Buffer is the AI’s top pick in 1 of 16 measured B2B categories and invisible in 15. Even where it leads, the engines do not agree: at best 5 of 8 name it first.contested
Where Buffer is a top pick, on average only 63% of the engines that answered agree on it. This report grades that as contested. A single-engine tracker would show you one of those views and call it your score. In this dataset, across all 16 categories, no tool is the unanimous pick of all 8 engines. The disagreement is not noise to average away; it is the real state of your AI visibility, and it is what every single-number tracker quietly hides.
Each row is a category where at least one engine ranks Buffer first. The dissent column is the honest part: the engines that recommend a competitor instead, on the same date.
| Category | Engines that agree | Engines that pick something else |
|---|---|---|
| Social media management | 5 of 8 | Llama 3.3 70B via Groq picks Hootsuite Cohere Command-A picks Hootsuite Llama 4 Scout picks Hootsuite |
These are categories Buffer genuinely competes in, where the engines list it but put someone else first. This is the gap a buyer asking an AI sees before they ever reach your site.
| Category | Your rank | Ranked ahead of you |
|---|---|---|
| Social media management | #2 | Hootsuite |
In these 15 categories, no measured engine surfaced Buffer at all. Some may be outside your market; the ones inside it are pure lost recommendation share.
Across all 16 categories, no single tool is the #1 pick of every engine. The "AI visibility" number a single-engine tracker shows Buffer is one engine’s view on one date; this report shows all 8.
This report is one dated capture, given to you at no cost. AI recommendations move every run and every week. The AI Visibility Tracker keeps score for you:
Each of 8 AI engines (Llama 3.3 70B via Groq, Cohere Command-A, Gemini 2.5 Flash-Lite, Perplexity, ChatGPT, Llama 4 Scout, GPT-OSS 120B, Qwen 3.6) answered the same buyer questions across 16 B2B and go-to-market software categories. Every recommendation is a recorded model output, canonicalized and scored by position-weighted frequency. Capture window 2026-06-19 to 2026-07-08.
The full dataset is published open under CC-BY-4.0 with DOI 10.5281/zenodo.20767878. This report states what the engines returned on the capture date. It does not judge product quality, and no vendor can buy a better number; the rankings are unpurchasable by design.