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Customer Analytics: Understanding Consumer Behavior, Segmentation and Personalization

30 May
Graphic depicting consumer behavior analysis

If businesses could read their customers’ minds, they’d be able to create products that were a raging success every time and know exactly where and how they should market those products. Customer behavior analytics are the next best thing, helping companies understand what their customers want and how they can reach those customers.1

This article will discuss the importance of understanding customer behavior analytics and methods for gathering and analyzing customer behavior data that you can learn with a master of science in business analytics (MSBA) in customer analytics.

Importance of Understanding Consumer Behavior

Customer behavior includes all of the actions, preferences and decisions people make when they interact with products and services in their daily lives. By understanding consumer behavior, businesses can identify what motivates their customers. When they know this, they can design products and services to meet those customers’ needs and desires.2

Understanding how customers make purchasing decisions allows companies to develop effective marketing campaigns. Companies can analyze the patterns and preferences of their target audience and use messaging that deeply resonates with that audience.2

Business leaders can also use the insights gleaned from their consumer behavior analytics to anticipate market trends and proactively adapt the marketing strategy to shifts in consumer preferences. This approach allows them to stay ahead of the competition and remain relevant in today’s fast-moving market.2

Customer analytics plays a pivotal role in both market segmentation and personalization. By collecting and analyzing data, marketers can gain a deep understanding of their audience and effectively deploy both segmentation and personalization strategies.

Market Segmentation Strategy

Market segmentation refers to the process of dividing a broad consumer or business market, normally consisting of existing and potential customers, into sub-groups of consumers (known as segments) based on some type of shared characteristics.3 The objective is to design and implement targeted marketing strategies that can more accurately meet the specific needs of the segments.

Types of market segmentation include:3

  • Demographic Segmentation: Based on age, gender, income, occupation, education, etc.
  • Geographic Segmentation: Based on location such as city, state or country
  • Psychographic Segmentation: Based on lifestyle, attitudes, interests and opinions
  • Behavioral Segmentation: Based on purchasing behavior, user status, loyalty, etc.

Customer Personalization

Customer personalization is a more granular approach, aiming to tailor marketing messages and experiences on an individual level, leveraging data-driven insights.1 This involves using customer segments and customizing content, offers, and communications to individual preferences and behaviors by using customer analytics.

Techniques for personalization include:

  • Segmentation-based Recommendations: Use insights from segmentation to personalize program recommendations
  • Dynamic Content: Modify website content or email content based on user behavior and preferences
  • Predictive Analytics: Employ predictive models to anticipate what programs a user may be interested in based on their previous actions
  • CRM Integration: Use customer relationship management systems to understand individual customer journeys and interactions

Customer Data Collection Methods

In order to get to a point where we can effectively segment and personalize, we have to collect the proper information. Data is what allows businesses to understand customer behavior. They can use various methods to collect this data. To gain a holistic picture, analysts need to collect data at every interaction point along the customer journey for market segmentation analytics. Surveys and questionnaires, for example, are direct methods through which marketers collect specific types of information about customer preferences, satisfaction levels and purchasing habits.4

Website analytics are another way businesses can understand consumer behavior. By tracking how users interact with a website—such as the pages visited, time spent on each page and the path taken through the site—companies can gain valuable insights into what customers are interested in and how they navigate online spaces. This data helps marketers optimize their website design, improve the user experience and create more relevant content.4

Social media monitoring captures real-time opinions and trends. Analyzing conversations, likes, shares and comments across social platforms helps businesses tap into public sentiment, identify new market opportunities and monitor their brand’s reputation.4

Analytical Techniques

Analytical techniques deliver insights that drive strategic business decisions. Marketers can use a combination of analytical techniques to understand what their customers have done and what they’re likely to do in the future.5

Descriptive analytics focuses on summarizing historical data to understand what has happened in the past. Analysts use data aggregation and data mining techniques to provide a clear view of customer behaviors and trends over time so their businesses can understand the broader patterns and root causes of consumers’ actions.5

Predictive analytics go a step further by utilizing statistical models and forecasting methods to identify the likelihood of future outcomes based on historical data. Businesses use predictive analytics to anticipate customer behaviors, such as purchase patterns and churn rates, and the potential success of their marketing campaigns. When they understand these future possibilities, leaders can better prepare and refine their strategies accordingly.5

Prescriptive analytics deliver actionable insights by suggesting specific courses of action. This method uses advanced technologies like machine learning and artificial intelligence to analyze potential decisions and their likely outcomes. It then recommends the best course of action for any given scenario. Business leaders use prescriptive analytics to optimize their processes, improve their decision-making and achieve their objectives through clear, data-driven recommendations.5

Key Metrics for Consumer Behavior Analysis

Businesses can measure their success by tracking key metrics. Purchase frequency, for instance, measures how often customers buy over a specific period. This indicator helps businesses understand customer loyalty and product appeal so they can gauge their customers’ engagement levels. High purchase frequency can signal an effective marketing campaign and product satisfaction, whereas low frequency might indicate areas needing improvement.6

Customer lifetime value (CLV) represents the total revenue a business can reasonably expect from a single customer throughout the relationship. CLV helps companies prioritize their resources and tailor their marketing strategies to maximize the value of their customer relationships over time. When they focus on high-CLV customers, businesses can optimize their efforts for retention and upselling by investing in the most profitable segments of their existing customer base.7

Churn rate, the percentage of customers who stop doing business with a company over a given period, identifies issues with customer satisfaction and product fit. A high churn rate can be a warning signal that prompts businesses to improve their customer retention strategy.8

Case Studies

Customer analytics drive success in many industries. For example, Starbucks has extensively leveraged customer analytics to improve its customer experience. Using data from its loyalty cards and mobile app, Starbucks was able to personalize its marketing messages and recommendations based on customers’ preferences and previous purchases. This tailored approach not only increased Starbucks’ customer loyalty but also significantly boosted its sales.9

Ikea is another big brand that has used consumer behavior analysis and insights to improve its customer experience. By analyzing customers’ movement patterns within its physical stores, Ikea has optimized its store layout to improve the flow and increase the likelihood of purchases, demonstrating how offline retail environments can benefit from behavioral analytics.10

Leverage Customer Analytics for Business Success

An Online MSBA from William & Mary will equip you with the skills you need to perform market segmentation analyses and make recommendations that will help your company increase its profitability. While you can complete your degree from the convenience of your home, learning online doesn’t mean learning alone. Our faculty are leading experts in their fields and will guide your learning experience every step of the way.

Schedule a call with one of our admissions outreach advisors today to learn more.