There are many challenges companies face when it comes to growing their brand. Identifying opportunities that provide the best chance of growth and understanding their current market position and just how much they can grow are two of them. And maintaining or creating relevant messaging by knowing who to go after to gain that growth—and how to do this effectively—is just as big of a challenge.
While market research is frequently used to address these issues, it generally covers the why and the what. Big data, on the other hand, adds an additional layer of understanding around the who and the how. As a result, we’ve found that combining survey data with big data can provide a deeper level of understanding of audiences and the ability to thoughtfully tie those insights into a communication or advertising strategy. Further, this approach is scalable and agile in nature; it doesn’t require multiple phases or studies, but leverages big data to fill the gaps in survey research to create one cohesive, actionable result.
Identifying and Understanding Opportunities
The biggest part of identifying opportunities is assuring that it’s the right opportunity. Ultimately, this is done through an understanding of a brand’s audience and category together. Once again, big data and survey data can work together to solve this need. Data from a data management platform (DMP) can be appended to survey data in order to build the connection between audience and category.
In other words, survey data can provide insights into consumer preferences when it comes to a specific product, while big data can provide actual purchase behavior of the entire product’s category. With this kind of approach, brands can conduct research with specific objectives in mind, but still pull higher level insights to understand where their findings fit into the marketplace.
Additionally, the ability to pull audience and category level insights allows a brand to know what, who, and how much to go after for brand growth. For example, our big data solution is able to derive brand equity (from survey data) of multiple brands and compare that to actual market share (from big data) to understand which segment or segments of audiences to go after and how much market share is available for growth among those segments.
The benefits of incorporating big data and survey data at the business level have far-reaching effects:
- Many times businesses know what their goals are or where they need to be, but don’t have a means of figuring out how to get there—or the process is far too complex, time-consuming, or costly.
- An approach with big data can also show a fuller picture of how to best apply the insights; it eliminates the need to run additional studies, in most cases, to garner enough understanding to move forward with a strategy confidently.
- Traditional segmentations are unable to provide this cohesive of a view, especially in one study, as they typically incorporate self-reported feedback specific to a single brand’s audience.
Using big data with survey data isn’t just about identifying and understanding opportunities either. Sometimes it’s a way to evaluate opportunities and minimize the risk of making assumptions based on insights that may only be telling half of the consumer story, especially when it comes to messaging.
Translating Findings into Effective Messaging
DMPs often include more information than just category level insights. In fact, data on social media usage, television viewing habits, and browsing history can be provided. This information, combined with demographics and feedback on specific brands or product concepts provides an unparalleled level of depth and understanding of an audience.
In fact, we use big data in order to learn more about the personalities of audiences by leveraging The Big 5 model. This model helps to learn more about consumers by assigning varying levels of each of the 5 unique personality traits:
- Openness: People who are open to experiencing a variety of activities.
- Conscientiousness: People who have a tendency to act in an organized or thoughtful way.
- Agreeableness: People with a tendency to be compassionate and cooperative toward others.
- Extraversion: People who have a tendency to seek stimulation in the company of others.
- Nervousness: People whose emotions are sensitive to their environment.
Without having to ask more questions or conduct lengthy interviews, market researchers can learn more about who to target and how to do so more efficiently. And since these personality traits can be used to extrapolate additional characteristics, they’re incredibly informative when it comes to messaging tactics. Combining consumer preferences, behaviors, and personality insights means brands can execute upon the findings.
Overall combining big data with survey data can provide more answers without having to ask more questions. And consequently, a more holistic picture of actionable insights can be generated with little to no impact on timelines—making it a perfect solution for agile market research. To learn more about our big data solution, download the snapshot below and you’ll see how GutCheck Constellation™ makes big data meaningful in an actionable way, to help grow your brand.