That anxiety is useful. Here's how to channel it:
Audit your third-party presence honestly. Not just your star rating—read the actual reviews. Look for patterns. What do customers consistently praise? What do they consistently criticize? How does that align with what you think your brand is?
Map the real customer journey. Not the one in your marketing deck—the actual experience from first touch through delivery and beyond. Where are the handoffs? Where does information get lost? Where do customers have to work harder than they should?
Compare your messaging to customer language. Pull the words and phrases customers use when they describe you. Put them next to your brand messaging. If there's daylight between them, that's a signal worth understanding.
Identify your experience gaps. Every business has them. The question is whether you know where yours are and have a plan to close them.
Invest in alignment, not just optimization. The companies that will win in AI search aren't the ones with the best technical SEO. They're the ones with the tightest alignment between promise and experience. That's harder to build—but it's also harder to commoditize.
I've focused a lot on the risks here, but there's a genuine opportunity in this shift—especially for companies willing to do the work.
For years, search visibility could be bought or gamed. Well-funded competitors could outspend you on content production and link building. Agencies could play technical tricks that had nothing to do with business quality.
AI search is harder to game. It's reading signals that come from genuine customer relationships, real reputation, actual expertise. Companies that have been doing things the right way—investing in experience, building genuine advocacy, aligning brand with delivery—are about to see that investment pay off in search visibility.
The playing field is leveling. And it's leveling in favor of companies that are actually easy to love.
The era of winning search through technical optimization alone is closing. The next era rewards something different: alignment between what you promise and what you deliver.
AI search is essentially asking one question: "Would a knowledgeable person recommend this company?" And it's pulling from every available signal to answer that question.
If the answer is yes—if your customers genuinely love working with you, if your brand promise matches your operational reality, if you've invested in closing the experience gaps—you're positioned well for where search is going.
If there's a gap, if there's dissonance between marketing and experience, if customers tolerate you rather than advocate for you—that gap is about to become visible in ways it never was before.
The good news? You get to choose which company to be. And unlike traditional SEO, the solution isn't a budget exercise. It's a commitment to actually being worth recommending.
That's the work. And it's work worth doing.
Seafoam helps companies become easy to love—aligning brand strategy, customer experience, and digital presence so that what you promise is what customers actually get. If you're ready to close the gap, let's talk.
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