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A brand’s visibility in ChatGPT is not an indicator of visibility across AI.  Different LLMs rely on different data sources, models and ranking signals, meaning a brand can perform well on one platform and remain virtually invisible on another.

Common platforms such as ChatGPT, Gemini, Claude, Perplexity and Copilot rely on different combinations of models, training data, search infrastructure, source selection, ranking signals and retrieval methods. As a result, the same brand can be highly visible for a relevant query in one platform and virtually absent for a similar query in another.

For marketers, this requires a shift in how AI visibility is measured. Rather than focusing on overall visibility, marketers need to understand where their brands appear, where they are absent and which AI platforms matter most to their customers.

AI visibility is not one ranking system

The temptation to treat answer engine optimization (AEO) as an extension of traditional SEO is understandable; both involve getting a brand or its content surfaced in response to a user’s query. But the similarities have limits.

Traditional search engines generally provide a ranked set of links. AI systems instead synthesize information from multiple sources, retrieve information from the live web, draw on their underlying model knowledge, or combine several of these approaches.

The algorithms behind these systems are proprietary and constantly evolving, so marketers cannot know precisely which signals determine every AI response. However, patterns across client work and industry research indicate meaningful differences in how major platforms surface brands and information. The effect of the varying approaches of the platforms:  strategy optimized for one AI environment may not produce the same result in another.

Here’s how the major AI platforms differ:

ChatGPT:  brand recognition is key

As the most widely recognized LLM and the source that drives 92% of LLM referral traffic, ChatGPT prioritizes trusted brands with strong entity recognition and draws heavily on third-party sources. Comprehensive, well-structured content plays an important role in improving a brand’s visibility within its responses.

ChatGPT places significant value on how well established and understood a brand is across multiple trusted third-party sources (e.g. Reddit, G2, Capterra, etc., for B2B brands). Consistent information about a company, authoritative third-party coverage, reviews, forums and other external references all contribute to a strong digital footprint.

For brands, that means AI visibility goes beyond content production to building authority and reputation. Brands that perform well often share several characteristics including strong recognition, credibility, consistent branding, and expertise in a specific subject area.

Gemini and Google AI Overviews: SEO still matters

Google’s AI experiences have the strongest relationship with traditional search optimization. Gemini and AI Overviews appear to place substantial weight on signals associated with traditional SEO, including organic visibility, topical authority, content quality and structured information.

This creates an important opportunity for organizations with a mature SEO program. Rather than building an entirely separate strategy for Google’s AI experiences, marketers can extend existing investments in technical SEO, content depth, site architecture and topical authority.

Of the major AI environments, AI Overviews currently have some of the clearest overlap with conventional search. That doesn’t mean traditional SEO and AEO are interchangeable, but Google’s AI ecosystem does provide one of the clearest examples of how strong search fundamentals can support AI visibility.

Claude: Depth, accuracy and technical authority reign

Claude presents a somewhat different opportunity, particularly for B2B and technical brands.

Claude tends to surface clear, factual and in-depth material, including educational resources, documentation, research and other content designed to explain complex subjects,  making subject-matter expertise particularly important.

For technical and enterprise brands especially, content created primarily to capture search demand may not be enough. Brands should also bulid resources that demonstrate genuine knowledge in the form of detailed explanations, original research, technical documentation, frameworks and educational material.

The recent rollout of Claude’s web search capabilities mean that freshness and authoritative online sources are increasingly relevant. As AI platforms evolve toward real-time retrieval, the distinction between content optimization and broader digital authority will continue to blur.

Perplexity: the importance of live web searches

Perplexity behaves differently than most other LLMs because it leans heavily on live web searches and citations. Brands with strong PR, authoritative backlinks, and recent content have an advantage because those signals increase the number and quality of sources an AI search engine can discover and cite.

Freshness also matters more to Perplexity than many competing platforms. Publishing timely research, proprietary data, industry commentary, or newsworthy content can increase the likelihood of appearing in Perplexity responses. If your brand’s content is regularly cited by reputable publications, Perplexity is often one of the first places you’ll see that investment pay off in AEO.

Copilot: The continued influence of Bing

Microsoft Copilot’s connection to Bing is its differentiator. Because Bing provides much of the underlying search infrastructure, traditional Bing signals, including site authority, technical SEO, structured content and backlink strength, can influence which sources are surfaced.

