Identifying the factors shaping customer behavior and decision-making has never been easy. Keeping pace with the constantly evolving preferences and needs of the target audience is also challenging, which is why marketers put in so much effort to understand them through artificial intelligence and deep customer data analysis. In this article, we will also look at customer behavior definition and specifics, overview the factors influencing it and provide you with actionable marketing strategies based on your customers' behavior patterns.

What is Consumer Behavior

Customer behavior is a set of sequential actions customers take when deciding on a particular purchase. It includes a wide range of activities, such as information search, evaluation of alternatives, purchase decisions, post-purchase evaluation, and feedback. 

According to consumer behavior psychology, there are four main types of buying behavior:

• Complex buying behavior. When customers are about to buy an expensive, risky, or important product, for example, a new car or house, they tend to show this behavior pattern. In this case, they do extensive research and evaluation, consider several options, and carefully weigh all the pros and cons before making a final decision.

• Dissonance-reducing buying behavior. This type of purchasing behavior is typical for customers whose knowledge of the product is either limited or who have no user experience with such a product before. For instance, those buyers who decided to switch from macOS to Windows may feel dissonance or doubt about their decision because of unrealistic expectations.

• Habitual buying behavior. This is the simplest buying pattern. According to it, users make a purchase effortlessly, without much thought, and that's why this behavior is mainly typical for low-to-medium priced consumables, like toothpaste or laundry detergent. Usually, they have strong brand loyalty and buy the product because they have long been used to it.

• Variety-seeking behavior pattern. As the name suggests, the customers who exhibit this buying behavior seek new experiences and variety in their purchases. Ordering a new type of coffee for a coffee machine can be one of such consumer behavior examples.

Main Factors that Impact Consumer Behavior

Each of the behavior patterns explained above is also influenced by factors that can be divided into four groups.

• Cultural factors. Customers from different cultures have different values and attitudes that influence their shopping choices. Religious beliefs and practices can also define consumer behavior in relation to the types of products or services that are acceptable or forbidden. For example, a Muslim woman will never buy a mini-skirt.

• Social factors. Social factors include the influence of family, friends, and other social groups on a consumer's behavior. In addition to these reference groups, social media shapes buying behavior significantly, making users follow certain fashion trends and buy the products recommended by celebrities, bloggers, and opinion influencers.

• Personal factors. Personal factors include but aren't limited to age, income, occupation, lifestyle, eco-awareness, and personal taste. Consumers' personality traits and self-concept can also influence their purchasing behavior, such as their need for achievement, affiliation, or self-expression.

• Psychological factors. Psychological factors are related to customers' motivation that triggers their purchase decision and perception, for example, a perception of a price-quality ratio.

Consumer Behavior Models

In addition to customer behavior types and the factors influencing them, there are also customer behavior models. Understanding them is essential for marketers to have a complete picture of the ways people make buying decisions, so let's take a look at them as well.

As for the model of consumer behavior definition, it is a factor-based framework that can be helpful for understanding and predicting the ways customers decide on a purchase. Below are the most common customer behavior models:

• The Economic Model. It suggests that the customers buy a certain product or service guided by self-interest or clearly defined need and want to get the best value for their money.

• The Learning Model. According to this model, the customers make a purchase decision after learning about the product or service through step-by-step interaction with the brand. In this way, they move from the top to the bottom of the classic sales funnel, going from awareness and consideration to purchase and post-purchase.

• The Psychoanalytic Model. This model suggests that consumers' purchasing decisions are influenced by their unconscious desires and motivations. For example, a consumer may purchase a luxury car not only because of its features and performance but also because it satisfies their unconscious desire for status and prestige.

• The Sociological Model. As the name of this model suggests, the customers' social environment is decisive for the purchases they make, including their family, friends, and other social groups. For instance, customers who are part of gym-goers or yoga enthusiasts’ social groups can buy athleisure clothing.

Why is Consumer Behavior so Important for Marketers

So, shopping behavior patterns are pretty different and depend on multiple factors. Some of them are easy to define with the help of customer behavior analysis, while predicting emotional purchases, for instance, is more challenging. That's why understanding consumer behavior is so important for marketers. With an in-depth insight into the customer's demographics, income, social environment, spending habits, pain points, motivators, and desires marketers can develop products and services best catered to the customer's needs and promote them with the help of hyper-personalized marketing strategies.

Consumer behavior can also inform pricing strategies. By understanding what consumers are willing to pay for a product or service, marketers can set prices that are competitive and attractive to their target audience. For example, a budget airline may offer low prices to attract price-sensitive consumers.

6 Best Marketing Strategies Based on Consumer Behavior

Below are some of the digital marketing strategies based on customer behavior data.

Product recommendations

Product recommendations that can be shown on the website, in a mobile app, or delivered via an email letter are the effective behavior marketing strategy you can consider for your business. It allows for unleashing unlimited marketing creativity. As an option, you can embed a "Customers also viewed" section to use the power of social proof and make the visitor dwell on the website, comparing the options. You can also recommend "New Arrivals" to let customers try something new. "The Best Fit For Your Product" recommendation is also a worth-try practice for up-selling and cross-selling.

Here is an example of how Dnipro-M, a Ukrainian construction tools retailer, embeds the “Bestsellers” section on their website. With the help of Yespo, the ROI of their personalized product recommendation grew by 23,5%.

