Mastering Data Quality in Online Research

Learn to improve data quality in online surveys for more accurate and reliable research results.

Quality of data is essential to accurate and reliable market research insights. This course equips online research practitioners with the knowledge, tools, and best practices to enhance Data Quality in online research projects. In this course, we will explore Data Quality challenges, uncover how to identify and examine best practice techniques to address them throughout the research project.

At the end of the course, participants will have the skills to optimize Data Quality in online research projects, elevating the credibility and impact of the research insights.

Learning Outcomes/Learning Objectives

• Understand the concept of Data Quality and its significance in Market Research.
• Learn what can impact Data Quality in online survey research.
• Identify and address common Data Quality terms and issues such as biases, incompletes, respondent fraud, and more.
• Analyze real-life case studies to witness the impact of Data Quality on research outcomes.
• Learn what tools and practices can be applied by and your suppliers at various stages of a research project to boost data quality.
• Witness first-hand how an enhanced respondent experience can impact data quality positively.
• Know how to deal effectively with Data Quality issues as they arise.
• Obtain practical knowledge enabling you to set realistic data quality metrics, work effectively with suppliers, consider GDPR implications, and more to ensure data quality in research projects.

Who will benefit?

This course is suitable for online research practitioners who are looking to enhance Data Quality in their research projects through understanding Data Quality drivers, best practices, and techniques.

Learning Method

A mix of theory, discussion, sharing points of view and exercises.

Course Delivery Mode

Online

Trainer Biography

Chris Stevens, brings 30+ years’ experience with expertise in panels, operational process , research methods  and impacts on quality. In prior roles e.g. Head of Quality at Kantar Profiles / Research Director at TNS, Chris focussed on identifying, analysing and implementing process around quality. He continues to support industry quality initiatives with the  most recent being MRS Mobile Optimization project,  ESOMAR’s recommendation for measuring demographics and is a contributor to the MRS program of activities, that is part of the Global Data Quality initiative. Chris brings a wealth of experience and knowledge to this topic area.