Traditional email vendor bake-offs rely on limited test volumes and manual analysis, often missing critical delivery failures and engagement differences. This week, SaaStr used an AI-powered agent to run a comprehensive comparison across three vendors, uncovering significant disparities in email deliverability and engagement metrics.
- AI-managed 500,000+ email sends across three vendors
- Challenger delivered 2.4x opens and 2.9x clicks vs incumbent
- Complete send failures uncovered despite green vendor status
What happened
SaaStr conducted a detailed email deliverability bake-off using an AI marketing agent named 10K to run and analyze more than half a million emails across three different sending vendors. This approach replaced the usual limited manual tests that rely on small sample sizes, dashboards, and subjective team input.
The AI agent orchestrated matched audience splits, tracked detailed step-level send records, and diagnosed causes by isolating variables. One key finding was a challenger vendor achieving more than double the open rates and nearly triple the clicks compared to the incumbent provider using identical content, timing, and recipients.
Why it matters
Traditional bake-offs typically leave serious deliverability issues undetected since they depend on team members sending a few hundred emails and trusting vendor dashboards. The AI agent exposed a major failure instance where an incumbent vendor reported 'completed' deliveries but logged over 80,000 errors with zero emails sent—while their status page remained green.
This level of diagnostic rigor is typically available only to large companies with dedicated deliverability teams or consultants. By automating these processes, companies of all sizes can objectively verify vendor claims, optimize engagement, and reduce wasted marketing effort and risk on poor-performing platforms.
What to watch next
The use of AI agents like 10K to strictly control and assess vendor performance tests could become standard in procurement decisions, disrupting incumbents who have relied on inertia and outdated trial methods. Buyers will expect transparent, data-driven scoring that includes delivery verification, engagement quality, and operational overhead.
Vendors will need to demonstrate proven scalability beyond small tests before migration decisions, with staged rollouts advised to protect deliverability when moving large subscriber bases. Ongoing AI-powered monitoring may also become a competitive edge to quickly detect transport or configuration issues in production.