Quality data is the foundation for activation strategies that yield growth outcomes.
As a research partner, our main objective is to deliver insights that our clients can take action on to move their brand forward. To help teams achieve their goals, we spend a lot of time in discovery sessions talking with stakeholders about their objectives, a process that helps us shape our research approach to deliver specific datasets that will impact their desired outcomes. Behind the scenes, we rely on a strong commitment to data quality to ensure our insights are accurate, reliable, and complete.
Identifying qualified respondents is the key to strong data.
Our stakeholder discovery sessions help us recruit ideal survey respondents. Rarely is the target audience “everybody everywhere at any time.” Various stages of research require respondents to give input on product definition, feature optimization, or messaging strategies, for example. By clearly defining research goals, we can seek out the most appropriate respondents with the applicable topical knowledge needed.
The efforts we put into ensuring data quality assures us that we’re delivering reliable and actionable insights to brand teams.”
A quality response pool is the critical element for sampling so we can project insights from a group back to the broader population. If we need deeper insights, we can zero in on a few specific respondents for immersive research. When conducting a study on power tools used on construction sites, we engaged in a rigorous process to identify and validate construction professionals who use the tools on a daily basis at worksites to get first-hand feedback and observations. Their specific input helped the team make critical decisions on design, function, and messaging for the tools.
The impact of emerging technologies on survey integrity.
New and emerging technologies are making it easier, in some ways, to conduct research, but they’re also raising concerns about authenticity and quality.
- Survey fraud can undermine data validity and compromise research outcomes. For example, we’ve observed instances where AI-generated responses were indistinguishable from those of real respondents, even for highly specialized questions.
- Do-it-yourself (DIY) survey tools are also becoming more popular, offering a quick and inexpensive survey solution, but they currently lack comprehensive measures for ensuring sample quality.
- B2B research studies, often conducted online where it’s easier to fake credentials, reward respondents with high participation incentives, which can lead to unqualified respondents exaggerating their qualifications in order to earn the fee.
To combat these issues, we work with field teams and reliable panel partners to identify fraud and streamline our data validation processes. As the data comes in, we closely monitor response patterns, employ advanced fraud detection techniques and vet responses to ensure data integrity. These methods take additional time and budget, but they offer improved data quality and greater assurance regarding the authenticity of respondents.
New and emerging technologies are making it easier, in some ways, to conduct research, but they’re also raising concerns about authenticity and quality. … To combat these issues, we work with field teams and reliable panel partners to identify fraud and streamline our data validation processes.”
Compelling data stories inspire activation.
The efforts we put into ensuring data quality assures us that we’re delivering reliable and actionable insights to brand teams. We tailor our reports to each team, so they can access and digest the data and insights that are most critical to their role in the overall activation strategy, and provide teams with rich data stories that blend qualitative insights shared through videos or interviews to give a human voice that reinforces crucial data points and insights.
Our focus on data quality builds a strong insights foundation for activation planning. Trusting the data helps us move teams through activation and execution with confidence that the data, insights, and implications will help them meet their growth objectives.
Want to discuss your data quality strategy?