For organizations that have historically optimized almost exclusively for Google, this is an important reminder: AI visibility can also expose gaps in a broader search strategy. For brands already investing in Bing Webmaster Tools and optimizing beyond Google, those efforts can translate directly into Copilot appearances. 

The common denominator: authority

Despite these differences, there is some overlap between LLMs. Across AI platforms, brands are more likely to benefit when they are credible, consistent, useful, authoritative and distinctive.

SEO remains an important foundation, particularly for Google’s AI experiences. But AI visibility depends on a broader digital footprint: content, reputation, third-party validation, entity recognition, technical accessibility and the ability to provide authoritative information that AI systems can retrieve and trust.

Stop optimizing for every LLM equally

One of the biggest strategic mistakes marketers can make is treating every AI platform as equally important. The right priority depends on the company’s audience, buying journey and industry.

For many B2B and SaaS companies, ChatGPT may be particularly important because prospects are adopting AI tools to conduct research, evaluate vendors and compare solutions. Claude may also warrant investment when a company’s audience relies heavily on AI for technical or enterprise research. For organizations whose customer journey begins in Google, AI Overviews may be a higher priority.

The best strategy is to allocate resources according to where the company’s customers are using AI to make decisions, which requires moving beyond aggregate AI visibility metrics. A brand that appears in four out of five AI platforms may look successful on paper, but if the one platform where it is invisible happens to be the one its highest-value prospects use most frequently, the aggregate number can be misleading.

How to approach an outlier

An outlier should not automatically trigger a complete strategy change. First, determine whether the platform represents a meaningful opportunity for the business. If a brand is performing well across the AI environments most relevant to its ideal customers, there may be little value in redirecting substantial resources toward a lower-priority platform. If the platform does matter, the next step is to diagnose the gap.

The diagnosis should focus on the brand’s priorities, including traditional search rankings, third-party sources, content freshness, and technical or educational depth. It should also examine where competitors are being cited and whether those sources represent gaps in the brand’s own digital presence.

The goal is to strengthen the specific signals that are missing in the AI ecosystem that matters to your business.

Measurement is the biggest challenge

Unlike traditional search rankings, AI responses are not static. The same prompt can produce different results at different times, and responses can vary based on the model, available web sources, user context and ongoing changes to the underlying systems, making AI visibility inherently directional.

Tools from established SEO platforms, as well as newer AEO-specific platforms, can provide useful visibility data, but there is not yet a universally accepted framework for connecting AI visibility directly to revenue. This uncertainty makes measurement more important, not less.

Without systematic tracking, marketers can easily overreact to anecdotal evidence. A single customer saying, “I found you on ChatGPT” is valuable qualitative feedback, but it can’t tell you whether your brand is consistently visible, which prompts produce that visibility, which competitors appear alongside you or which platforms represent the greatest opportunity.

Measurement structures for AEO work most effectively when they track visibility by platform, query type, competitor, citation source and trend over time.

The way forward

As AI platforms mature, their differences will become even more important. Some will behave more like search engines, while others will rely more heavily on model knowledge, retrieval systems, citations, user context or proprietary datasets.

As you adapt, make sure your strategy reflects AEO’s underlying principle: success ultimately depends on building visibility in the AI environments that customers rely on to research, evaluate and make purchasing decisions.

The post AI Visibility Is Platform-Specific. Your Strategy Should Be Too. appeared first on SiteProNews.

Why the Click is Dying and Consumers Let AI Do all the Shopping.

No one wants to do manual labor anymore. Consumer behavior has shifted from automatic browsing to delegating work to AI to do it for them. These days, we are all asking AI to research tasks, compare options for the best prices and better deals, and decide for us, and so businesses still optimized for the blue-link click are invisible in responses and buried, invisible.

I can attest to this on a personal level and have seen the behavior shift in myself as a marketing expert. For example, I use an AI assistant to do all of my shopping research, comparing options I would like based on my algorithm, and AI does everything for me including the final purchase, without me having to open a million tabs. Why is browsing becoming the exception and not the rule? The pattern becomes to create a laundry list of things I have to do and have AI decide for me and do them. Are we simply becoming lazy or too busy?

In 2026 alone, almost 65 percent of all Google searches end without a click while the average zero-click rate spikes to 83 percent when Google AI overviews appear. Consumers are quickly weaving AI into daily research and buying decisions.

AI Overviews has become our new bestie, they give us the answers before we have a chance to think on the results page. Chatbots don’t even use the results page. But in both cases, the takeaway is that no one will land on your website either way.

