Article 001 · Research and customer discovery
Navigating search and AI recommendations
A clearer path for business owners and the customers choosing them
Running a business already asks a great deal of you. You should not have to spend every evening sorting through conflicting advice about search rankings, AI tools and the next marketing trend. You need to know what is changing, what it means for your business and which action is worth taking.
That is the purpose behind ATLAS. Like a useful map, it should help you understand where you stand and navigate toward your next decision. Our goal is to help your business be seen, understood accurately and considered for the right customer recommendation. A customer deserves the same clarity when deciding whom to trust.
Your customers are asking AI. Is AI recommending you?
What the evidence actually tells us
AI is already part of how some people research purchases and understand their options. Four sources help put that change in context. They measure different activities, so their percentages should be read separately.
PayPal: its October 22, 2025 survey announcement reported that 40% of Americans had used AI to assist with a purchase in the previous year. PayPal commissioned an online survey of 1,000 U.S. adults, conducted September 5 through 9, 2025. This is evidence about shopping assistance, not proof that AI completed the purchase. [1]
Plaid: its Spring 2026 report page states that 55% of people had used AI for money tasks in the previous 12 months, and 86% of AI users said it helped them understand money better. These figures concern financial activities, not the percentage of customers using AI to choose a local business. [2]
Adobe: its September 28, 2026 report states that AI driven traffic to retail sites grew 127% in August 2026 compared with August 2025. That is growth in traffic from AI sources, not a claim that 127% of shoppers use AI or that AI supplies most retail visits. [3]
Pew Research Center: its July 22, 2025 analysis found a traditional search result click on 8% of Google visits with an AI summary, compared with 15% without one. It studied browsing data from 900 U.S. adults. The comparison describes an observed pattern, not proof that AI alone caused fewer clicks. [4]
Our reading of this evidence is straightforward: owners need to pay attention to the answers customers encounter as well as the links they click. These studies do not establish one universal rate of AI adoption, predict your sales or measure ATLAS results.
Being found and being chosen are different questions
A customer might search for a plumber nearby, then ask an AI assistant which option is suitable for an urgent repair. The first question helps discover businesses. The second asks for a comparison and a reason to choose. The answer might discuss services, availability, location or evidence of expertise. Those details need to be correct.
Google helps you find information. AI helps you make sense of it. That is a useful way to explain the distinction, while remembering that search engines now include AI features too. SEO and AI visibility belong in the same conversation.
Search Engine Optimization, or SEO, helps search engines access and understand your website. AI Visibility Optimization, or AVO, examines how AI systems discover, describe and recommend your business. ATLAS AVOSEO is intended to coordinate both kinds of work while keeping their measurements distinct.
Google says its established SEO practices remain relevant to AI Overviews and AI Mode. Its guidance emphasizes accessible pages, useful text, internal links and current business information. Structured data should match the visible page. Google requires no special AI markup and does not guarantee inclusion. [5]
The practical starting point is information that clearly explains what you do and whom you serve. Search position, an AI mention, a citation, a recommendation and a sale are different outcomes. Being first on a list is only part of the picture.
The experience that helped create ATLAS
In July 2026, one of my own local businesses appeared among the top three results in the traditional searches I checked. Yet it did not appear in my initial AI search. How could customers find the store through search, but miss it when asking AI for help choosing a business?
That question helped motivate three months of work on ATLAS: helping small businesses and larger companies understand their AI representation, correct inaccurate or missing information, and work toward relevant recommendations.
In the first of two later recorded ChatGPT checks, a general customer question returned the local business second among the options listed. When asked which business it would recommend, ChatGPT favored that business for the customer need discussed. In the second check, ChatGPT listed the business first and again recommended it in the follow-up answer. Neither opening question named the business. Two additional checks I reported, including one by another person out of state, also included the business as a recommendation alongside another business. Across all four reported checks, the meaningful result was that the business was recommended for the customer need discussed.
These are observations involving my own business, not a representative study or proof that ATLAS caused the recommendations. We record the question, answer and context so the result can be understood accurately. Different questions, devices and sessions can return different answers.
The correct location needs the correct information
While researching my own business, I encountered an AI answer that used a historical finding about the corporate office when discussing my local store. As I reported it, the finding preceded the opening of my store by about three years. AI should distinguish the individual location from its parent company and assess whether a finding is valid and applicable to that local business. That means checking whom the source names, the dates involved and any documented connection to the local location. A finding about a parent company should not be presented as a finding against a local business without evidence supporting that attribution.
