GUIDES
Analysing customer data to understand buyer behaviour
Customer Behavior Analysis
What is customer behavior analysis?
Behavior analysis refers to methods used to try to understand behavior using a scientific methodology. The study of behavior analysis includes understanding the “why” behind the behavior, how behavior changes, and what can be introduced to an environment to alter behavior. The field of behavior analysis is a broad one.
However, when applied more specifically to groups such as consumers, it can be an effective tool for retail businesses. Customer behavior analysis doesn’t just focus on who is shopping but on how and why they are shopping. A customer behavior analysis example may include shopping frequency, customers’ preferred products, and shoppers’ perception of marketing efforts.
A customer behavior analysis model is used as a guide when studying consumer behavior using behavior analysis. It is a theoretical framework to outline predictable customer behavior up to conversion.
A customer behavior model may fall into several categories. Traditional behavior analysis models include:
- Learning model: assumes that buyers’ motives are based on basic needs
- Psychoanalytic model: assumes customers have subconscious motives
- Sociological model: assumes that buyers are influenced by societal groups
- Economic model: assumes customers want to spend as little as possible
Having customer behavior analysis tools in place is essential to studying customer behavior effectively. Using a customer data platform (CDP) such as Lexer gives you the ability to utilize our powerful artificial intelligence (AI) predictive analytics and surveys to uncover insights beyond the direct customer relationship.
Consumer behavior analysis
A modern consumer behavior model considers deliberate decisions consumers make based on actionable steps retailers take to increase visibility, offer money-saving deals, or implement various stimuli to influence customer behavior. Understanding consumer behavior analysis will help retailers understand their customers’ behavior and empower them to influence the buying decisions those customers make.
There are several ways to conduct consumer behavior analysis using customer behavior data. A customer data platform (CDP) is valuable because it can help you better understand consumer buying behavior. Data collected for customer behavior is not limited to purchase-only interactions. Today, many business-to-consumer (B2C) interactions occur through social media, emails, advertisements, shopping apps, loyalty programs, and in-store interactions. By collecting consumer behavior data at each point of contact, retailers can perform a complete consumer behavior analysis.
A customer data platform (CDP) such as AI-powered Lexer can integrate data from multiple consumer interaction platforms and streamline them into a single interface for detailed consumer behavior analysis. Data insights are collected automatically using AI technology. AI-powered analytics provide results from the metrics you want to focus on and can give you a real-time picture of consumer buying behavior. Furthermore, they can also give you a predictive model that helps retailers craft more personalized experiences and marketing campaigns.
Applying consumer behavior theory to the collected data will give retailers a better understanding of why consumers are making purchases and predict if they will continue to do so in the future. Predictive analytics allows retailers to decide if current marketing efforts are working or if changes need to be made to increase consumer buying behavior.
Importance of consumer behavior
The importance of consumer behavior goes beyond traditional marketing. Today every intersection of customer interaction matters in terms of brand recognition, brand loyalty, and consumer buying behavior. Understanding how buyers feel, think, and make decisions, empowers retailers to market their brands and products in a more personalized way. Personalization and customer experience are what matter most in today’s market.
Personal, social, and psychological factors are the defining characteristics of consumer behavior.
- Personal factors: individual interests and opinions. Personal factors are influenced by demographics such as age, gender, gender identity, or culture.
- Psychological factors: perceptions and attitudes affect responses to marketing messages
- Social factors: such as friends, family, social media, education level, and income.
The importance of consumer behavior is emphasized by the fact that almost everything we see today involves some marketing effort. Traditionally society experienced advertisements through radio, television, and print advertisements that were seen for only short periods of time per day. Today society lives with twenty-four seven online access for work, social and entertainment marketing is occurring all day, every day, including social interaction through social media. For retail businesses capturing data from all of these interactions, this analysis is an essential part of understanding the characteristics of consumer behavior.
Using a consumer data platform (CDP) to streamline and analyze consumer behavior helps businesses segment customers and determine the characteristics of consumer behavior by segmentation. Then a consumer behavior model example can be devised to help personalize consumer experiences and influence consumer purchasing behavior based on specific segments of customers. Sorting all the data is simplified using artificial intelligence-powered CDPs such as Lexer.
