Here is our take on behavioral segmentation. What makes it important? It’s different types and examples.
Marketing is no more a one-way street. What marketing firms had to do earlier was write good copy, take amazing pictures, and strategically ensure it reaches customer attention. Customers of today are smart and have evolved to being engaged proactively based on their requirements. As per a survey, 80 percent of B2B customers hope that businesses understand their needs and align according to them.
The more important aspect is customers are now well-aware of product choices and brand options. Customers are also happy if they get more self-serve options as opposed to ticket-based support. This makes it important to know the customer journey and with B2B behavioral segmentation, we can work out a strategy accordingly.
Behavioral segmentation is a type of market segmentation that focuses on customers, prospects, audiences based on their behavior and action. The demographic segmentation study shows who makes up your customer base and what the customers do. The data suggests possible interactions with the brand. Customer behavior can be understood deeply-
Data-informed, effective behavioral segmentation can be possible with AI.
Behavioral segmentation will help you take advantage of types of behavior and align your marketing messages accordingly. New customers will be happy if they have access to introductory offers. Loyal customers will be satisfied if get a chance to join a special exclusive VIP club. This enhances how targeting takes place and creates better results.
By knowing customers’ wants, needs, and problems, you can connect with them on a personal level. Nowadays customers don’t want to look a second time at a generic email. With data insights, you can make relevant offers and tips that they will pick up. For example- If a customer is female and looking for apparel, you can personalize messaging like that.
Behavioral segmentation helps simplify things cost-wise. You can set your budget to target and engage with interested and valuable audience. This is better than spending it on uninterested cold leads. For example- If a customer is engaged with you, you can send them personalized communication and cut costs where spending is not yielding any results.
Customers will stick with a brand that makes them feel positive and special. You can increase brand loyalty when customers are happy. Customer loyalty also helps increase customer lifetime value and boost revenue for the business.
Behavioral segmentation is important to know how interactions can be improved with the brand, service, or product. These variables can help create a strategy that is sustainable and simple.
The main types of behavioral segmentation include-
Purchasing behavior is how customers behave when they are looking to purchase. Customers are involved in research and decisions, and this can be understood through AI. Another type of purchasing behavior is based on dissonance. Some customers are highly involved in the purchasing process but find it hard to pick the one they want. They will want assurance that they have made the right choice. Other customers just prefer variety over anything else. Some customers just look for the ones they are habituated to.
How does the customer use the product- how often and where? This segment understands the frequency and type of customer interaction with your business. The nature of the interaction, how long they spend, and features they use are discussed. You will know the light, medium, and heavy users and can improve your marketing strategy accordingly.
Which benefit is the customer looking for while making the purchase? Customers put some benefits on a higher value pedestal than others. For example- any shampoo may be good for cleaning hair. Customers look for ones that have terms like-
At what stage of the customer journey is the customer in? The five touchpoints include- awareness, consideration, purchase, retention, and advocacy. Segmenting and understanding behavior based on customer journey will help improve growth.
How satisfied and happy are your customers?
Customers’ wants and needs change in real-time as they move on in their purchase journey. The NPS is not the sole metric that matters. Real-time behavioral data is a correct and reliable way to measure customer satisfaction.
Loyal customers are valuable assets of the company. They have high customer lifetime value, are cheaper to retain, and contribute to brand equity. Behavioral segmentation gives you an idea of the needs of customers so that you can keep them with special rewards and privileges to improve customer relationship.
In this, you can segment users as per how much they use the business. This includes non-users, regulars, first-timers, freemium, prospects, and defectors.
How do customers interact across branded channels? This behavioral segmentation tracks all brand interaction and shows how engaged the customer is. The interactions in a brand can include-
Here are some behavioral segmentation examples that are successful.
Olay is a popular US skincare brand that has great brand recall. The company uses AI through their tool- Skin Advisor. The mobile-friendly tool finds out about customers’ skin and their routine. With the insights, the team at Olay could-
Netflix is a popular streaming service that delivers content to customers in a personalized way. The app uses AI to offer recommendations to users based on previous viewing history. This tailors information as per user profile. This improves the recommendations list and thus enhances user experience. Data collected across Netflix users will show how they use the service. This helps fine-tune the experience and ensure customers keep the binge on.
Behavioral segmentation will help you identify and develop the value proposition, personalize communication, and conduct brand research. This will help you track many metrics related to the business from awareness to advocacy. You can also know and understand customers better and improve customer loyalty. The end goal is to offer a targeted experience for every customer.27
Artificial intelligence, customer data, and automation combination will ensure that customers get better results and lead to greater yield. This will facilitate efficiency and strategic analysis of customer behavior in a positive manner.
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