It’s helpful to know things like what and how much your customers are buying or not buying, or whether they are buying a competitor’s product. But these insights miss an important aspect of consumer behavior, namely why a consumer made their decision. Now, using advanced social listening tools driven by AI, companies are gaining a better understanding of the emotions and opinions that motivate purchasing decisions and brand engagement.
Approaching consumer behavior analysis with these powerful tools can generate actionable insights that are relevant across a company, including marketing, R&D, customer service, finance, and operations. These insights power strategic decisions that enable your brand to deliver a product that speaks to what your customer wants and the reasons they want it.
Read on to learn how consumer behavior analysis helps you better understand and better serve your customers.
What Is Consumer Behavior Analysis?
At a basic level, consumer behavior analysis refers to the study of how consumers behave and why they behave the way they do. This includes asking questions about when and where consumers are making purchases, along with more nuanced questions, such as how consumers’ emotional responses to a particular product, service, or marketing campaign influenced their purchasing behavior.
In the past, these more nuanced questions were difficult to answer, because they can be difficult to quantify. While consumer research methods such as focus groups and surveys were able to make some progress, they lacked the analytical sophistication to consistently identify actionable insights from large data sets.
But the rise of social media as a dominant mode of conversation around brands and products, along with innovations in data analytics and AI technology, have led to a revolution in the capabilities of consumer behavior analysis.
Social Listening Tools Bring New Insights
Social listening tools are software used to study conversations for insight into how a brand is perceived. In our social media-saturated world, these tools are directed at analyzing online conversations; they are designed to search through platforms such as Facebook, Instagram, Twitter, and Reddit, as well as online comment sections and reviews.
But how can a brand identify the relevant online content and generate actionable insights into consumer behavior from such a large amount of data? The answer is powerful AI.
AI powers social listening by using methods such as text analysis, image analytics, and natural language processing (NLP) to search through online content. The goal is to identify discussions that reveal underlying emotions and opinions connected to a brand, to brand-relevant events and content, or to a competitor’s brand.
For example, a beverage company might use social listening to determine if any flavors are receiving more positive attention than others in online discussions. Or they could determine if individuals were mentioning their brand in connection with an event such as a movie release or a big game. This information can help companies know which brands, products, events, and interests to emphasize in their future marketing campaigns.
Companies don’t need to know which products or events to target in advance when utilizing social listening tools. Intelligent AI does the heavy lifting: systems can analyze large amounts of consumer behavior data and identify trends that would otherwise be difficult to spot. Platforms such as NetBase Quid are able to aggregate this data and display it using intuitive visualizations that highlight the broad trends suggested by detailed analytics.
NetBase Quid AI relies on sentiment analysis, which involves identifying phrases, terms, and images that indicate approval and disapproval (known as polarity), or that indicate specific emotions such as excitement or anger.
Once you have gathered this data, you can create audience segments to study the behavior of groups that feel the same way about your product. What other events or interests do those who like your product feel positively about? How can you connect with those interests in your branding? Understanding how the emotions and opinions of consumers relate to areas outside of your brand is central to creating branding that reaches them at a deeper level.
Moving From ‘What to Why’ in Consumer Behavior Analysis
While it is helpful to know the fundamental where, when, and how much of consumer behavior, next-level analysis requires digging deep into the question of why consumers behave the way they do. Using AI-based social listening tools that can gather, analyze, and visualize large data sets of consumer behavior, companies are answering this question to better connect with consumers.