Customer behavior analysis marketing
Customer behavior analysis marketing highlights the enormous impact of marketing strategies on consumer behavior. It is a two-way street between the consumer and the retail business. Consumer behavior influences marketing decisions, and, in turn, marketing decisions affect consumer behavior. Companies must find software solutions that capture and analyze consumer behavior data and then present it in a clear, easy-to-understand way. In addition, the ability to capture data from multiple sources and integrate it onto one platform is critical. Marketing moves quickly, and understanding consumer behavior in marketing empowers marketers to make the best decisions for their brands and customers.
Lexer’s marketing solution helps businesses analyze customer behavior to orchestrate personalized marketing experiences across paid and owned channels. Intelligent analysis powered by artificial intelligence (AI) allows companies to target segmented groups with the proper marketing at the right time – thereby attracting high-value customers. Innovative insights using surveys enhance customer behavior marketing analysis with real-time customer insight.
Customers interact with brands and businesses in various ways, including but not limited to making a purchase. Data from all points of interaction help companies form a complete picture of consumer behavior. Then, companies can apply a consumer behavior model in marketing. In addition, AI-powered consumer data platforms can segment consumer behavior data. Segmentation combined with consumer behavior analysis helps businesses develop intelligent predictions and a deeper understanding of customer behavior and purchase patterns.
Choosing a customer data platform (CDP), like Lexer, that can integrate data quickly and efficiently will position businesses to move forward in a customer-centric way. This is exactly what today’s market demands as consumers respond to transparency, personalization, and positive experiences while purchasing products.
Customer behavior prediction
Customer behavior prediction is a valuable way to use consumer behavior data for predictive analysis. It involves analyzing customer data gathered from multiple sources and using customer insights to anticipate consumer behavior before it occurs. Examples of a customer behavior prediction include grocery-ordering apps pinging when a customer’s favorite items go on sale and highlighter a customer’s preferred eCommerce payment method at checkout. Both of these examples predict a customer’s behavior based on past behaviors. Data is gathered at different points of engagement and then analyzed to predict buying behavior using machine learning or artificial intelligence (AI).
Customer behavior prediction models are structured theories that attempt to explain a customer’s purchasing decisions. These models aim to outline a predictable map, showing customer decisions through every interaction with a brand or store up until conversion. Insights about customer behavior from customer behavior prediction models can help retailers steer every step of a consumer journey.
The Lexer Customer Data Platform (CDP) uses the latest artificial intelligence (AI) and marketing models to create intelligent metrics to predict what customers will do next. You can transform raw data into individual customer profiles with an AI-powered customer data platform. Segmented, individualized data helps you understand your highest-value customers comprehensively. An AI-powered CDP efficiently performs data analysis on an integrated platform using customer behavior data from multiple channels. Choosing the right customer data platform, like Lexer, empowers you to apply data-driven decisions quickly.
Customer behavior dataset
Market research and consumer behavior go hand in hand. When conducting market research, businesses collect a customer behavior dataset generated by customer interactions across multiple channels. Data about customer behavior is no longer limited to purchase points or cumbersome instore surveys. Now digitized surveys, social media interactions, email activity, purchases, and many other engagement points provide data for a customer behavior analysis report. Analyzing the consumer market involves collecting mountains of data that can be intimidating for many companies.
Using intelligent customer data platforms like Lexer provides customer analysis using machine learning (AI). Segmenting, analyzing, and providing individualized customer profiles from customer behavior datasets collected across all engagement channels. Simplifying and streamlining market research and consumer behavior analysis.
Valuable customer behavior data set analysis uses actionable artificial intelligence to help retailers predict customer behavior. Benefits from using an AI-powered customer data platform include increased customer retention and decreased customer churn. Maximizing profitability potential with market research and customer behavior predictions using a top-rated customer data platform like Lexer helps companies stay competitive in today’s market.
A customer behavior data set collected from multiple channels and integrated onto one consumer data platform allows companies to conduct more accurate consumer behavior analysis. Lexer is an example of an AI-powered platform with easy-to-use tools and detailed reporting empowering you to make data-driven customer-centric decisions. Pre-built integrations allow you to quickly utilize the data from your customer behavior dataset to perform consumer behavior analysis. Enrich your customers’ experience and influence buying decisions with valuable insights.
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