Love this take, and agree that automated SDRs were too early in 2016 ;)
A thought that might bridge the gap between the real problem of exhausting the TAM for a target market and the psychological block of GTM operators not wanting to give up the controls of what they do ...
What if the best use case for an AI SDR is an edge case? Hear me out ...
What do these have in common?
- SQL deadwood (closed lost)
- Unexpected patterns for niche customers (narrow targeting, long tail match, etc)
- Researching potential customers about to switch from other providers
These are all research-intensive tasks with little present value, **until they find a customer**
Since AI/LLMs do not get tired, use them to:
1) reach out in a programmatic way to cold, previously qualified customers (e.g. + 180 days past cycle)
2) analyze current sales qualified leads and suggest alternate ways to find potential leads, propose a low-volume experiment and report back with the results (and search terms)
3) keep a "top N" list of the top 100 customers you would like to get if you knew when they were about to switch from their current providers
Great Scooby Doo unmasking cartoon!!
Love this take, and agree that automated SDRs were too early in 2016 ;)
A thought that might bridge the gap between the real problem of exhausting the TAM for a target market and the psychological block of GTM operators not wanting to give up the controls of what they do ...
What if the best use case for an AI SDR is an edge case? Hear me out ...
What do these have in common?
- SQL deadwood (closed lost)
- Unexpected patterns for niche customers (narrow targeting, long tail match, etc)
- Researching potential customers about to switch from other providers
These are all research-intensive tasks with little present value, **until they find a customer**
Since AI/LLMs do not get tired, use them to:
1) reach out in a programmatic way to cold, previously qualified customers (e.g. + 180 days past cycle)
2) analyze current sales qualified leads and suggest alternate ways to find potential leads, propose a low-volume experiment and report back with the results (and search terms)
3) keep a "top N" list of the top 100 customers you would like to get if you knew when they were about to switch from their current providers