Why Customer Insights and Analytics Matter

Customer insights and analytics are closely connected, but each plays a distinct role. Analytics focuses on collecting and interpreting customer data – purchase histories, click-through rates, churn patterns and more – to uncover what customers are doing. Insights and customer intelligence emerge when a human-centric lens is applied to that data, uncovering the motivations and drivers behind those behaviors. Together, they reveal not only the what but the why of customer behavior and decision-making. 

With a deeper understanding of customer needs and expectations, brands can refine campaigns, tailor products and services and strengthen loyalty. In other words, insights and analytics empower organizations to turn data into meaningful action that improves business outcomes. 

By continuously tracking customer behavior and the reasons driving it, companies can anticipate shifting trends and respond proactively, giving them a competitive edge. And because these insights are grounded in quantitative data – not assumptions – they lead to smarter, evidence-based decisions. As data-informed improvements to customer experience, segmentation and marketing strategies begin to generate measurable ROI, internal confidence grows. At the same time, customers feel better understood, fostering stronger loyalty and long-term brand affinity. 

How Are Customer Insights Generated?

Customer insights and analytics begin with data. Organizations can, and should, glean relevant information about customer behavior, preferences and sentiments from numerous sources.  

• Transactional data from stores, e-commerce sites and other purchase points shows who is buying what, when and where they’re making the purchases and how they’re paying. 

• Web, email and app analytics show how customers interact with each of these brand channels. 

• Customer feedback via interactions with customer service reveals consumer pain points. 

• CRM data includes some, if not all, of the above, as well as information regarding how customers were acquired and the ways various channels and data points interact.  

• Social listening demonstrates what customers are saying about the brand in organic, unprompted settings. 

• Customer surveys can unveil demographic information and even basic attitudinal data.  

• Qualitative market research via focus groups, one-on-one interviews and shop-alongs helps substantiate the reasons for consumer behaviors. 

After collecting and cleaning the data, brands analyze it using statistical models, AI algorithms and other tools. This reveals patterns, correlations and trends among the data. Interpreting these findings is the next stage of the customer insights and analytics loop. The similarities, differences and shifts among the data points and patterns provide a robust picture of what various segments of customers look like and how they behave – and together suggest why they behave that way as well.  

Organizations then draw upon these insights to assess the best ways to engage with customers and prospects. Once brands put their plans into action, the consumer insights strategy cycle begins again, with new data to analyze, interpret and act on. Customer insights and analytics are ideally iterative and part of a continual improvement framework. 

Types of Customer Insights 

You can categorize customer and consumer market insights in myriad ways, including by source and by data type (demographic, behavioral, psychographic). The following framework echoes how each stage of the customer insights and analytics loop builds upon the previous one. 

• Descriptive insights reveal what happened. Purely quantitative insights, they come from analyzing and interpreting behavioral data, such as determining the purchase frequency and average order value of customers segmented by age, gender and income.  

• Diagnostic insights uncover the causes for what happened: Why has churn increased during the past six months? What’s behind the recent decline in purchases among men 25-34? 

• Predictive insights forecast future customer behavior based on what buyers have been doing and why. Machine learning models and other AI applications have enabled faster, more accurate projections. 

• Prescriptive insights draw upon all of the above customer insights and analytics to recommend what the organization should do to achieve its goals. Just as it has sharpened forecasting, AI has turbocharged brands’ ability to generate actionable data-driven recommendations. 

Leveraging Customer Insights and Analytics

Organizations can apply customer insights research and analysis at just about any intersection of consumer and brand. Several areas in particular are highly relevant. 

Marketing and campaign optimization 

Segmenting customers based on common traits and analyzing each cohort’s behaviors and motivations enables an organization to more accurately customize marketing campaigns for each group as well as better allocate resources. Men of all demographics might buy from a particular sneaker brand, for instance, but younger, athletic males likely choose different styles than older men for different purposes. Each segment is also apt to consume different media and engage with different influencers. Customer insights and analytics can identify optimal messaging tactics and campaign channels for each group.   

Product development and innovation 

Organizations that analyze customer feedback, social listening findings, purchase behavior and qualitative market research often uncover hidden customer pain points and needs. Descriptive and diagnostic insights, along with competitive analysis, can point out gaps in the market and suggest improvements to existing products or new products altogether that meet these needs. 

Customer journey mapping and personalization 

Customer journey mapping that moves the needle entails more than knowing which touchpoints customers engage with as they move through the marketing funnel. Customer insights research, including analysis of transactional data and channel behavior, reveals points of friction and reasons for consumer drop-off. Armed with this understanding, a brand can act on data-driven recommendations to improve and personalize the customer journey. 

Building an Insights-Driven Organization with Material 

Effective, profitable use of customer insights and analytics doesn’t happen in a vacuum. It needs to exist within an insights-driven organization that values evidence-based, customer-centric decision making.  

The customer insights and analytics experts at Material have decades of experience unlocking actionable insights and consumer intelligence for the world’s leading brands, fueling increased market share, stronger brand loyalty and significant revenue growth. Reach out to us today to learn how our market research services can help drive growth for your brand – with the customer at the center.