1/ hiring a sales rep for an unproven product is the most expensive experiment you'll run
everyone thinks a new rep or moving X to Y to Z product is the solution
Quick context: I own a communal sauna and cold plunge studio. Mindbody is the booking and membership software studios like mine run on.
I spent an hour on the phone with Mindbody support. They couldn't fix my problem. I asked @Muse to look at my actual setup. Five minutes later it had the answer, and support agreed it was right.
The problem: a member with unlimited sessions plus 4 instructor-led classes a month kept having instructor-led classes deducted when booking regular sessions. The scarce resource, gone. The unlimited, untouched. That's backwards.
The cause: Mindbody decides which pricing option pays using a priority hierarchy. Both options defaulted to Medium. This effects purchase order, and inside the sale the instructor-led classes were rung up just before the membership itself. Leading to me getting a message that they couldn't book with an instructor.
The fix: one dropdown. Unlimited sessions to High priority.
Here's the part that matters: the rep wasn't dumb, they were structurally blind. They work from scripts and general product knowledge. They can't see your configured state. Muse read my actual setup...in 5 min
Every support interaction is a diagnosis problem, and diagnosis needs ground truth. The L1 support role is done. Not in ten years, now.
Just like anything else AI, humans move up the stack: the ambiguous 5%, the judgment calls, the trust moments. Everything else gets replaced by what can see the truth of your setup. Question is, can support reps catch up fast enough?
our reply rate looked healthy
then we checked the trend week over week
it was falling (from 7% reply rate -> 0.8-1% WoW)
we changed the channel instead of optimizing a metric that was hiding the problem
topline metrics are useful
they are not the sales motion
60% ready and outbound shipped, is better than 95% ready and no messages sent
learn as you go and don't over engineer what you don't have answers to yet
better data can make bad gtm harder to notice
now the list is cleaner
the timing is better
the personalization looks sharper
but is it really working? teams get stuck on over optimization when you should be testing
positive replies
booking rates
no show rates
2nd meeting conversion
until you know more about the target customer, you should not be heavily engineering your gtm
Signal-based GTM usually fails before the signal ever matters.
Teams use a funding round, a new VP, or a hiring spike as proof of demand.
It isn't.
A signal tells you something changed.
It doesn't tell you the change is painful.
It doesn't tell you the buyer cares.
It doesn't tell you your product is the answer.
Without that, you're just sending a better-timed generic message.
The signal gets you into the account.
The pain gets you a reply.
Most teams want better signals.
They need a better reason to reach out.
seeing hate on static data and “generic lists” in outbound
this isn’t a take that flows with the zeitgeist but you need the static information
use an assumption to start then introduce signals & iteration
you won’t know what to look before validating who you’re selling to
just ran an experiment on my own cold outbound
Apollo told me deliverability across two domains was great (>90% health score) when in practicality they were returning <18% open rates
if you would’ve iterated copy on this, you would’ve lost both domains and thousands in time
everyone is selling signals when the problem with your GTM is the foundation.
those who know how to fix that, have a massive opportunity ahead of them.
most founders default to buying the sales tool.
blindly spending hundreds on tools marketed as your solution to revenue.
reply % bad
poor ROI on outbound
meetings you do book -> unqualified
if I was starting to sell a new product, business, vertical, I’d do it all by hand.
send cold outbound by
icp
channel
persona
test that until something sticks. Then move on to copy (variants) until that sticks.
once you’ve seen with your own eyes what’s works, then scale it.