Happy Triple Threat Thursday!
Here’s one Signal to notice, one Spark to try, and one Shift to consider.
📡 Signal — What’s Changing
AI-driven self-service is overtaking direct seller calls.
Buyers now complete the first 40 to 60 percent of their purchase journey without ever speaking to a person. The old demo-first motion is being replaced by search-then-decide. But the search is no longer on Google. It is inside ChatGPT, Claude, and Perplexity, where buyers ask a question and expect a complete answer.
Ask those models: “What’s the best [your category] platform for mid-size teams?” and you’ll see a few predictable names. Maybe not yours.
Why it matters: If AI does not know you exist, buyers will not either. The next wave of visibility is no longer keyword-based. It is LLM-based. These models surface the brands they understand best. They favor clear, structured, and consistent information across the public web.
What to do this week
Run your own AI Search Test in ChatGPT, Claude, and Perplexity. Note whether your company appears and how it is described.
If you are absent or misrepresented, fix the source material: clear category definition, consistent messaging, and public citations.
Treat AI discoverability as the new SEO because that is exactly what it is.
If your brand cannot be found by AI, it will not be found by humans either.
⚡ Spark — What to Try This Week
If AI cannot find you, your buyers will not either.
A CEO I worked with recently put his company name into ChatGPT and asked, “tell me about my company.”
What came back wasn’t accurate. It described his old business model, the version he had abandoned a decade ago. Somewhere between rebrands, product pivots, and press cycles, the internet stopped learning who they are today. And since large language models learn from that same public data, they kept serving the outdated story.
That is the quiet danger of this new search era. When buyers ask AI who to trust, the answer depends entirely on what those models already believe about you.
The LLM Discoverability Audit GPT measures that gap. It runs a visibility audit, scores how accurately your company is represented across large language models, and tells you exactly how to improve.
Why It Is Worth Trying
Creates a measurable visibility metric for AI discovery, not just web traffic.
Builds a framework so your messaging and data feed AI systems the way they expect.
Delivers actionable improvement steps today, not in six months.
How to Use It This Week
Open the LLM Discoverability Audit GPT.
Enter your company name, website URL, and any other information you want to share.
Get your score out of 100 and review the suggestions. The GPT might tell you to:
Clarify your category definition across all public touchpoints so AI models recognize what you actually do.
Create a simple FAQ section on your website that answers five high-intent buyer questions in plain English. Each answer should be one short paragraph that AI can quote directly.
Strengthen your About page and LinkedIn descriptions with consistent, plain-language summaries of your value proposition.
Publish concise explainers, comparisons, or “how we’re different” pages that AIs can easily quote.
Encourage executives to update bios and public profiles so AI models have current reference points.
Bottom line: You are not optimizing for clicks anymore. You are training the internet to describe you accurately. If AI cannot name you in your category, you do not exist in it.
🔄 Shift — How to Rethink It
Default belief: More personalization equals better results.
Flip it: Better segmentation and clearer messages create more impact.
Personalization used to feel like progress. Add a name, a title, a little context, and conversions would follow. But in a world where buyers self-educate through AI and skim faster than ever, personalization is noise without clarity.
When every message tries to sound custom, none of them sound clear. And when your content shifts tone or focus with every audience, even AI struggles to understand what you stand for.
Why it matters: Large language models, like buyers, favor structure over style. They amplify consistent, well-defined messaging and ignore scattered variations. Clarity now scales better than personalization ever did.
How to apply it
Define your three core segments and write one crisp value statement for each.
Replace name-based personalization with contextual relevance such as industry or challenge.
Audit your last outbound campaign: could AI summarize your offer in one sentence? If not, simplify.
Keep your message consistent across every channel until both humans and AIs can repeat it accurately.
Clarity converts. Personalization distracts.
Thanks for reading Triple Threat. See you next Thursday with another Signal, Spark, and Shift.
— Alexandria Ohlinger
p.s. If you’re looking to build real growth systems as leverage inside your business, where people and automation work together, you can book a strategy session here to map the first steps.
And as always, I share quick insights on LinkedIn each week. Connect with me here if you’d like to follow along.