Collecting information from web clients without explicit input from users is important in a variety of contexts including content customization, experience personalization, accounting and online advertising. A standard approach for gathering web client telemetry is through deployment of Javascript instrumentation that is placed either directly on web pages or through third-party "tags" that are referenced in web pages. In this paper we present a design study of web client measurement methods. The objective of our work is to enhance understanding of best practices in web client measurement toward the goal of developing future tags that are reliable, robust and efficient. We begin by conducting a detailed examination of Javascript instrumentation collected from five well known third party services. Our analysis shows that these code-bases have diverse capabilities and return a broad range of client characteristics. Next, we describe a web client measurement framework and an implementation that we call IntegraTag, which enables us to examine details of performance, accuracy and reliability through live deployments. We use IntegraTag to conduct case studies of tag behavior on a single website which resulted in over 500K page-loads, and on a publisher network which resulted in over 150M page-loads. We establish a lower-bound on the tag's reporting fidelity using a Bernoulli trial. We report on the wide range of client characteristics returned by IntegraTag, as well as its performance and robustness.