Your Next Customer Might Not Google You | Studio UNA

2 November | Studio UNA

Imagine a customer looking for a new skincare routine. They have sensitive skin, a limited budget, and zero interest in spending an hour comparing ingredients, reviews, and product claims.

A few years ago, they would have opened Google, searched for "best moisturisers for sensitive skin", clicked through several beauty publications, scanned user reviews, and eventually landed on a brand's website.

Today, they ask an AI tool:

"I have sensitive, dehydrated skin. Recommend three moisturisers under £30 that are fragrance-free, explain the differences, and tell me which is best for everyday use."

Instead of a page of links, they receive a tailored comparison, a three-product shortlist, and clear reasons to choose one over another.

For consumers, this is convenient. For brands, it fundamentally changes the game: it is no longer only about whether a customer can find your website; it is about whether your brand enters the conversation at all.

This shift is already reshaping commercial behaviour.

Adobe reported that traffic from generative AI tools to US retail websites rose by 693.4% during the 2025 holiday shopping season. While total user numbers remain modest, the trajectory is clear: AI is becoming an established engine for product research and discovery.

Traditional search is not dying, but the route from a customer question to a shortlist is expanding. For brands, this creates a new strategic imperative: How do you become the answer an AI system considers relevant enough to recommend?

1. From Searching for Options to Asking for Answers

Traditional search requires consumers to do the heavy lifting: enter a query, scan links, evaluate sources, and compare websites manually. AI-assisted discovery compresses these steps into a single, iterative conversation.

A customer can state their budget, explain their preferences, request alternatives, and demand a final recommendation without ever starting a fresh search. Google’s AI search features and ChatGPT’s shopping integrations are engineered specifically around this needs-led behavior.

Consumers are rarely looking for the loudest brand or the biggest ad budget instead they are looking for the precise fit for their situation.

Consider three people shopping for a face serum:

• Shopper A: Wants a simple routine under £20.

• Shopper B: Demands a specific active ingredient backed by clinical science.

• Shopper C: Seeks a luxury, sensorial experience with high-end packaging.

All three operate in the same category, but their purchase drivers are entirely distinct. AI-driven recommendations respond directly to these micro-needs. Brands that clearly communicate what they offer, who they serve, and why they are relevant build a far better foundation for recommendation.

THE STRATEGIC SHIFT: Brand discovery is moving from keyword matching to needs-led conversation. Understanding your customer is still essential, but making that positioning explicitly visible online matters just as much.

2. The Shortlist Effect: The Competition Starts Before the Click

When consumers scan traditional search engine results pages (SERPs), they stumble across peripheral options, niche businesses, and unexpected links.

When AI generates a response, consumer attention is concentrated entirely on the shortlist provided.

If a shopper asks for three independent fragrance houses offering distinctive scents under £100, the AI selects brands with clear product specs, transparent pricing, and accessible online data. A competitor making equally exceptional fragrances but lacking structured, clear online information remains absent.

That absence doesn't automatically mean bad SEO or poor products; AI responses fluctuate by platform, prompt, and available data index. But the commercial reality is stark: If you are excluded from the shortlist, you never get the chance to earn the conversion.

This is a critical vulnerability for emerging beauty, fashion, and lifestyle labels. Broad positioning makes brands invisible. Specific positioning gives both human shoppers and AI algorithms something concrete to evaluate.

3. The Visibility Gap: Discoverable vs. Recommendable

A brand can invest heavily in glossy campaigns, high-budget social assets, and beautiful web design while leaving basic functional questions unanswered:

• What exactly does the product do?

• Who is it formulated for?

• What makes the formula different?

• What evidence supports its claims?

Describing a serum as "the ultimate glow essential" might sound poetic in a campaign line, but it fails to communicate key ingredients, skin compatibility, or functional utility.

An informative description explains the product's primary purpose, key actives, routine placement, and realistic results. Creative brand voice should elevate factual information, not replace it.

Google’s official guidance confirms that core SEO fundamentals still apply to AI features in Search. There is no secret technical backdoor for inclusion in AI Overviews; it relies on structured, useful content and credible web authority.

Clear information helps customers evaluate. Distinctive positioning gives them a reason to buy. Brands require both.

4. Your Website Is Only One Part of the Ecosystem

Consumers do not form buying decisions solely through brand-owned channels. They rely on independent reviews, creator demonstrations, retailer listings, and community discussions. AI tools synthesize this broader web of information to build recommendations.

