When it comes to persuasion, numbers don't like to share the spotlight. Statistics like to present themselves as fact, as hard data. Numbers, though, are often useless without context.
When Twitter opened up its historical data for mining a few months ago, the most valuable part was the context of the tweets; the individual experiences of the customer. As an example: knowing that 437 twitter complaints were received means nothing. Knowing what the complaints were, and how they were resolved is the real value. This contextual insight comes from what is known as "qualitative" information, based on individual emotion and experience.
At first glance, this seems messy. How can one summarize experience and emotion of an entire customer base? There are many factors that cannot be controlled or measured, and all of the data seems to exist in a “web” of tensions and interactions. Approaching it may seem overwhelming: there are just too many factors to understand. This is exactly why it is so potentially valuable.
Mass qualitative data analysis and interpretation is the next golden age for marketing. It is now possible to extract experiential information from an entire customer base and formulate it in useful ways. It is now possible to know how many customers feel about your product in comparison to the competition, in ways that can allow a company to intelligently shift their market approach or product strategy. Sounds great, right? Now for the fun part: how?
The answer is clear: mixed data. Adding qualitative data (context and experience) to quantitative data (statistics and generalizability) in your research design can yield more predictive insight. Mixed data is more robust, has more depth, and can predict consumer behavior better than isolated data. Mixed data has traditionally been created through a combination of focus groups and customer surveys, methods that can be expensive, inaccurate, and difficult to unify. Better options are emerging.
Through the use of crowdsourcing and Crowd Intelligence, mixed data gains even more strength. Huge communities can interact with their favorite product brands to discuss preferences, concerns, take part in activities, and to receive brand perks. The mixed data found in these communities can be mined in a countless number of ways, giving a company unprecedented insight into sentiment and action. Customers get to express their opinions, meet other brand enthusiasts, and get rewards; companies deliver more desirable products and services. Everybody benefits.
The mobilization of mixed method data will soon be a requirement for successful strategic marketing. How long will you wait?
In the comment section below, let me know how you see the role of big data in marketing, and how can we use crowdsourcing to understand it?