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Blogs Bob Terzotis Churn Modeling Customer Acquisition Customer Lifetime Value Featured Wine Wine Analytics

30 AugWine Industry Sales Symposium Recap

Blogs Bob Terzotis Case Study Featured Wine Wine Analytics

26 JulData Uncorked: July Edition Newsletter

Bob Terzotis Case Study Churn Modeling Content Analytics Customer Acquisition Customer Lifetime Value Featured Newsletter Wine Wine Analytics

02 JunA Step-by-Step Guide to Minimizing Churn

Blogs Featured Katherine Ruane Nathan Hart Wine Wine Analytics

01 JunEmployee spotlight featuring Rebekah Day

Churn Modeling Featured Market Based Pricing Strategy Revenue / Demand Forecasting Russel Ramtahal Subscription Pricing Strategy Wine Wine Analytics

11 AprEmployee Spotlight featuring Russell Ramtahal

Bob Terzotis Environmental Economics Featured Inventory Optimization Matthew Lulay Russel Ramtahal Wine Wine Analytics

11 AprFeaturing new wine partner: Villa Creek Cellars

Bob Terzotis Featured Inventory Optimization Matthew Lulay Revenue / Demand Forecasting Wine Wine Analytics

11 AprNew wholesale dashboard designed for inventory management

Blogs Wine Wine Analytics

14 JanMeet Nathan Hart: Wine Analytics Expert

Featured Inventory Optimization Matthew Lulay Russel Ramtahal Uncategorized Wine Wine Analytics

20 OctPutting the Cork on Club Member Churn

Bob Terzotis Featured Luke Boutwell Matthew Lulay Russel Ramtahal Wine Wine Analytics

14 JulNew Tool Takes DTC to the Next Level

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Glossary terms for Listener

Ad Revenue at Risk: The advertising revenue that is impacted under varying scenarios. Not all ad revenue may be lost even though it is at risk.
Article PVs at Risk: The article page views that are impacted under varying scenarios. Not all page views may be lost even though they are at risk.
Conversions: The volume of users who become paid subscribers after encountering the paywall at a given meter setting.
Conversion Rate: The ratio of users who become paid subscribers vs. users who encounter the paywall at a given meter setting.
Engagement Group: A categorization for users based on how engaged the are on the site over a 30 day period. Engagement includes page views, article page views, number of unique days a user visited the site, the number of sections a user visited, the total time a user spent on the site, and how far down the page the user scrolled (scroll depth).

Fanatics: the most engaged group of the engagement group.
Enthusiasts: the second most engaged group.
Stable Users: the third most engaged group.
Dabblers: the fourth most engaged group.
Flybys: the fifth most engaged group.
Non-Engaged: the least engaged group.

Impression: An advertisement view or delivery.
Paywall: The software that restricts access to online content for unpaid users.
Meter Setting: The free amount of either pages or days that a user can view before hitting the paywall.
Known User: An anonymous user who engaged with the newsletter or logged in using Gigya over the 30-day period
Paid Subscribers: Subscribers who are paying some price for a subscription.
Paywall Hits: The volume of users who encounter a paywall and are restricted from reading metered content at a given meter setting.
MIP: Mather intelligent paywall. A dynamically adjusting paywall based on user propensity and other behavioral, environmental, and predictive characteristics
ATB: Across-the-board. A static paywall that is not data-driven