The Big Data Breakdown, and How to Fill the Gaps

With the advent of artificial intelligence, it is easier than ever to access large amounts of information. Platforms such as Salesforce and Google Analytics provide vast amounts of consumer data, and machine learning algorithms analyze the data at record speed. Marketing professionals then use this “big data” to analyze consumer habits and to optimize strategies.

However, despite its utility for marketing professionals, big data still fails to clarify why consumers act the way they do. While it may identify large-scale trends, big data does not provide insight into consumers’ cognitive patterns. By contrast, experimental data identifies the root causes of consumer behavior. In this post, we explain the benefits and drawbacks of using big data in your business, including the gaps left in the decision-making process. We then introduce experimental data as a way to fill this gap in order for you to save time and money in your marketing campaign.

The Big Data Generation

Big data refers to large datasets that are processed with non-traditional algorithms such as machine learning. These datasets hold vast amounts of consumer information and rely on many sources, including social media platforms and web services. When marketers design a campaign, they often turn to big data to make their decisions. This allows for fast, data-driven insights into consumer behavior, preferences, and patterns across their digital footprint.

The Limitations of Limitless Data

However, big data still lacks the depth to uncover the why behind consumer behavior. While segmentation can show, for instance, that your campaign underperforms among younger audiences, it will not tell you why it underperforms or what aspects of your messaging need to change—whether the tone, the visuals, the timing, or the message itself. Instead, big data will only reveal correlations that are useful but not sufficient for decision-making. In order to optimize your marketing campaigns, you need insights into the cognitive-emotional factors that drive consumers.

How EEG-Based Experiments Fill the Gaps

With electroencephalography (EEG), you can look beyond big data into the minds of your consumers. Rather than identifying large-scale trends, you can use experiments to answer specific questions such as the following:

• Which version of our ad evokes more attention and emotional engagement?

• Does our call-to-action generate cognitive effort or mental fatigue?

• Are viewers experiencing trust or skepticism when they see our brand?

To answer these questions, EEG experiments use non-invasive sensors that monitor brain activity. Scientists measure neural markers such as attention and emotional resonance through this brain activity in order to understand consumer perception.

While big data offers large-scale insights on consumer trends, experiments provide refined answers to your most pressing problems. Experiments allow you to investigate why patterns exist and to identify causes as opposed to correlations. Experimental data thus complements big data in your decision-making process.

The Experimental Difference

Image created using generative AI

Smarter Campaigns Begin with Smarter Data

The best marketing strategies use a combination of big and experimental data. While big data provides insight on overarching trends, experimental data explains why certain trends appear. When marketers use a combination of big and experimental data, they make more informed decisions and create a greater impact through their campaigns.

Our Research

At ThinkAlike Laboratories, we design experiments to answer your toughest questions. With a combination of neuroscience, marketing, and advanced data analytics, we identify the root causes of low engagement in your marketing campaigns.

Contact us today to learn how we can enhance your marketing campaign.