English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We study user sentiment (reported via optional surveys) as a metric for fullyrandomized A/B tests. Both user-level covariates and treatment assignment canimpact response propensity. We propose a set of consistent estimators for theaverage and local treatment effects on treated and respondent users. We showthat our problem can be mapped onto the intersection of the missing dataproblem and observational causal inference, and we identify conditions underwhich consistent estimators exist. We evaluate the performance of estimatorsvia simulation studies and find that more complicated models do not necessarilyprovide superior performance.

User Sentiment as a Success Metric: Persistent Biases Under Full Randomization