We scan new podcasts and send you the top 5 insights daily.
Instead of replacing third-party tools for initial emails, a custom-built agent excels at the follow-up stage. By integrating all first-party data (past event attendance, call transcripts, proposals), it crafts hyper-contextual follow-up emails that off-the-shelf tools cannot replicate.
Dramatically increase sales velocity and personalization by building an AI workflow that generates proposals. The agent pulls context from all past interactions, including meeting transcripts, to weave in specific personal details that a human would likely forget.
A powerful, untapped use case for AI is reviving neglected leads directly within your CRM. An agent native to Salesforce can access all historical data to send highly personalized follow-ups to thousands of leads your team previously ghosted, effectively turning forgotten data into new opportunities.
While many third-party AI outbound tools are effective for initial outreach, they fail when a prospect responds. Their inability to access deep, first-party customer data for context makes their automated follow-ups generic and ineffective, creating a major gap in the sales cycle.
The best use of AI in sales is not to automate generic emails, which can make reps lazy. Instead, it should be used as a research and efficiency tool to triple the number of hyper-personalized, human-centric calls a salesperson can make daily.
SaaStr built its own outbound agent capabilities because third-party tools are walled gardens, unable to ingest and leverage SaaStr's deep, first-party data (e.g., past sponsorship ROI). This "perfect email" level of personalization can't be bought and required a custom build.
Standard AI sales agents are limited to CRM data. A custom-built agent for renewals can outperform them by pulling from a company's entire data universe—website, social media, podcasts, even founder emails—to create hyper-personalized, context-rich pitches that third-party tools cannot match.
HubSpot observed that while sales reps enjoyed building their own prospecting agents, these DIY tools were consistently outperformed by centrally-built agents. The global versions benefit from superior context, data, and continuous evaluation, proving that institutional knowledge codified into a well-tuned agent delivers better results at scale.
A powerful two-stage workflow combines different AI tools. Use scalable, off-the-shelf AI SDRs for initial outreach to get a response. Once the prospect engages, deploy a custom, context-rich agent to deliver a hyper-personalized pitch or deck as the more impactful follow-up.
Perplexity Computer can identify prospects, find specific contacts (like partnership managers instead of CEOs), research their company's news and personal social media, and draft unique, hyper-personalized emails, automating a complex sales development workflow.
Off-the-shelf AI go-to-market tools fail because they are purely transactional. ElevenLabs' CRO built custom AI agents for SDRs, proposals, and customer success that assist humans by drafting personalized messages, which are then reviewed, sent, and used to fine-tune the models, leading to actual revenue generation.