Data Quality in Brand Tracking – 38 Best Practices

Quality data is the bedrock of any brand tracking program. Get relevant, reliable insights from your brand tracker by using these best practices.

Is your brand tracker capturing the real dynamics of the marketplace, or are data quality issues painting a deceiving (or inconsistent) picture?

While a totally flat trendline is boring, no insights team wants the “excitement” of brand tracking metrics that shift inexplicably from wave to wave. At best, the team could end up spending tons of time and effort trying to disentangle data issues from marketplace movements — and at worst, they can lose the faith of their organization, brought down by scrutiny and distrust from stakeholders.

Quality data is the bedrock of any tracking program

Quality data can only be achieved with a robust and rigorous approach to creating consistency in methodology and careful management of change when it is unavoidable. This applies to everything from sampling procedures to questionnaire design, participant evaluation to data analysis.

What does good data look like?

High quality data comes from asking questions that are:

• Valid (i.e., the questions measure what you think you measure),
• Reliable (i.e., the data will only change if there is a real change in the marketplace),
• Sensitive (i.e., you are able to effectively detect change over time, or capture changes between key market subgroups).

Why master the art of quality control?

Brands need strict adherence to detailed protocols throughout the program to have an effective and actionable brand tracker — that is, one that can be relied upon to evaluate marketing effectiveness and inform business decisions.

Revisit your program protocols frequently to ensure they reflect the current and future needs of what is likely an evolving business.

There are no do-overs in tracking

Discover 38 procedures you need for tracking data quality control with Material’s latest guide, then build data quality controls into your brand tracking program.

What you’ll learn

• Tips for ensuring meticulous documentation for your tracking program,
• Insights for controlling the composition of your sample,
• How to implement strict participation controls,
• Smart survey design,
• Best practices in pre-launch protocols, analysis, and reporting,
• How to plan for change, and more!