AI-First BDR, Internal Signals, Not LinkedIn Scrapes (L3)
Sendoso cut from 15 BDRs to 1, then rebuilt to 4-5 with AI. Pipeline went from <15% to >30% of total. The unlock: marrying Snowflake product usage + Salesforce closed-lost/champion history + UserGems, not the LinkedIn-scrape email everyone else sends. From Austin (Sendoso) on the GTM AI Podcast.
The steps
- 01
Take email off the BDR's plate
Tool: Manual change
BDRs only own: dials, LinkedIn DMs, real conversations, gifting. AI owns: every outbound email. Counterintuitive but it's what unlocked the 30% number. Email is an ad impression in 2026, humans don't scale on it.
- 02
Feed the agent INTERNAL signals
Tool: UserGems Gemini + Snowflake + Salesforce
Product usage from Snowflake. Closed-lost ops + previous-user history from Salesforce. Champion job changes from UserGems. The agent knows "Kevin used you 2 years ago at his old company", nobody else can write that email.
- 03
Seed with your best BDR's best emails
Tool: Manual + Gemini
Take your top performer's reply-rate winners. Tell the AI "do this, better." Continuously eval against actual reply rates and re-prompt. Sendoso's been doing this for 18 months.
- 04
Layer in SmartSend gifting on high-intent signals
Tool: Sendoso SmartSend
AI picks the gift (e.g., found prospect's dog on Twitter → hands-free leash) based on signal strength. BDR's queued dialer fires when the prospect replies positively.
- 05
Run the same motion for expansion
Tool: Same stack
Apply identical signal logic to existing accounts: usage drops, new contacts joining, champions leaving. The agent surfaces who to reach and why; AM/CSM dials.
Tools in this playbook
- Manual change
- UserGems Gemini + Snowflake + Salesforce
- Manual + Gemini
- Sendoso SmartSend
- Same stack
Next playbooks
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