Mowt vs WorthSignal

Mowt provides real-time subscription analytics for SaaS businesses, with views of MRR, ARR, net revenue, and churn. Its dashboard can segment results by plan, region, or acquisition channel, while cohort analysis visualizes retention and customer drop-off over time. Forecasting projects revenue from historical trends and lets users set MRR goals. Mowt connects directly to Stripe and syncs subscriptions, plans, prices, invoices, charges, refunds, proration, coupons, trials, failed payments, and customer metadata. The connection is read-only and cannot create charges; Stripe is the only supported billing platform. Mowt says it encrypts databases at rest with AES-256 and connections with TLS 1.3, and lists a completed SOC 2 Type II audit and adherence to UK GDPR and the UK Data Protection Act 2018. Support is available by email and dashboard live chat, with a stated two-hour average email response time. The Startup plan costs $79 a month when billed monthly; annual billing saves 20%. It includes up to $15k MRR, and a seven-day trial is available.

WorthSignal is a free, open-source toolkit that turns spreadsheet and data files into customer value analyses for marketers. It reads XLSX, XLS, XLSM, CSV and JSON files, suggests column mappings and lets users correct them without changing the uploaded file. Its analyses cover nine areas, including RFM targeting, customer lifetime value, customer equity, acquisition and retention budgets, Markov switching ROI, contractual retention, BG/NBD, BG/BB and complaint recovery. Results can be downloaded as Excel or JSON. In local mode, analysis runs in memory on the user's computer; WorthSignal says uploaded customer data is not intentionally sent to its maintainer or a third-party API. Hosted deployments process files on the chosen server, and that operator is responsible for access controls, logs, retention and privacy obligations. The app requires Python 3.10 or newer and can be launched on Windows or Mac, through terminal instructions for any operating system, or with Docker. Its documented methods are described as classic, deliberately simple models. The project uses the AGPL-3.0-or-later license, with commercial use subject to its conditions.