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Traders know they should evaluate strategies with metrics like profit factor, expectancy, drawdown and time-of-day performance, but the post highlights the real friction: tracking these consistently from raw trades is hard enough that most don’t do it. Without consistent measurement, traders keep trading negative-expectancy windows/strategies and only notice after accumulating losses.
Trade Metrics Autopilot
A lightweight trade-journal ingestion and analytics SaaS that turns raw fills into strategy health metrics (profit factor, expectancy, max loss streak, time-of-day breakdown) automatically. It focuses on fast setup (CSV/broker export in) and opinionated, decision-oriented outputs (what to stop trading, what time windows to avoid) rather than generic charting.
Active retail day traders and small prop teams (1–20 traders) who place high trade volume and need repeatable strategy evaluation without maintaining complex spreadsheets.
The post explicitly notes the hardest part is consistent tracking; this product removes manual spreadsheet maintenance by automating data normalization and metric calculation. The time-of-day and consecutive-loss analytics directly support the ‘trade less, trade cleaner’ behavior by identifying statistically negative windows and risk-of-ruin patterns.
Free spreadsheet template + sample dataset and a ‘5-metric’ calculator web page for a single CSV upload (limited rows).
$19 one-time ‘Import Pack’ with broker-specific CSV templates and tagging conventions.
$29–$79/month subscription for automated imports, unlimited trades, time-of-day analysis, and alerts.
Add-on $15–$30/month for multi-account aggregation, weekly PDF reports, and goal tracking (e.g., avoid negative windows).
$299–$999/month team plan for small prop groups: shared metric definitions, admin controls, and performance reporting across traders.
MVP is a web app with CSV ingestion, trade normalization, tagging, and metric computations plus visualizations; feasible for 1–2 engineers in ~8 weeks using a standard web stack. Key risks are broker/export variability and data quality; mitigated by starting with 3–5 popular brokers and a robust mapping wizard. Regulatory risk is low if positioned as analytics/journaling (no trade execution, no personalized investment advice).
TAM (active self-directed traders globally) ~20–40M; SAM (high-frequency/active day traders likely to journal and pay) ~1–3M. SOM initial wedge: English-speaking active day traders using CSV exports from top brokers, ~150k–400k.
Can feel heavy/over-featured for traders who mainly want a few metrics and fast answers; pricing can be high for casual users.
More opinionated ‘stop trading this window/strategy’ rules and simpler onboarding focused on the 5 metrics.
Solo traders who want minimal journaling overhead and only metric-driven decisioning.
Strong journaling brand but onboarding and workflows can still require manual tagging discipline to get clean analytics.
Broker-export-first flow with automatic normalization + rule-based guardrails around time windows and loss streak tolerances.
High-volume traders who want automation-first metrics without adding journaling chores.
Desktop-style workflow and steeper setup; less seamless with modern broker exports and continuous reporting.
Fast web-based imports and time-of-day analytics that are simple to interpret and act on.
Newer traders who will pay for simplicity but won’t maintain complex setups.
Narrow wedge: become the ‘metrics compliance layer’ for discretionary day traders—broker-export in, 5 core metrics out, plus guardrail alerts that help traders avoid known negative windows (e.g., afternoon). Compete on speed-to-value (first insights in <10 minutes), opinionated defaults, and automation rather than trying to be a full journaling suite.
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