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Editor's note: Keith Johnson is chief product officer at GutCheck.
Our world has been quickly changing and is only going to continue to as technology evolves. By 2021 we’ll have as many as 46 billion connected devices thanks to the Internet of Things. With more interconnected devices comes more data.
In 2010 the influx of information as a result of the Internet came to be known as big data. Big data plays a key role in many technologies. Take artificial intelligence, machine learning and automation for example. Each of these tools exploits big data in some form or another. And while these tools have been in existence in various forms for some time, big data provides the means for them to reach their full potential. We can now incorporate the large amounts of information necessary to truly learn and act in meaningful ways. While big data influences several industries and technologies, it has a significant impact on one industry in particular – marketing research.
Big data encompasses extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations often relating to human behavior. Therefore, by definition, big data is a part of marketing research – which is the action or activity of gathering information about consumers’ needs and preferences. Besides this, why should marketing researchers care? Some of the most common frustrations with research today center around the fact that it’s too slow, too expensive and can take too many iterations to get to the right depth of information to truly understand consumer behavior and take action. When big data is part of a researcher’s toolkit, it provides a unique opportunity for researchers to reduce costs, timelines and complexity when it comes to conducting research. The more data we have, the better we understand consumer behavior. This means we can ask fewer questions to get to the answer. Further, it provides the means to gain deeper consumer understanding and develop richer consumer profiles. If you’re in the business of marketing research, my advice is to get on board with utilizing big data or risk getting left behind.
Making big data actionable
There are several complexities when it comes to making big data actionable. Let’s start by defining the four V’s of big data: volume, variety, velocity and veracity. Volume is the amount of data currently available. Variety is the different types of data or sources, such as point-of-sale data, browser history and purchase data. Velocity is the speed at which the data is collected and then accessible. And finally, veracity is the quality or accuracy of it. If we analyze the four V’s based on which ones are the most vetted, volume and variety score the highest. We have more data than we even know what to do with coming from a wide variety of sources. Velocity scores in the middle as our access to real-time consumer data becomes more commonplace. But scoring the lowest, and requiring the most effort when it comes to using big data, is veracity.
The biggest challenge with big data is having too much data, making it difficult to establish veracity. For many of our clients, the data is coming at them from too many sources, too quickly for them to understand what data is accurate and relevant to their business. The risk of making a strategic decision on bad data is high. In fact, in a survey of 300 enterprise organizations conducted by IDG Connect, 42 percent of them stated that their biggest challenge with using big data was the difficulty in extracting insights due to the amount of data. In a separate study put out by IBM and the Econsultancy, they found that just 3 percent of marketers would label their ability to act on insights as excellent, with 54 percent labeling it as poor or very poor. Simply put, data without insight is meaningless, and insights without action are useless. As a result, the research industry is faced with creating a means to discern the signal from the noise within data sets to create actionable insights.
While we understand that there are challenges with using big data, we also recognize there are invaluable opportunities, especially given the frustrations with marketing research. The beauty of big data and marketing research is in the synthesis between the what and the why. Big data will be able to define the who, what, when, where and how, while marketing research will be able to answer the why and ultimately build an entire view of the consumer.
Focus on behaviors
Generating a more holistic view of consumers through big data also increases the quality of information gathered. For example, marketing researchers no longer have to rely on self-reported data from consumers and instead can focus on actual behaviors. Additionally, researchers won’t have to ask as many questions and can reduce the impact of bias from both respondents and the questions themselves.
By pairing agile marketing research with big data, brands can gain a more unified view into the behaviors of consumers when it comes to a particular product or situation. This allows teams to identify consumer sentiment toward products before they launch and get a better understanding of what types of consumers are likely to be interested in the products, how they will feel about them and how to better connect with these consumers.
While it’s still something new, incorporating big data into marketing research – particularly for products early in the product development life cycle – can have a huge impact on understanding new opportunities and optimizations. It will help marketing researchers, as well as product and marketing managers, differentiate between what is and isn’t important as they take on new initiatives and plan business objectives. Couple that with an agile research approach – which allows for faster and more focused movement throughout development – and you’ll have supercharged marketing research.
Time and effort
Still, some feel big data is promising but not worth the time and effort to understand. To those critics, I recommend working with a partner you can trust to act as a guide on this journey. Interrogating and assessing the accuracy and validity of data isn’t easy. That’s why having a research partner with the tools to analyze and pull insights for you can be invaluable.
In addition to hearing this from our own clients, respondents shared similar frustrations in the 2017 Quirk’s Corporate Researcher survey:
“Big data – very promising, managers don’t understand it.”
“Too much data not enough insights.”
“Data without actionable insights.”
“Data quality. Not reliable enough to make sound business decisions.”
“Cost and turnaround time.”
That’s why we’ve pioneered agile market research to provide clients with actionable answers and confidence at the speed of their business; and we are continuing to craft new ways for our clients to think smarter and act faster.