In addition, segmenting different types of customers into groups and providing personalized recommendations for each is one of the proven ways to boost digital customer experience and customer loyalty. For example, with the help of the Yespo customer data platform, you can build dynamic segments, set up segmentation by events and provide relevant recommendations in response to users’ actions and take the expectations of each group into account.

Personalized omnichannel communication

Omnichannel marketing communication is a behavior-based marketing strategy that involves reaching out to customers across multiple channels in a coordinated and personalized way. This approach recognizes that modern customers interact with brands through a variety of touchpoints, such as email, mobile and web push messages, SMS, and instant messengers. By consolidating all these channels into a single system, you can create custom communication workflows based on user behavior, reaching out to them at the right place and time.

For example, by using behavioral segmentation and analytics, businesses can send automated messages in response to specific actions taken by the customer. As an option, after the customer has placed an order, you can send them a "Thank You For Your Order" email and share a personalized discount incentive for the next purchase.

Here is how you can use an omnichannel communication strategy:

• Send reminders at the right time. For example, if the customer orders pizza with your app every Friday, it would be right to remind them of it.

• Keep the users informed. After the customer made an order, they would be happy to receive an order confirmation, shipping update, or payment reminder.

• Gather customer feedback. After the customer receives their order, you can ask them to share their impressions and provide feedback by rating their experience with a tap or taking a short survey.

So, by building a behavior-based omnichannel marketing strategy, businesses can deliver a consistent experience for their customers, leading to stronger relationships and greater loyalty.

Behavior-based website widgets

Implementing behavior-based widgets is another effective tactic for interacting with prospective leads and current customers. Below are some of the ideas to consider.

• Convert leads into customers with a popup discount for the first order.

• Encourage new visitors to subscribe with a newsletter subscription popup.

• Retain those intending to leave the website with exit-intent popups.

• Invite those users who browsed the FAQ section to start the conversation with the brand via a chatbot.

• Share a personalized promo code with the customers who have abandoned a shopping cart and are intending to leave.

By using these types of widgets, businesses can capture the attention of visitors, encourage customer engagement, and increase conversions. However, it's important to use these tools strategically and avoid overwhelming visitors with such interactive elements. With the help of Yespo, you can create and embed responsive widgets, customize them according to your brand style, set flexible display rules, and track their performance within a single platform.

Retargeting ads

The essence of retargeting is simple and purely behavior-based. Retargeting is a digital marketing strategy that uses cookies or tracking pixels to follow users who have visited a website. For example, after the customer has abandoned a product view, the company can retarget them with social media advertising. The main goal of retargeting is to remind the customers of the brand and re-engage them.

Custom loyalty programs and gifts

Encouraging your customers in response to their interaction with your brand is always a good strategy. For example, you can offer free delivery for those user groups who purchased a certain number of items and whose order value reached a certain sum.

As for a more advanced strategy, you can develop a personalized and behavior-based loyalty program for each of the customer segments. In this case, you have to analyze customer data, like purchase history and frequency, product preferences, and feedback. Then, depending on the financial reasonability, you can custom-tailor the rewards. For example, those customers who stay with your brand for over a year may get a 10% discount for all their orders, regardless of the order value.

Predictive customer data analytics

Predicting customer behavior is an advanced marketing strategy based on data. The toolset to implement it includes machine learning algorithms, predictive modeling software, and data visualization applications, so when used together, they allow for catching invisible consumer purchase behavior patterns. For example, a subscription-based business may use predictive analytics to identify customers who are most likely to cancel their subscriptions, and then offer targeted incentives to keep those customers engaged.

The goal of customer data predictive analytics is to spot customer behavior trends, anticipate their needs and custom-tailor marketing campaigns accordingly. Such a tactic also allows for advanced customer segmentation.

How Yespo Helps with Collecting Customer Behavior Data

Now, let’s discover how the Yespo customer data platform can help you with data collection and analysis.

Create a Single Customer View

Yespo CDP creates a unified customer profile that combines data from multiple sources, allowing you to gain a comprehensive view of each customer and their interactions with the brand.

Leverage behavior-based segmentation

Next, you can segment your users based on customer behavior, such as purchase history, website activity, and engagement with marketing campaigns. Advanced segmentation enables you to create targeted campaigns that are more likely to resonate with each customer.

For instance, Multiplex Cinema, one of our customers and one of the largest entertainment services providers in Ukraine, leveraged behavior-based segmentation to custom-match the media content to the users’ preferences. The company also segmented users depending on their location to personally invite them to their favorite and/or nearest cinema. Then, Multiplex proceeded with post-sales communication by informing customers about upcoming events in the cinema they are used to visiting. As a result, the company increased ticket sales by up to 50%.

Analyze user engagement across the campaigns

With the help of our platform, you can get detailed insights into user engagement across all marketing campaigns, measure their performance and make data-driven decisions to optimize future campaigns for better results.

Conclusion

Understanding consumer behavior is crucial for businesses to develop effective marketing strategies and get a competitive edge by matching the product or service to the customer's expectations. A customer data platform is just a solution custom-matched to this goal.

For example, Yespo can gather customer data across multiple data sources, analyze customer behavior trends, and segment customers into groups. With our solution, you can provide personalized product recommendations, create event-triggered workflows, and engage customers across multiple communication channels.

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