Step 1
Research Agent reviews the data
AI Agent
Agents used
AI Agent Recipe
Discover which accounts are talking about your products, what they care about, and who to engage.
What this recipe gets you
Solves for missed product interest mentioned in conversations, scattered across calls, emails, and stakeholder activities.
CLARITY
Catch intent the moment it surfaces
Buried mentions get pulled into one clear view, so you know which accounts are leaning in on a specific product.
ACCURACY
Reach accounts most likely to buy
When you can see what's being discussed and who's driving it, you can prioritize those already showing interest.
RELEVANCE
Ground your pitch in real data
Each summary shows the themes and sentiment, so you can lead with what matters and keep the discussion moving forward.
How it works
Outreach connects to the CRM and tools your team already uses, then layers on an AI agent that pulls together the context a rep would otherwise dig for manually. Here's the full path, from disconnected insights to a structured product discussion summary your team can use.
1
Research Agent reviews the data
AI Agent
2
A structured summary is delivered
Action
It analyzes calls, emails, and activity tied to the account, picking out every mention of the product, noting who raised it, and how the conversation went.
The agent returns one structured view of how often the product came up, what's driving the interest, who's involved, and the overall sentiment.
See the recipe in action
Book time to see your AI agent recipes in action and explore how they can help your team drive predictable revenue with Outreach.
Configuring your agents is easy
In Outreach, you set up an agent once using plain-language instructions. No code required. You tell it what to look for and what to produce, and the agent turns a stack of activities into key insights you can actually use.
FAQ
Where does the agent find product demand signals?
The Research Agent monitors: social media mentions, industry forums, internal conversations your team hears about, customer reviews and comparisons, job postings mentioning product skills (e.g., "experience with Salesforce" in the context of a new hiring spree), and news articles about company initiatives.
How does discussing a product translate to sales opportunity?
If an account is talking about your product, they've likely evaluated it or at least know it exists. This is a strong buying signal. They're either (a) building a business case to buy, (b) trialing it, or (c) considering it as an alternative to their current tool. All three are sales-ready moments.
Should I reach out directly or do research first?
The recipe does research first. It identifies the account AND the likely stakeholder (the person discussing the product), then surfaces this to your sales team with context: "This account mentioned us in a [channel/source] on [date]. Here's what was discussed..." Then your team can reach out more intelligently.
What if they're discussing us negatively?
The recipe captures sentiment. Negative mentions are lower-priority leads but still worth following up on: you get to understand objections and possibly turn a critic into a customer by addressing their concerns. Sometimes skeptics become the most loyal customers.
How often are new demand signals found?
Depends on your product category and visibility. Popular enterprise products see 2-5 new mentions per day; niche products might see 1-2 per week. The recipe monitors continuously and flags high-priority signals in real time.
How much pipeline can this source generate?
It's a supplementary channel, not your primary one. But accounts actively discussing your product are 3-5x more likely to convert than cold outreach. Most teams source 10-20% of their pipeline from these "warm" demand signals.
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