Subscription-based businesses often struggle with accurately forecasting revenue due to the complexities of managing subscriber churn, varying subscription tiers, and the impact of seasonality. Traditional forecasting methods, like those used in Excel, lack the sophistication to handle cohort-based analysis and scenario planning effectively. This can lead to inaccurate financial projections and suboptimal pricing strategies.

Subscriptix is a financial modeling platform designed specifically for subscription businesses, providing tools to build robust, fully-modifiable cohort-based forecasting models. The platform enables users to generate models based on historical subscriber retention data and customize them with features like seasonality adjustments and cohort modifiers. Subscriptix allows for the creation of different models for various future scenarios, facilitating comparative analyses through aggregated reporting. It also offers full Excel integration via an add-in, allowing users to enhance existing spreadsheet-based models with cloud-stored data and advanced features.

Cohort-based forecasting models for accurate revenue projections

Subscriber retention data analysis and modeling

Seasonality adjustments and universal cohort modifiers

Scenario planning and comparative analysis

Excel add-in for seamless integration with existing models

Secure cloud-based data storage

Subscriptix is designed for finance professionals, analysts, and executives at subscription-based businesses who need accurate revenue forecasting and financial modeling capabilities.