Case study: Sellers Umbrella
Getting an Amazon agency named in AI answers
How we track and improve how often AI engines recommend Sellers Umbrella, an Amazon ecommerce marketing and PPC agency.
- Client
- Sellers Umbrella
- Industry
- Amazon marketing agency
- Market
- USA
- Services
- AEO, AI visibility tracking, Entity and citations, Content
- 126
- AI answer mentions in 90 days
- 1.7
- average position when named
- 73/100
- sentiment in AI answers
The challenge
Sellers Umbrella is an Amazon ecommerce marketing and PPC agency. Its buyers increasingly ask AI tools which agency to hire for Amazon growth, and the answers tended to name a handful of larger competitors. The goal was to get Sellers Umbrella named and cited in those answers.
What we did
1. Prompt set and competitor benchmark
We built a set of prompts that Amazon sellers actually ask, such as which agency to hire for Amazon PPC or account management, and benchmarked Sellers Umbrella against five well-known Amazon agencies across the major AI engines.
2. AI visibility tracking
We set up ongoing tracking so every month shows which prompts mention Sellers Umbrella, which cite its website and which still favour competitors.
3. Answer-first service content
Service pages were planned around direct answers, clear pricing and proof, so engines have something specific and quotable to cite.
4. Entity and citation work
We aligned the agency’s brand facts across its site and profiles and targeted the comparison and list pages that AI engines cite for Amazon agency prompts.
Results
Measured with ZeroRank AI visibility tracking over the 90 days to 26 October 2026, across prompts Amazon sellers ask when choosing an agency:
- 126 mentions of Sellers Umbrella in AI answers.
- Average position of 1.7 when named, the best of the six agencies tracked.
- 73 out of 100 average sentiment when an answer names Sellers Umbrella.
When AI engines mention Sellers Umbrella, they tend to list it near the top. The work now is to appear in more answers, where larger competitors are still named more often.