EquiForge Analytics
Guided preview — hover or tap anything underlined or any info icon for a plain-English explanation. dev: DuckDB45-day windowseed data
EquiForge — marketing funnel
Ad spend
$27,236
Leads
517
CAC
$52.68
Activation rate
55.7%
517Leads
298MQL · 58%
219SQL · 73.5%
122Activated · 55.7%
Daily spend vs leads
Spend & CAC by channel
SpendCAC
Trading — momentum_v1 (PnL / risk)
Realized P&L
$10,241
Win rate
58.3%
Expectancy
$53.34
Max drawdown
10.66%
Equity curve & drawdown
EquityDrawdown
P&L & win rate by setup
P&LWin rate
How it all connects
Money flows left to right: spend buys leads, which filter to MQLs, then SQLs, then activated customers. The cost of one customer at the end is CAC. In trading, expectancy is CAC turned around — profit per unit instead of cost per unit. Both answer one question: do the economics work?
Money flows left to right: spend buys leads, which filter to MQLs, then SQLs, then activated customers. The cost of one customer at the end is CAC. In trading, expectancy is CAC turned around — profit per unit instead of cost per unit. Both answer one question: do the economics work?
Every figure compiles from the metrics registry against the dbt marts. Example:
GET /metrics/cac?by=channel&filters={"campaign":"EquiForge%"} — each response also returns the compiled SQL and source model for lineage.