Citena Explained: How to Win Customers with AI in 2025

The Rise of GEO

Citena monitors how AI-powered answers from ChatGPT, Perplexity, Claude, and Google have compressed the buyer journey. Customers ask a single question and receive a definitive answer—no ten blue links, no chance to pitch a better offer later in the funnel.

Generative Engine Optimization (GEO) recognizes that owning those AI answers is the new storefront. Citena makes sure your brand is the recommended option when customers ask for help, inspiration, or comparisons.

Unlike traditional search where users browse multiple results, AI assistants synthesize information and present a single authoritative answer. This means being mentioned in that answer is no longer optional—it's the only way to exist in the conversation.

The shift is happening faster than most teams realize. Recent data shows that over 40% of purchasing research now begins with an AI assistant, and that number is doubling every quarter. Brands that wait to adapt will find themselves invisible to an entire generation of buyers.

Key Differences Between GEO and SEO

Traditional SEO rewards authority and backlinks, but GEO rewards structured evidence. Models look for consistent brand narratives, recent third-party validation, and human-sounding proof points.

Unlike SEO, GEO outcomes are probabilistic. The right feature snippet might appear for 20% of queries today and 2% tomorrow. Winning requires more experimentation and instrumentation around model-specific behaviors.

Where SEO focused on keywords and meta tags, GEO demands semantic clarity. AI models need to understand not just what you do, but why customers choose you, what problems you solve, and how you compare to alternatives. This means your content must be structured for machine comprehension while remaining genuinely helpful to humans.

Another key difference is velocity. Search rankings change slowly over months. AI model training cycles mean your visibility can shift overnight when a new model version launches. This demands continuous monitoring and rapid response capabilities that most marketing teams haven't built yet.

A GEO Playbook for Growth Teams

Start by auditing the questions that matter most for your category. For each query, evaluate who appears, what evidence they cite, and how fresh the response is.

Next, orchestrate updates across your owned and earned channels. Press, analyst notes, documentation, and customer proof need to reinforce the same core story so that assistants have no alternative but to cite you.

Create a content calendar that aligns with how AI models learn and update. This means refreshing key messaging quarterly, publishing case studies with measurable outcomes, and ensuring every product launch includes AI-optimized assets that partners and press can reference.

Build relationships with the sources AI assistants trust most. Industry analysts, trade publications, and authoritative review sites carry outsized weight in model training. A single mention in the right publication can shift your visibility across multiple assistants overnight.

Finally, instrument AI assistants as a new performance channel. Track impressions, adoption, and conversion lift from assistant-sourced traffic to prove the business case internally. Treat this like any other growth channel with clear KPIs, regular reporting, and dedicated ownership.