Recommender Agent
The Recommender Agent is a Genezio Agent type that simulates recommendation-seeking behavior in multi-step AI conversations.
It is designed for scenarios where a persona is trying to find a specific solution that fits their needs and constraints.
How It Works
For a Recommender Agent topic:
- the scenario defines the user situation and goal
- Genezio generates a sequence of prompts from that scenario
- the AI conversation runs across multiple turns
Example scenario:
John's team of three has been tracking leads in a spreadsheet but they are losing follow-ups as inbound volume grows. They need a simple CRM that integrates with Gmail and costs under $50/user/month.From this scenario, Genezio generates conversational messages such as:
User query: I run a small startup and we've been tracking leads in a spreadsheet, but it's not working anymore. What CRM tools would you recommend for a team of three?
User query: We need something that integrates with Gmail and stays under $50 per user per month. Which of those would fit?
Typical Use Cases
Recommender Agent conversations are useful when you want to evaluate:
- recommendation frequency for your brand
- how your brand is positioned against competitors
- how recommendations change after follow-up constraints
KPI Impact
Recommender Agent conversations are a core input to:
- AI Recommendations - percentage of Recommender Agent conversations where your brand is recommended
- Brand Visibility - included because brands are selected by the AI, not forced by prompt wording
Multi-Step Behavior
Multi-step flow makes this agent useful for realistic buyer journeys:
- initial broad recommendation
- filtering by budget, features, or team size
- shortlisting alternatives