All posts categorized in: Data Science

%s

D-Curve: An Improved Method for Defining Non-Contractual Churn with Type I and Type II Errors

Businesses need to know when customers end their business relationships, an act called “churn.” In a subscription business model, a customer churns by actively canceling their contract. The company can therefore detect and record this churn with absolute certainty. But when no explicit contract exists, churn is more passive and difficult to detect. Without any […]

Read the full article »

Time-Tested: 7 Ways to Improve Velocity When A/B Testing a New UX

A/B testing holistic redesigns can be tough. Here at Indeed, we learned this firsthand when we tried to take our UX from this to this:   The Indeed mobile Search Engine Results Page (SERP) circa mid-2017 (left) and circa mid-2018 (right) Detailed description of image The before and after image includes two screenshots: one of […]

Read the full article »

The Evolving Language of Data Science 

…or Grokking the Bokeh of Scarse Meaning Increasement “You keep using that word. I do not think it means what you think it means.” — Dr. Inigo Montoya I’m a technical writer at Indeed. One of the many great things about my job is that I get to work with smart people every day. A […]

Read the full article »