A franchise location, a corporate office and another store under the same brand are different subjects. Establishment dates, ownership relationships and source dates help explain that distinction. Sharing a brand alone does not establish that a local store committed a violation. Any relevant connection to current products or practices needs its own evidence.
Examples like this are part of the reason I created ATLAS AVO. Every business deserves an opportunity to be seen, understood and considered for recommendation using accurate information about that business. The correction should clarify who a finding concerns, when it occurred and what the source supports today. It should neither erase a relevant fact nor attach an unsupported allegation to a location.
What useful industry advice looks like
Connor Gillivan offers practical guidance beyond a single social post. In his April 14, 2026 article, he connects website foundations, customer questions, credible sources, user experience and measurement across Google and AI. In his August 8, 2026 article, he recommends checking realistic buyer questions across several AI systems, retaining dated results, opening cited sources and turning gaps into specific work. [6, 7]
These are practitioner methods, not independent proof that any provider guarantees a recommendation. The useful lesson is to investigate the actual answer and the information behind it. A listing, a website correction and a clearer explanation of a service may matter more than another subscription or a larger volume of generic content.
How to navigate your next decision
Start with the customer question. What would someone ask before choosing you? For a new business, the answer may depend on a clear opening status, service area and explanation of the work you offer. For an established business, it may involve qualifications, availability or a specific customer need.
Check the answer and its sources. Save the question, date, answer and links. Is the correct business named? Is the correct location described? Is the information current? A fresh session can reduce prior conversation influence, but no individual check represents every customer experience.
Choose the most useful correction. Prioritize information that could confuse a customer: an incorrect phone number, outdated service, missing qualification or finding attributed to the wrong location. Support the change with records. Publish it where customers can read it and search systems can access it.
A clear path needs follow through
Our goal is to help a business become visible, accurately understood and recommended for the customers it can serve. A relevant recommendation is a meaningful result whether the business is recommended first or alongside another suitable company. List position provides context, but it does not erase that result. We work toward relevant recommendations without promising first place, exclusivity or control over an AI platform’s answers.
Collect the evidence. Use it correctly. Fix supported problems. Prove what changed. Share the findings. That is the ATLAS approach. It includes implementing authorized corrections where we can and preparing clear owner actions where another party controls the information. We verify the correction and preserve the records before reporting the outcome.
Verify the work, then check again. A published correction is something we can verify directly. A changed AI answer is a separate observation. Keep the earlier evidence so comparisons remain honest. A private conversation does not automatically reach other AI users, and an AI platform decides which sources and answers it uses.
Ask for a clear explanation before paying for help. What problem was found? What will be corrected? Who can make the change? What evidence will show completion? What remains outside the provider’s control? Those questions help you judge whether a service fits your budget and needs.
You do not need to understand every tool to make a sensible decision. You do need a partner who explains the findings, respects your business and gives you a practical next step. When AI recommends a business, we record that result and continue looking for supported opportunities to improve its representation. AI answers and customer needs evolve, so each later observation should be compared with the evidence already collected.
For customers, the goal is just as simple: know more before you choose. Accurate information should help you compare suitable businesses and feel comfortable with the reasons for your decision.
Explore the business owner questions at atlasavo.com/blog/002-business-owner-questions/ or contact ATLAS through atlasavo.com/contact/. Start with your actual needs. The right path should be understandable before you commit to it.
Sources
1. PayPal holiday shopping survey announcement | October 22, 2025
2. Plaid State of Intelligent Finance | Spring 2026
3. Adobe 2026 Holiday Shopping Trends report | September 28, 2026; August observed traffic figure
4. Pew Research Center Google users and AI summaries | July 22, 2025
5. Google Search Central AI features and your website | Updated December 10, 2025; accessed October 12, 2026
6. Connor Gillivan How I Show Up on Google AND ChatGPT | April 14, 2026
7. Connor Gillivan AI already decided whether to recommend you | August 8, 2026
Observation basis: July starting point recalled by Kenneth Griffith; retained September 23 record and October 12 screenshots, plus additional device and out of state observations reported by Kenneth Griffith on October 12, 2026. Business names are withheld. These are observational examples, not a controlled comparative study.
Research context: PayPal’s methodology footnote describes AI percentages in relation to people who used or considered AI purchase assistance. Plaid’s public report page does not state its sample size or full methodology. Pew used March 2025 browsing records and collected corresponding search results in April. Adobe’s August figure is observed growth; its future holiday forecasts are not used here. Sources were checked October 12, 2026.