Data Quality & Standards

Data Quality & Standards

Let’s not accept poor data quality as the norm. 
Meet the data quality challenge with Insights Association.

The cornerstone of the insights and analytics industry's success is data quality, defined as a measure of the condition of data based on factors such as accuracy, completeness, consistency, reliability, and how up-to-date it is. Poor data quality interferes with our industry's ability to inform smart marketing decisions. According to a 2023 Insights Association member survey on data fraud, an aspect of data quality:

  • 63% Accept some level of fraud as part of conducting market research studies
  • 64% Have had a project delayed or negatively impacted by fraud
  • 56% Claim their decision-making has been impacted by fraud

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Our approach to improving data quality and data integrity

Improving and adopting protection measures against poor data quality requires cross-collaboration, the development of innovative approaches to data collection, validation, and analysis, and the setting of new standards for excellence. The path to this includes:

  • Partnerships. Facilitated by Insights Association's Council for Data Integrity and the cross-association initiative, Global Data Quality, the development and adoption of collective solutions with the insights and analytics industry.
  • Education. Ongoing education and provision of tools and frameworks on data quality, management, and ethics. Additionally, raising awareness that data quality is the responsibility of all, not any one company type, function, methodology, and across the insights cycle.
  • Language. Encouraging the adoption of consistent industry language to help provide more clarity on where data quality problems exist and solutions.
  • Benchmarks. Defining data quality and fraud standards quantitatively so the industry and individual companies can track performance on a level playing field.

Council for Data Integrity

Led by Insights Association member industry leaders and experts, the Council for Data Integrity (CDI) follows the continual evolution of sample and data integrity definitions, quality standards, evaluation processes, and industry education. Founded in 2021, the CDI develops educational content, best practices, and guidelines for the insights and analytics industry. The CDI also acts as the U.S. extension of the Global Data Quality initiative, a partnership of global associations.

Our Goals

  1. Build awareness of data quality and integrity issues and their potential impact.
  2. Define data integrity terms, highlighting implications on results.
  3. Guide data evaluation by developing quality measures, scorecards, and benchmarks.
  4. Empower members to evaluate and select data providers that adhere to quality standards
  5. Increase interest in professional certifications and standards that can benefit insights organizations.
  6. Advocate to ensure policies and legislation preserve data quality and protect the industry.

Global Data Quality initiative

We’re working together with associations across the world to take data risk out of research. 

Established by the Insights Association, our organization is coordinating efforts with Association for Qualitative Research (AQR), The Canadian Research Insights Council (CRIC), ESOMAR, Insights Association, the QRCA, MRS (Market Research Society), The Research Society (TRS), SampleCon, and the Association of Market Research Austria (VMÖ) to address ongoing and emerging risks to data quality in the market and social research, consumer insights and analytics industry. With the goal of increasing information and building trust, each organization will lead a workstream that delivers global quality resources to improve the conversation and outcomes.

Initiatives & Resources

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Resource Library

These resources, both developed and curated by the Council for Data Integrity, provide actionable insights for every research professional across the research cycle.

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Data Quality Glossary

A consistent industry language needs to be adopted to provide much more clarity on where the problems really exist and the solutions to solve them.

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Participant Bill of Rights

As an extension of the professional Code of Standards drawn specifically to protect the participant experience in the ever-evolving world of market research.

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Data Quality Slack Channel

We invite you to actively participate in building a community where we continue to advance both the participant experience and data quality. Join other IA members to talk all things data quality.

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Council for Data
Integrity

The 2024 Council represents a wide range of business types and expertise in the insights and analytics industry. Insights Association thanks everyone for their time and resources.

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CIRQ

Become certified to the ISO standards designated applicable to the market research and insights industries as a pathway to increasing data quality across the project lifecycle.


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Global Data Quality Pledge

The Global Data Quality (GDQ) Pledge will be a set of practices and standards an organization commits to in order to signal they are upholding the highest standards of data quality in every aspect of their work. The GDQ Pledge will be supported with a robust compliance mechanism overseen by the associations that make up the GDQ initiative.

Coming Soon

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Data Quality
Benchmarks

The Data Quality Benchmarks will define quantitative benchmarks that will help set industry standards and serve as signals of data set quality for both the industry, brands, and research providers. Fraud removal, abandonment, length of Interview, use of secure end links, in-survey removals, and incentives will be the initial benchmarks tracked.

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Data Quality Fundamentals Course

This comprehensive course on Data Quality and Fraud Prevention in Research will offer a detailed exploration into safeguarding the integrity and validity of marketing research through advanced detection and prevention strategies.


Launching Soon