I built this to show how I'd stand up your pipeline instrumentation on Salesforce + Snowflake. You're private and don't publish CRM data, so I grounded it in what I could actually verify about your GTM build-out.
I pulled every LinkedIn profile listing you as employer, filtered to sales/GTM titles, and read them by start date: the real version of your "5 reps → 100+." Click any bar to see who joined.
You don't publish ARR in dollars, so I used the growth-rate and payroll-volume figures Ayush has posted publicly, with dates.
I applied your own posted comp bands (from your live open roles) to the real hiring curve above, then set that cost against your revenue index, to see whether it's buying proportionally more growth over time.
A modeled quarterly cohort, tracked through close, split by SMB and Enterprise at every stage
| Company | Segment | States ↓ | Employees | Open roles | Est. annual value |
|---|
You have real Salesforce and Snowflake access to check this against; I don't. So instead of guessing at your actual data, here's the schema I'd propose to produce every number in the funnel and rep sections above, plus two queries that, run against it, generate those exact figures. This is a design proposal, not a live connection.
select segment, count(*) as closed_won
from int_pipeline_stages
where stage = 'Closed Won'
and close_date >= date_trunc('quarter', current_date)
group by segment
select
count(*) filter (where stage_order >= 3) * 1.0
/ count(*) filter (where stage_order >= 2) as rate
from int_pipeline_stages
select r.name, r.track,
sum(o.amount) filter (where o.stage='Closed Won') as closed,
r.quota_quarterly as quota
from fct_pipeline_stage p
join dim_rep r using (rep_id)
join opportunity o using (opportunity_id)
group by r.name, r.track, r.quota_quarterly
select date_trunc('quarter', date) as qtr,
sum(cumulative_cost) / nullif(sum(cumulative_revenue),0) as ratio
from fct_hiring_cost
group by 1 order by 1