I'll find online mentions of your product from customer employees and flag potential advocates for a customer success story.
Your best case study candidates are often already praising your product online, but finding them takes hours of searching. This AI agent scans the web for employee mentions by account, scores advocacy signal, and flags top accounts with a story angle.

Per-customer update with new mentions and sentiment, delivered continuously or when you mention the agent.
Advocacy score with high-scoring accounts flagged for follow-up, delivered continuously or when you mention the agent.
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Customer success story angle and target persona, delivered continuously or when you mention the agent.
The agent confirms customer details against Salesforce and checks what has already been reported, so every run only surfaces new findings.
It searches for online mentions of your product by that customer's employees, expanding into localized terms for non-English market accounts.
Each mention gets a sentiment tag, and each person mentioned is classified as an advocate, decision maker, or power user.
It calculates an advocacy score from mention volume, recency, sentiment, seniority, and source quality, then flags high scorers to the account owner in Slack.
For strong candidates, it proposes a customer success story angle and the specific persona worth reaching out to first.