Sales Development Agent

AI sales rep that remembers prospect interactions and personalizes outreach

intermediateTechnologysalescrmoutreachlead-qualification

Overview

A sales agent with memory transforms cold outreach into warm, contextual conversations. By remembering every interaction, researching prospects, and learning what messaging resonates, the agent becomes an increasingly effective sales development representative.

Memory Components

Prospect Intelligence

Building rich prospect profiles:

  • Company information and recent news
  • Individual contact details and role history
  • Past interactions across all channels
  • Expressed interests and pain points
  • Buying signals and timeline indicators
  • Conversation History

    Every touchpoint remembered:

  • Emails sent and responses received
  • Call notes and outcomes
  • Meeting summaries
  • Objections raised and how addressed
  • Commitments made by both sides
  • Pattern Learning

    Understanding what works:

  • Email templates with highest response rates
  • Best times to reach each prospect
  • Messaging themes that resonate by persona
  • Common objections and successful rebuttals
  • Deal Context

    Current opportunity status:

  • Stage in sales process
  • Key stakeholders and their positions
  • Competitive alternatives being considered
  • Budget and timeline constraints
  • Next steps and blockers
  • Sales Workflows

    Personalized Outreach

    "Draft an email to the VP of Engineering at Acme Corp"

    With memory:

  • Knows they downloaded your API docs last week
  • Remembers the CTO attended your webinar in Q2
  • Notes their recent funding round
  • Aware of competitor evaluation mentioned in past call
  • Meeting Preparation

    "Prepare me for my call with Sarah at TechCo"

    Agent provides:

  • Summary of all past interactions
  • Her stated priorities and concerns
  • Recent company news and triggers
  • Suggested talking points based on stage
  • Questions to advance the deal
  • Follow-up Sequencing

    Intelligent next-step planning:

  • Optimal timing based on past responsiveness
  • Content relevant to last conversation
  • Escalation when engagement drops
  • Multi-threading to other stakeholders
  • Objection Handling

    "They said they're happy with current solution"

    Agent recalls:

  • Specific pain points mentioned earlier
  • Success stories from similar companies
  • This objection raised by others and what worked
  • Champion who might help navigate
  • Integration Points

    CRM Sync

    Bidirectional memory with your CRM:

  • Pull existing contact and account data
  • Push new interaction summaries
  • Update deal stages automatically
  • Enrich with external data sources
  • Email and Calendar

    Full communication context:

  • Parse incoming emails for intent
  • Draft contextual responses
  • Schedule meetings with relevant prep
  • Track commitments and deadlines
  • Sales Intelligence

    External data enrichment:

  • Company news and triggers
  • Funding announcements
  • Leadership changes
  • Technology stack information
  • Example Scenario

    **Day 1 - Initial Outreach:**

    "I see Acme Corp just raised Series B - congratulations! Given your growth trajectory, infrastructure scaling often becomes a priority. Would love to share how similar companies have approached this..."

    **Day 14 - Follow-up:**

    "Following up on my note. I noticed your team posted a job for a DevOps lead - often a sign you're investing in infrastructure. Happy to share some patterns we've seen work well..."

    **Day 30 - After Response:**

    "Great speaking with you, James. As discussed, I'm sending over the case study from TechCo who had similar Kubernetes challenges. For the security review Maria mentioned, I've attached our SOC 2 report. Let me know what questions come up..."

    Metrics Impact

  • Higher response rates from personalization
  • Shorter sales cycles from continuity
  • Better qualification from memory accumulation
  • Increased deal size from thorough discovery