Consider two beauty brands selling £35 treatments:

• Brand A: Has a beautiful direct-to-consumer (DTC) website, but its product descriptions vary across retail partners, ingredient details are hidden, and independent press coverage is non-existent.

• Brand B: Features consistent product specifications across all stockists, verified customer reviews, and clear editorial coverage explaining its formulation philosophy.

Brand B provides a far more coherent, verifiable body of information for both customers and discovery systems to draw upon.

Reputation is no longer just a PR metric; it is functional data. Claims around ingredient performance, materials, and clinical results must stand up to external scrutiny across the wider web.

5. The Zero-Click Challenge: When the Customer Never Visits

Historically, website traffic was the primary metric of digital marketing performance. A user searched, clicked, landed, and converted.

AI summaries interrupt this linear funnel. A consumer may obtain enough comparative information to make a decision without ever clicking through to a brand's website.

Pew Research Center analysis revealed that users who encountered a Google AI summary clicked a traditional search link in just 8% of visits (compared to 15% when no summary appeared). Direct clicks on links inside the AI summaries occurred in only 1% of visits.

Visibility no longer automatically translates into immediate web traffic. A customer might discover your brand through an AI comparison, recognise it later on a retail shelf, or search for it directly weeks later.

To adapt, brands must widen their measurement frameworks beyond basic site sessions:

• AI Referral Traffic: Tracking traffic quality and conversion behavior from identifiable AI platforms.

• Brand Consideration Visibility: Auditing whether your brand appears when target customers test relevant, needs-based prompts.

• Accuracy & Sentiment: Monitoring whether AI tools describe your product utility, price points, and positioning accurately.

• Commercial Impact: Tracking changes in direct branded searches, qualified enquiries, and overall sales velocity.

6. What Brands Should Do Now: A Practical Playbook

Answer Engine Optimisation (AEO) and Generative Engine Optimisation (GEO) are fast becoming industry buzzwords. However, no software or agency can guarantee permanent placement in AI answers. Long-term advantage comes from mastering the fundamentals.

1. Make Your Positioning Unmistakable

Ensure a first-time visitor or a web scraper can understand what your brand does, who it is for, and why it exists within two sentences. Strip out vague, filler language from your homepage, product pages, and retailer listings.

2. Build a Factual Product Base

Product pages must provide accurate product names, full ingredient/material lists, exact sizing, usage instructions, and transparent pricing. Where supported, deploy structured schema data correctly.

3. Answer Real Customer Questions

Move beyond broad keywords. Identify the friction points, comparison questions, and objections your customers face before buying. Build clear, highly informative guides, ingredient breakdowns, and comparison pages that resolve these specific queries.

4. Cultivate Credibility Outside Owned Channels

Focus on genuine external validation: encourage authentic customer reviews, maintain consistent product descriptions across wholesale partners, and build relationships with credible creators and industry press.

5. Audit Your AI Presence

Run simple, routine prompts across major AI tools to test your category visibility:

• "Which independent brands offer fragrance-free moisturisers under £30?"

• "What are the best structured leather totes for work under £300?"

Document whether your brand appears, how it is framed, which competitors share the space, and which sources are cited. Use missing details to fix gaps on your owned and wholesale channels.

6. Never Stop Building Brand Equity

Optimising for discovery platforms is only half the equation. Algorithms process information, but humans buy based on emotion, identity, aesthetics, and trust. Factual product details make a brand easy to evaluate; emotive storytelling and world-building make it desirable.

7. The Real Competitive Advantage: Being the Right Answer

AI-driven discovery does not level the playing field, it shifts the battleground.

Mass-market labels bring high volume and broad recognition; niche brands bring sharp, highly specific relevance. The competitive advantage belongs to brands that define their purpose clearly and make that purpose effortless to discover.

Instead of asking: "How do we rank for this keyword?"

Start asking:

• "What specific problem is our customer trying to solve?"

• "What makes our product the most credible choice for that need?"

• "Is our positioning clear enough to be distinguished from our competitors?"

The channels will continue to evolve. The need for clear brand positioning, verifiable evidence, and a compelling reason to be chosen remains unchanged.

THE VERDICT: UNDERSTOOD, TRUSTED, CONSIDERED

The next era of commerce will not be won by technical tricks, volume posting, or inflated ad spend. It will favour brands that make themselves easy to understand, simple to evaluate, and worth choosing.

AI may shape the shortlist, but it does not remove the need for strong brand strategy. If anything, it makes it paramount.

For STUDIO UNA, the key insight is simple: the challenge is no longer just to be found online. It is to be understood, trusted, and considered at the exact moment the customer is ready to buy.