SoftGuide > Functions / Modules Designation > Subscription shelf life statistics

Subscription shelf life statistics

What is meant by Subscription shelf life statistics?

Subscription shelf life statistics refer to the analysis of customer retention and satisfaction in the subscription business. It involves examining how long subscribers remain loyal to a particular product or service before canceling or terminating the subscription. This statistic is crucial for companies to evaluate the attractiveness of their offerings, strengthen customer relationships, and develop strategies to improve customer retention.

Typical functions of software in the area of "subscription shelf life statistics" can include:

  1. Data Analysis and Reporting:

    • Collection of data about subscribers and their subscription history.
    • Generation of statistics and reports on subscription duration, churn rates, and customer retention rates.
  2. Subscriber Segmentation:

    • Segmenting subscribers based on various criteria such as subscription duration, payment behavior, or demographic characteristics.
    • Identifying trends and patterns among different subscriber groups.
  3. Forecasting and Trend Analysis:

    • Forecasting future churn rates and customer retention rates based on historical data and current trends.
    • Analyzing causes of churn and identifying measures to improve customer retention.
  4. Dashboard and Visualization:

    • Providing dashboards and visual reports for easy presentation and interpretation of subscription retention data.
    • Interactive visualizations for analyzing subscriber trends and patterns.
  5. Customer Feedback and Surveys:

    • Soliciting customer feedback and opinions on satisfaction with the subscription offering.
    • Integrating surveys and feedback mechanisms for continuous improvement of the subscription service.

The function / module Subscription shelf life statistics belongs to:

Statistics/Forecast

analyses of covariance
Article hit and rivet lists
Bayesian analysis
Before-and-after comparisons
Budget information
Business Impact Analysis
Capacity evaluations
Cashier hit list
Classification and prediction
classification and regression trees
Cluster analyses
Clustering
Collaborative Planning
combinatorial problems
comparative statistics
Container accounting
Correlation matrix
Correlations
Cost analysis and budget control
Course participant and learning statistics
Course statistics
Customer and sales data analysis
Customer evaluations
Customer statistics
Econometric and statistical analyses
Energy price analysis
Error analysis
Excel export
Financial market statistics
Financial reporting
Fluctuation statistics
forecast result
Forecasting
Forecasting and planning
Gibbs sampling
Key figure simulations
KTL evaluation
Linked data management
liquidity analysis
Management evaluations
Mandate analysis
matrix calculus
Mean values
Measurement data
Metropolis algorithm
Movement profiles
Network Statistics
Order tracking
Performance analysis
Permutation test
Personnel key figures
Plausibility check
predictions and model simulation
Predictive analytics
Predictive Modeling
previous year view
Probabilities of occurrence
Probability analysis
Probability distributions
Probability functions
Projection comparison
Random generator
Regression analysis
Regressions or equalization calculations
Resume analysis
Risk analysis
Sales comparisons
Sales hit lists
Sales lists
Sales statistics
Sales statistics
Sampling system
Seller hit list
Sequence analysis
Service report
Shopping cart analysis
Signal statistics
Six Sigma
Statistical Analysis
statistical calculations
statistical cost planning
statistical methods
Time data, time series, calendar
Time series analyses
Travel expenses
Trend value analyses
Utilization analysis according to loss classes
Weighting functions
What-if analyses

Software solutions with function or module Subscription shelf life statistics:

knk Subscription Management Module