From history to practice: enhancing data quality in the final stages of market research

A typical market research project includes several stages, and focusing on data quality during each of these is, of course, critical.

If you search for “data quality” in ESOMAR’s vast library dating back more than 75 years, you’ll find papers tackling this topic from as early as the 1970s, although the challenge has certainly been going on even longer than five decades. In 1972, the paper “Sources of Error in the Personal Interview” made a plea for reducing errors in survey interviews and focusing attention on raising fieldwork standards. Sound familiar? Looking back even further, Professor Richard Millar Devens coined the phrase “business intelligence” in 1875 to mean gathering information to gain competitive advantage. Is this where our data quality woes began?

While the conversation around data quality has ebbed and flowed over the years, it has never dropped off the radar completely. Although many fingers have been pointed, specific practices blamed, and band-aid solutions implemented, no one has been able to find the data quality magic wand. Over my years in the industry, I have uncovered one thing for certain: it is nearly impossible to overstate the importance of data quality in building true audience understanding.

Ensuring quality in data analysis and reporting

A typical market research project includes several stages, and focusing on data quality during each of these is, of course, critical. For example, after the business question is posed and the best approach for uncovering insights is determined, a research team might employ the following steps:

• Selecting sample
• Designing the survey questionnaire
• Sending the survey into the field
• Gathering the data
• Organise and analyse information and data
• Present findings

Here, I’m going to focus on the last two points. While the analysis and reporting stages are only as good as the data that is gathered, there are ways that you can continue to ensure quality throughout these final steps in the process. The right technology plays a large role in data quality at this point in the process, especially if it is purpose-built for market research data.

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✍️ John Bird of Infotools, Insights powered by Harmoni

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