aOne of the most commonly used terms in the business world is “big data.” If you accept the buzz around social media, you might feel it offers the answer to every marketing challenge that has ever been in the history of company. It’s easy to assume that Big Data will one day supplant market research. The truth, however, is that this is not the case.

That isn’t to suggest that data analysis isn’t valuable, but it differs from traditional market research methodologies in terms of strengths and weaknesses. Big Data is not a replacement for market research, as some argue, but rather a tool that can be used in conjunction with research to gain more insight. This article will highlight five ways for firms to benefit from the synergies that come from merging big data with market research.

1-Predictions and Comprehension Collaboration

The first chance is to deal with a long-standing problem: the disconnect between action and reaction. Individuals’ words and actions may be opposed. Market research, in its most basic form, is asking people what they would do in a certain situation. Data analysis, on the other hand, makes use of past data to understand behavioural tendencies.

By combining big data analytics with market research, it is possible to gain insight into both public sentiment and past behavior. When these two perspectives are contrasted, far more accurate data is acquired on which future decisions can be made. Customers may say they’d buy a new brand extension, but their previous actions may contradict that statement. As a result, a product extension with a far more effective launch plan may be able to address this issue. It would have been difficult to reach this conclusion without conducting both data analysis and statistical analysis.

2- Hypotheses Validation

Big data mining can also be used as a secondary research tool to help test hypotheses. If your depth interviews and creative quality assignments all tell the same narrative, behavioral and financial data sets can be used to confirm the likelihood of your forecasts coming true. Of course, if you’re going to use data and study in this way, you have to be careful to prevent confirmation bias.

The mindset of only seeking facts that support your point of view is known as confirmation bias. It’s especially risky in big data scenarios since the information can be interpreted in so many diverse and unique ways. To avoid confirmation bias, carefully manage information throughout your team so that analysts are unaware of the hypothesis they are proving or disproving, and researchers are unable to sway the outcome through misinterpretation.

3- Completing the Story

Big data and market research are essentially the same thing. Their mission is to supply managers with information about the firm that they can use to make better decisions. However, the two approaches to achieving this aim are noticeably dissimilar. The “what” of a tale is revealed via Big Data? What exactly did the buyers purchase? What did people try to stay away from? Which advertisement had the most impact on their decision-making?

In-depth qualitative research, on the other hand, is what brings the “why” to this tale. Customers bought that goods for a variety of reasons. Why did they keep their distance from the rest of the group? Why did they choose our advertisement over the ones of our competitors? It is possible to build captivating narratives that people will listen to by stitching these two sides of the same story together. Business activity is sparked by complete tales. Ones that aren’t completed merely raise more questions.

4- Data Humanization

There is universal agreement that storytelling is the way to go when it comes to presenting findings. When presented with numbers, we have a natural tendency to be skeptical—not to be duped by statements we know are meant to deceive and perplex. We are far more willing to suspend our disbelief when listening to stories. There is something that unites us on a human level with others through the art of storytelling. We can empathize by visualizing ourselves in the same scenario and our reactions.

So, how can you gather stories that will not only support your data but also serve as the foundation of a presentation? Through in-depth examinations of emotion and cognition Analyze data to better understand people’s actions, then ask them why they act the way they do. Ascend to the highest level of abstraction you can summon in your quest for deep, emotional knowledge.

5- Continuous Enhancement

A continuous development cycle is another innovative technique to combine qualitative research and data analysis. When it comes to analyzing previous behaviors and making forecasts for the near future, data analytics shines. Market research can address a broader range of consumer issues, but not always those that can be resolved immediately.

It is possible to construct short, continuous development cycles that better serve the business by leveraging the characteristics of both technologies. Data may be utilized to rapidly improve products, services, and experiences by making modest, incremental adjustments. Long-term qualitative research that reveals essential structural enhancements to the brand design should also be conducted at the same time. Of course, putting these ideas into action is a much longer process, so it’s even more critical to focus on the short-term, urgent changes that can be achieved at the same time.

To summarize, big data and market research are not the adversaries that many people believe them to be. Rather, they are complementary tools that not only exist in your business, but also operate together to produce some outstanding results. My goal is that, in the future, we will see a lot more collaborative efforts and integrated teams working together instead of competing. Only when we embrace this will we be able to properly appreciate the value of the Big Data economy.

SSubscribe NOW to Freemind-MENA newsletter!