Synopsis
Churn is the bane of any subscription business, such as content subscriptions, software as a service, and even ad-supported freemium apps. You can improve customer retention through product changes and targeted engagement campaigns based on data-driven interventions.
This hands-on guide is packed with techniques for converting raw data into measurable metrics, testing hypotheses, and presenting findings that are easily understandable to non-technical decision makers.
Don’t let your hard-won customers vanish from subscription services, taking their money with them. In Fighting Churn with Data you’ll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether.
• Identifying processes suited to machine learning
• Using machine learning to automate back office processes
• Seven everyday business process projects
• Using open source and cloud-based tools
• Case studies for machine learning decision making
For readers with basic data analysis skills, including Python and SQL.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Carl Gold is the Chief Data Scientist at Zuora, Inc, a comprehensive subscription management platform and newly public Silicon Valley “unicorn”. Zuora is widely recognized in a leader in all things pertaining to subscription and recurring revenue, with 1,000 customers across a range of industries worldwide. Carl joined Zuora in 2015 and created the predictive analytics system for Zuora’s subscriber analysis product, Zuora Insights.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Fighting Churn with Data: The science and strategy of customer retention
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Paperback. Etat : New. Churn is the bane of any subscription business, such as content subscriptions, software as a service, and even ad-supported freemium apps. You can improve customer retention through product changes and targeted engagement campaigns based on data-driven interventions. This hands-on guide is packed with techniques for converting raw data into measurable metrics, testing hypotheses, and presenting findings that are easily understandable to non-technical decision makers. Don't let your hard-won customers vanish from subscription services, taking their money with them. In Fighting Churn with Data you'll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether. . Identifying processes suited to machine learning . Using machine learning to automate back office processes . Seven everyday business process projects . Using open source and cloud-based tools . Case studies for machine learning decision making For readers with basic data analysis skills, including Python and SQL. N° de réf. du vendeur LU-9781617296529
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Fighting Churn with Data
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ISBN 13 : 9781617296529
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Paperback. Etat : New. Churn is the bane of any subscription business, such as content subscriptions, software as a service, and even ad-supported freemium apps. You can improve customer retention through product changes and targeted engagement campaigns based on data-driven interventions. This hands-on guide is packed with techniques for converting raw data into measurable metrics, testing hypotheses, and presenting findings that are easily understandable to non-technical decision makers. Don't let your hard-won customers vanish from subscription services, taking their money with them. In Fighting Churn with Data you'll learn powerful data-driven techniques to maximize customer retention and minimize actions that cause them to stop engaging or unsubscribe altogether. . Identifying processes suited to machine learning . Using machine learning to automate back office processes . Seven everyday business process projects . Using open source and cloud-based tools . Case studies for machine learning decision making For readers with basic data analysis skills, including Python and SQL. N° de réf. du vendeur LU-9781617296529
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