Freemium economics leveraging analytics and user segmentation to drive revenue
Freemium Economics brings a practical, instructive approach to help you successfully implement the freemium model by building analytics into product design from the beginning. Your freemium product generates vast volumes of data, but using that data to maximize conversion, boost retention, and deli...
| Autor principal: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Waltham, MA :
Morgan Kaufmann, an imprint of Elsevier
2014.
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| Edición: | 1st edition |
| Colección: | Savvy manager's guides.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009627866906719 |
Tabla de Contenidos:
- Front Cover; Freemium Economics; Copyright Page; Contents; Acknowledgments; Author Biography; Introduction; 1 The Freemium Business Model; Commerce at a price point of 0; Components of the freemium business model; Scale; Insight; Monetization; Optimization; Freemium economics; Price elasticity of demand; Price discrimination; Pareto efficiency; Freemium product case studies; Skype; Spotify; Candy Crush Saga; 2 Analytics and Freemium Products; Insight as the foundation of freemium product development; Analytics; What is analytics?; What is big data?
- Designing an analytics platform for freemium product developmentStoring data for a freemium product; Reporting data for a freemium product; Data-driven design; The minimum viable product; Data-driven design versus data-prejudiced design; 3 Quantitative Methods for Product Management; Data analysis; Descriptive statistics; Exploratory data analysis; Probability distributions; Basic data visuals; Confidence intervals; A/B testing; What is an A/B test?; Designing an A/B test; Interpreting A/B test results; Regression analysis; What is regression?; The regression model in product development
- Linear regressionLogistic regression; User segmentation; Behavioral data; Demographic data; Predicting user segments; 4 Freemium Metrics; Instrumenting freemium products; Minimum viable metrics; Working with metrics in the freemium model; Retention; The retention profile; Retention metrics; Tracking retention; Monetization; Conversion; Revenue metrics; Engagement; The onboarding funnel; Session metrics; Net promoter score; Virality; Virality hooks; The k-factor; Using metrics in the freemium model; Metrics and the organization; Dashboard design; Ad-hoc analysis
- Minimum viable metrics as a source of revenue5 Lifetime Customer Value; Lifetime customer value; Lifetime customer value and the freemium model; Making use of LTV; LTV in, LTV out; Retention versus acquisition; Discounting LTV; Calculating lifetime customer value; The spreadsheet approach; Constructing the retention profile in a spreadsheet; Calculating user lifetime from the retention profile curve; Calculating revenue with trailing ARPDAU; Structuring the LTV worksheet and deriving LTV; ARPDAU versus projected individual revenue; The analytics method; The Pareto/NBD method
- The regression methodImplementing an analytics model; Auditing an analytics model; Making decisions with LTV; LTV and marketing; LTV and product development; LTV and organizational priority; The politics of LTV; 6 Freemium Monetization; The continuous monetization curve; Choice, preference, and spending; What is the continuous monetization curve?; Engineering a freemium product catalogue; Freemium and non-paying users; Revenue-based user segments; Data products in the freemium model; Recommendation engines; The dynamic product catalogue; Productizing analytics; Downstream marketing
- Reengagement marketing
