Personalized Sales Outreach
Scrapes verified B2B leads from Apollo, generates personalized cold emails via AI.
What it does
You save time finding prospects by automatically scraping verified B2B contacts from Apollo that match your ideal customer profile. The AI researches each lead to draft personalized cold emails for you, which are queued in Telegram for your final approval before sending via Gmail.
Step by step
- Configure the scheduled trigger to run at specific intervals for lead scraping.
- Set up API credentials and connection strings for Apollo, OpenAI, Gmail, and Telegram services.
- Define the data schema for passing contact details from Apollo to the LLM enrichment step.
Where the LLM does the work
- Generate personalized cold email copy that incorporates specific lead research insights.
- Evaluate scraped lead profiles against the Ideal Customer Profile criteria to filter relevance.
- Summarize company news or recent events to add a human touch to the outreach message.
Watch out for
Gmail sending quotas may be exceeded quickly, so batch emails and add delays between sends.
Telegram notification failures can cause lost approvals, so build a fallback queue or retry mechanism.
Tools that fit
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
You are helping me build the following AI agent workflow. ## Goal Personalized Sales Outreach: Scrapes verified B2B leads from Apollo, generates personalized cold emails via AI. ## Specification - What it does: You save time finding prospects by automatically scraping verified B2B contacts from Apollo that match your ideal customer profile. The AI researches each lead to draft personalized cold emails for you, which are queued in Telegram for your final approval before sending via Gmail. - Trigger: On a schedule (Scheduled · daily) - Autonomy: You approve along the way - Expected setup effort: about an afternoon - Tools/services involved: - Apollo: Lead scraping and verification - OpenAI Chat Model: Enriching leads with research and generating emails - Gmail: Sending approved cold emails - Telegram: Human approval of email drafts ## Known pitfalls, handle each one explicitly in your implementation 1. Gmail sending quotas may be exceeded quickly, so batch emails and add delays between sends. 2. Telegram notification failures can cause lost approvals, so build a fallback queue or retry mechanism. ## Reference implementation https://n8n.io/workflows/8523 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/automated-personalized-sales-outreach/ via usecasesforagents.com
Frequently asked questions
Can I use a different Data Enrichment than Apollo?
Yes. Apollo is only the example data enrichment in this recipe. The same flow works with BatchData API, Dumpling AI, influencers.club and PredictLeads API. Swap the data enrichment connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for founders and execs who need sales handled without hiring for it.
Sales teams can plug this into their own CRM and call cadence just as easily.