So have websites become obsolete in a sea of AI summary – is this the new first impression of you and your business? It seems that way. So let’s say I am searching for the best chef near me, AI will pull up an answer and not a list of links to click through. This means something. What is my takeaway here? “We spent twenty years optimizing for the click, but now that click is dying and the AI answer is becoming everything.”

So what can we do as small businesses to stay afloat amid the sea of AI summaries?

Answer-engine optimization (AEO) is key, so when you create and structure content, make sure you keep asking yourself, how do I structure this so AI can find, trust, and cite it with clear FAQs, direct answers, schema markup, making it easy for people and taking the guesswork out?

The importance of using reviews as training data. AI models depend on third-party reviews and mentions, so you have to build your reputation to be machine-readable, so every review counts, so make sure to ask customers for real reviews that will populate online.

Do great PR and get articles about you and your business online so that you become the business AI recommends so, if AI doesn’t mention you, you don’t exist.

What can you do as a first step? Claim and complete every business profile, publish helpful Q&A content, make your expertise quotable plainly and get yourself in the news by pitching reporters, build a Wikipedia page, create that Google knowledge panel, and you and your business have to show up everywhere.

How can we achieve this goal?

First of all, we use AI agents to support the admin work and as thought leaders to help us find things that we normally wouldn’t have or to speed up the process. Something for research that would have taken us 3 hours may now take us 20 minutes. This helps do more with greater more accuracy. We have AI agents on the team that work as team members, that help us update CRMs, tasks, and keep us accountable as well.

We rebuilt our own operations around this new movement, so we know how to build it for clients too. We show clients what the AI is doing and what it’s producing so that you get an inside look into how it all works and actually understand AI so you can work with it, not against it. I always say, “You can’t sell the future if you’re not living in it.”

So what can we take from all this? The businesses that will win in the next five years aren’t the ones with the prettiest websites. They’re the ones AI trusts enough to recommend. Audit how you show up in AI answers today by asking a chatbot about your category and see who it names. If it isn’t you, that’s your marketing plan.

“Your next customer isn’t Googling you. Make sure the AI knows your name.”

The post Your Next Customer Isn’t Googling You. They’re Asking AI. appeared first on SiteProNews.

In 1998, while working at Whistler Blackcomb in British Columbia, Dominique Bastien overheard guests complaining that they couldn’t take pictures through the scratched windows of the resort’s gondolas. At the time, replacing damaged windows was often the only option available to ski resorts, and Bastien wondered whether there was a better solution.

That observation became the starting point for a business she would spend nearly three decades building. What began as a small window restoration operation eventually developed into The Gondola Shop, a specialized company handling complete gondola restorations, custom fabrication, and projects for customers in multiple countries.

Bastien’s entrepreneurial journey is unusual in several respects. She entered a market with few established competitors or technical procedures, developed restoration methods through experimentation, and gradually expanded into services that extended well beyond her original business concept. Along the way, she navigated the challenges of operating in a predominantly male industry, establishing relationships with international manufacturers, and convincing major ski resorts to invest in restoration rather than replacement.

Creating a Market From Scratch

Bastien initially launched Sunshine Polishing with a business partner, concentrating on restoring acrylic and polycarbonate gondola windows. Although polishing plastic surfaces was nothing new, restoring large, curved transportation windows presented challenges that existing techniques did not adequately address.

The work required developing procedures that accounted for surface distortion, heat, pressure, and the durability of the finished product. Bastien and her team experimented with equipment, materials, and techniques until they established methods that could deliver consistent results across entire fleets.

“When you start a business in an industry that barely exists, there is no manual telling you what to do,” Bastien explains. “You have to figure out the technical side, the equipment, the pricing, and then convince customers that what you are offering actually works and is worth the investment.”

Winning customers was particularly challenging because gondolas are passenger transportation systems. Resort operators needed confidence in the quality and reliability of the work before allowing an outside company to restore their equipment.

Bastien also faced the additional challenge of establishing credibility as a woman in a field dominated by men. She recalls having to work harder to demonstrate her technical knowledge and convince prospective customers that her company could handle demanding restoration projects.

In 2006, she became the sole owner of the business, gaining greater freedom to determine its direction and pursue opportunities as they emerged.

As the company grew, Bastien noticed a recurring problem. Customers who hired her to restore scratched windows frequently had gondola cabins with faded paint, deteriorating seats, and damaged hardware. Restoring the windows improved visibility, but the cabins still looked decades old.

