dsh-growth

Growth teams rarely suffer from a lack of raw data. They suffer from data scattered across notes, event exports, revenue spreadsheets and meeting docs, with every team defining "activation," "retention" and "CAC" slightly differently. A funnel dashboard shows you where users drop off but never answers the harder question: what should you investigate next? And a backlog of growth ideas without falsifiable hypotheses, owners or stop criteria tends to rot quietly. That gap between data, judgment and execution is exactly where dsh-growth steps in—as a local-first plugin that keeps every analysis inside your file paths, with no uploads and no external leakage.

It wires Markdown, CSV and JSONL growth assets into one diagnostic pipeline: AARRR funnels sliced by channel and segment, retention cohorts and lifecycle states, MRR bridges, CAC/LTV/Payback math, HADI experiment cards with RICE/ICE scoring, and finally WBR/MBR/QBR reports that carry sources, caveats and decision dates. The whole flow moves through six decision gates—context, measurement, diagnosis, experiment, priority, review—and halts at the first gate missing evidence rather than inventing a metric or treating correlation as causality.

It is built for SaaS and subscription teams running growth experiments, product or growth analysts who need a consistent operating layer, and solo developers maintaining internal growth SOPs inside a local knowledge base. If you want every growth number to be traceable, every experiment to have a stop criterion, and every sensitive record to stay on your machine, dsh-growth is your growth operating layer.