Visible to the public Measuring Metrics

TitleMeasuring Metrics
Publication TypeConference Paper
Year of Publication2016
AuthorsDmitriev, Pavel, Wu, Xian
Conference NameProceedings of the 25th ACM International on Conference on Information and Knowledge Management
Date PublishedOctober 2016
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4073-1
Keywordsa/b testing, Measurement, Metrics, metrics testing, online experimentation, pubcrawl, quality, search metrics
Abstract

You get what you measure, and you can't manage what you don't measure. Metrics are a powerful tool used in organizations to set goals, decide which new products and features should be released to customers, which new tests and experiments should be conducted, and how resources should be allocated. To a large extent, metrics drive the direction of an organization, and getting metrics 'right' is one of the most important and difficult problems an organization needs to solve. However, creating good metrics that capture long-term company goals is difficult. They try to capture abstract concepts such as success, delight, loyalty, engagement, life-time value, etc. How can one determine that a metric is a good one? Or, that one metric is better than another? In other words, how do we measure the quality of metrics? Can the evaluation process be automated so that anyone with an idea of a new metric can quickly evaluate it? In this paper we describe the metric evaluation system deployed at Bing, where we have been working on designing and improving metrics for over five years. We believe that by applying a data driven approach to metric evaluation we have been able to substantially improve our metrics and, as a result, ship better features and improve search experience for Bing's users.

URLhttp://doi.acm.org/10.1145/2983323.2983356
DOI10.1145/2983323.2983356
Citation Keydmitriev_measuring_2016