Few things frustrate a B2B team more than asking ChatGPT about their own category and watching it list three competitors. Usually it isn't a verdict on the product. It's a verdict on the evidence available about it.
1. Fewer independent sources agree on you
If your brand only describes itself, AI models have little to go on. Competitors that appear in comparisons, community discussions, and expert content give the model several sources saying the same thing. That consistency is what earns a mention.
2. You're targeting the wrong questions
Lots of content answers informational questions ("what is SOC 2?") that never lead to a vendor recommendation. Buyer questions sound different: "best X for Y", "X alternatives", "X vs Y", "how much does X cost". Those are where shortlists form.
3. Your site doesn't hold up when checked
When a model looks at your site, can it tell quickly who you serve, what you do, and how you're different? Vague solution pages, missing comparisons, and no case studies make you hard to recommend with confidence.
4. Technical blocks
Sometimes the cause is mundane: a CDN or firewall rule blocking AI crawlers, key content hidden behind scripts, or pages that never get indexed. Worth checking before anything else.
Where to start
- List 20 to 40 real buyer questions for one offer and one buyer segment.
- Record who gets named for each today, across the engines your buyers use.
- Fix the gaps on your own site first, then build outside evidence around the same questions.