The ultimate guide to customer behavior analysis

In the dynamic world of retail, customers are more than just shoppers -- they are active participants in a complex system of choices, preferences and decisions. From the moment they consider a purchase to the final checkout, their actions are shaped by many factors.

In this guide, we dive into the world of customer behavior analysis: what it is, how to do it, and how you can use it to maximize business success.

Customer behavior is how individuals, groups or organizations make purchase decisions and how they use and dispose of goods. It explores the behavioral process when customers decide what products to buy, accounting for factors like personal preferences, cost, environment and convenience.

When someone visits a store or website, their behavior is shaped by these factors, impacting the time spent at the store, the items purchased and their likelihood to come back and make another purchase. It’s crucial for businesses to understand customer behavior because it influences products, marketing, pricing and merchandising strategies. By analyzing the emotions, attitudes, preferences and motivations of customers, businesses can tailor strategies to convert their target audience into buyers and segment them based on their preferences to drive further engagement.

Customer preferences refer to the specific choices, inclinations and desires that individuals have when selecting products or services. These preferences are influenced by factors such as personal taste, lifestyle, cultural background, life stage and previous experiences.

Customer preferences may span:

• Product features: Customers may prefer specific features or functionalities in a product. For example, some smartphone users prioritize camera quality, while others focus on battery life.
• Brand loyalty: Customers may favor certain brands due to trust, reputation or emotional connections.
• Pricing: Price sensitivity varies among customers. Some prioritize affordability, while others are willing to pay a premium for quality.
• Customization: Personalized options, such as color choice or additional accessories, cater to individual preferences.
• Channel preferences: Customers may prefer online shopping, in-store experiences or a combination of both. 

Customer pain points are issues that negatively impact the overall customer experience. They highlight specific moments in the user experience where the customer encounters frustrations, friction or challenges with the product or service.

There are four common types of pain points:

1. Process pain points are problems relating to a design flaw or a longer (often frustrating) process for the customer to get and use a product or service. Examples include slow delivery or check-out processes.
2. Product pain points happen when a customer feels like they are investing more time and resources into a product or service in comparison to the output or value they receive from it. Examples include a product that may lack essential features or one that needs to be repaired or returned soon after purchase.  
3. Financial pain points are problems that make a customer feel like they’re losing money or overpaying for a product or service. Examples include hidden fees or lack of payment flexibility.
4. Support pain points are problems created when the customer doesn’t feel fully assisted before, during or after purchasing a product or service. Examples include lack of onboarding or poor customer support.

Customer behavior analysis looks at how customers make decisions, their product and buying preferences and how they respond to various initiatives, including marketing campaigns, product updates and offers. An analysis can include the psychological factors and social influences that lead to a decision.

Customer behavior analysis is important because it provides valuable insights for businesses to tailor their offerings, enhance customer experiences and create effective marketing campaigns and product updates. Understanding customer decisions and preferences is essential for long-term success in the marketplace.

Wondering what methods to use for a customer behavior analysis? Let’s look at the process using the example of a retail company:

• Step 1: Aggregate all available, permissible data on target customers
• Step 2: Segment your customers to better understand their interests, preferences and pain points. This segmentation can include demographics, values, challenges and life stage.
• Step 3: Evaluate your customers’ preferred channels to better understand their buying journey. Are they shopping online or in store or both?
• Step 4: Identify patterns and investigate the underlying reasons behind purchases. It could be factors like a promotion, new marketing campaign or other external influences.
• Step 5: Optimize and adjust your customer’s overall experience based on the analysis.
• Step 6: Personalize your customer outreach to enhance engagement and loyalty.

Best practices for getting actionable insights from your analyses include:

• Combine multiple data sources
• Focus on transaction-level insights

Customer behavior analysis, when done correctly, can have a huge impact on marketing and sales. Let’s look at some examples:

Myer, a leading Australian retailer, wanted to understand how customers spent money outside their stores, which would illustrate the customers’ spending power and inform direct marketing campaign strategies.

With Mastercard’s Customer Data Enhancement product, Myer was able to segment shoppers using this enhanced data. Customer Data Enhancement provided insights on customers’ spending headroom, share of wallet and propensity to spend across retail categories. This informed Myer’s overall customer management strategy and significantly improved their targeted marketing campaigns.

Customer Data Enhancement created several models, such as a luxury spend propensity model, which revealed that Myer could capture 88% of potential luxury buyers by targeting the top 10% of customers. The Customer Data Enhancement models activated lapsing customers effectively, driving over a 2x uplift in sales compared to existing targeting models.

Responding to growing consumer interest for healthier breakfast alternatives, a national grocer wanted to improve the performance of a premium granola brand. By growing sales of this leading brand in a priority category, the grocer hoped to increase overall shopper loyalty and store revenue. However, the grocer wasn’t sure which elements of its strategy to change.

Mastercard Market Basket Analyzer enabled them to dive deep into their customer loyalty, understand which products were frequently purchased together and analyze subsequent purchase behavior.

They quickly conducted a robust analysis of the premium granola brand’s performance and developed hypotheses for future testing. The process was:

1. Evaluate assortments
2. Identify common attachments
3. Assess purchase sequence

By using Market Basket Analyzer, the grocer better understood the premium granola brand’s sales, loyalty and customer behavior.

Customer behavior analysis plays a pivotal role in successful marketing, personalization, customer experiences, and more.

By delving into psychological factors and social influences, businesses more effectively tailor their offerings, enhance customer experiences, and create effective marketing campaigns, all of which are crucial for long-term success in the marketplace.