Rather than limiting the company to its original specialty, she expanded into painting, upholstery, hardware replacement, fabrication, and eventually complete cabin restoration.

In 2019, Bastien established The Gondola Shop to bring those services together under one business.

One of her most consequential decisions was developing the ability to perform much of the work in-house. Managing multiple contractors for a single restoration could complicate scheduling, quality control, and accountability. By expanding the company’s internal capabilities, she gained greater control over production and customer expectations.

That approach became particularly important as The Gondola Shop began handling larger, multiyear restoration programs. At Breckenridge in Colorado, for example, the company works on a fleet of 111 gondola cabins, with restoration scheduled in smaller groups so the resort can maintain operations.

For Bastien, managing such projects requires considerably more than technical expertise. Transportation, staffing, materials, production schedules, and customer budgets all need to be coordinated, sometimes over several years.

Growing Beyond the Ski Industry

International business opportunities developed largely through relationships rather than a formal expansion strategy.

The ski industry is relatively interconnected, with resort operators, equipment manufacturers, and technical specialists frequently working across countries. As Bastien’s reputation developed, those connections helped introduce her company to new customers and projects.

Working internationally also required adapting to different environmental conditions and business cultures. Gondolas operating in Switzerland face intense ultraviolet exposure, snow, and extreme cold, while equipment in Vietnam encounters heat, humidity, and other environmental challenges.

The business practices were equally varied. Bastien learned that establishing trust with customers in Japan or Europe could require different approaches from those she used in North America.

Her relationships with equipment manufacturers have become another important part of the company’s development. One example is CWA, a Swiss gondola cabin manufacturer within the Doppelmayr Group. After several years of working together, Bastien and the manufacturer have discussed a potential formal partnership to support CWA gondola cabins in North America.

For Bastien, those discussions represent a significant professional milestone.

“When I started almost 30 years ago, I was a small independent business restoring scratched windows,” she recalls. “Today, I am sitting at the table with one of the world’s leading manufacturers discussing how we could work together.”

Bastien has also found opportunities outside the traditional ski resort market by repurposing retired gondola cabins for commercial uses.

At Columbia Sportswear’s headquarters in Portland, Oregon, 10 gondola cabins restored by her company have been installed throughout the office, providing employees with spaces for private conversations, phone calls, and individual work.

Other projects have included converting retired gondolas into food-service cabins, including three used by a customer selling cookies at ski resorts.

These projects introduced the company to customers in hospitality, corporate offices, restaurants, and other industries. They also created a new avenue for growth beyond the seasonal demands of the ski business.

Repurposing gondolas requires considerably more than cosmetic restoration. Each project can involve electrical systems, ventilation, insulation, seating, accessibility considerations, and custom fabrication. Bastien was able to expand into these applications because her company had already developed the technical capabilities necessary to dismantle, restore, and modify existing cabins.

The Business Lessons Behind Nearly Three Decades of Growth

Bastien’s experience offers an example of how a business can develop around a highly specialized service that larger companies have overlooked.

Her early competitors were not necessarily other restoration businesses. In many cases, she was competing against the established practice of replacing damaged equipment. Building a viable alternative required demonstrating that restoration could deliver practical and financial value to resort operators.

As her company expanded, the challenges changed. Bastien had to move beyond handling nearly every aspect of the operation herself and develop a team capable of managing increasingly complex work.

“Today, some of the best improvements come from employees who look at a problem differently than I do,” she says.

The company’s future opportunities reflect the same willingness to adapt that shaped its early growth. Bastien sees continued demand for restoration, fabrication, inspections, and replacement components as ski resorts evaluate the cost of maintaining aging equipment. She is also pursuing opportunities to strengthen relationships with original manufacturers and expand the market for custom gondola applications.

Her entrepreneurial philosophy remains grounded in the practical problem-solving that launched the business. Rather than following a predetermined expansion plan, she allowed customer needs to reveal opportunities for new services, then invested in the capabilities required to deliver them.

“I started with scratched windows and a pretty simple idea in 1998,” Bastien says. “I never imagined it would become what it is today.”

Nearly three decades later, Dominique Bastien has built an international business in a field that offered little established guidance when she entered it. Her experience demonstrates how technical expertise, persistence, and the ability to recognize overlooked commercial opportunities can support the growth of a highly specialized company.

The post How One Entrepreneur Built a Business in an Industry That Barely Existed appeared first on SiteProNews.