Whether we like it or not, our past experiences, habits, and emotions all have a significant influence on our behavior. Many people have daily routines that force them to perform the same thing every day. As marketers, we want to know who our figurative everyday customers are and distinguish them from those who buy products more frequently.
While knowing your average customer’s region, age, and gender are important initial steps in meeting their demands, it is often required to go one step further. In this post, we will discuss the fundamentals, types, and examples of behavioral segmentation. Additionally, we’ll explain in detail how marketers may employ these tactics.
How Does Behavioral Segmentation Work?
Behavioral segmentation is the practice of categorizing and classifying clients based on their behavior. These behaviors include the items and material people consume, as well as the frequency with which consumers connect with an app, website, or company.
As marketers, we frequently walk a fine line between psychology and business. We often bring our marketing beliefs about how people will react to a marketing effort. Behavioral segmentation is the monitoring of each customer’s behaviors in order for marketers to offer personalized content to them.
Once users are recognized based on their individual activity, mobile marketers may adapt messaging and campaigns to these groups.
Why is Behavioral Segmentation Important?
Once users are recognized based on their individual activity, mobile marketers may adapt messaging and campaigns to these groups. Behavioral segmentation has several advantages:
Behavioral segmentation tells you more than simply what product or service a certain set of clients like. It enables you to learn which channels they use and what sort of messaging they respond to, allowing you to increase conversions.
- Budget allocation
Now that you know which groups spend the most and how they spend, you can better target them with your efforts.
By analyzing the patterns of each sector, you may discover trends and prepare for the future more efficiently.
4 Types of Behavioral Segmentation
There are four forms of behavioral segmentation that may be used to create a full consumer profile throughout the purchasing cycle. Each aspect provides actionable information that can be placed in a number of marketing channels to encourage customers to follow through on their purchasing decisions.
Purchase and usage behavior-based segmentation
Understanding specific consumer behavior patterns can assist enhance customer experience and satisfaction. This is about how a consumer behaves while making a purchasing choice. Do they read every single detail that comes with the product/service? Or do they go with the recommendation of their relatives and friends? Or do they buy things out of habit?
In other words, research the things that impact their purchasing experience and use those features more frequently in your app marketing plan. And, eventually, greater profits.
Purchasing on occasion
This behavioral segmentation component evaluates the timing of a customer’s life, year, or day as a determinant of making a purchase.
Starbucks employs behavioral segmentation to target its regular morning customers with an incentive to return later in the day for another purchase. It employs email marketing and pushes alerts inside their mobile app to advertise happy hour events since these frequent customers are likely to grab an afternoon coffee on occasion.
Customer loyalty-based segmentation
Loyalty-based segmentation assesses a customer’s level of loyalty to your brand, whether through a rewards program, the number of transactions made, or overall participation in your marketing activities.
Using loyalty-based behavioral segmentation allows you to focus on existing repeat consumers, their demands, behavior patterns, and other factors. Aside from producing recurrent sales for your company, loyal consumers are extremely beneficial in terms of recommendations, word of mouth, and feedback.
Segmentation of benefits desired
Segmenting by benefits desired means separating your audience based on the one-of-a-kind value proposition your consumer expects from your product or service.
Grouping your data by benefits sought allows you to zero in on the intricacies of what motivates client purchases, exposing the product feature or service component to which they are most sensitive.
5 Examples of Successful Behavioral Segmentation
When utilized correctly, behavioral segmentation may provide remarkable results, converting previously cold leads or customers into freshly engaged and kept ones. Here are some real-world instances of behavioral segmentation at its most nuanced and effective.
Examine the following examples of behavioral segmentation to motivate your marketing team.
BabyCentre UK is a pregnancy and childcare resource that is part of the Johnson & Johnson global enterprise. The startup uses a Facebook Messenger app to provide tailored advice and targeted suggestions depending on the user’s input via a series of questions and replies.
The tailored interaction provides BabyCentre with relevant data, allowing it to classify the user according to their choices. For example, their child is in the age group that goes through weaning. This data may be used to target customers with repetitive, relevant material, such as recipe instructions or other useful suggestions.
Guinness sponsors the Guinness Six Nations Rugby Cup every year and sees sales increase as a result of fans purchasing drinks to accompany the game.
However, with industry statistics indicating that 6.1 million people actively choose not to consume alcohol, Guinness wanted to diversify their marketing strategy to appeal to those who don’t drink, while having the aim to preserve existing clients.
While alluding to the brand-new component of H2O, the ad featured phrases such as “Make it a night you’ll remember” and “Sometimes less is more”. The promotion reached 21 million people and drew rapid global media interest, with purchasers unsure if the product was a new product or simply water.
When developing its Skin Advisor, the American skincare company Olay employed benefits-seeking behavioral segmentation. The artificial intelligence beauty product gathers consumer information by posing five to seven straightforward inquiries about their skin conditions. The adviser then discloses the real age of the customer’s skin and makes product recommendations appropriately.
By asking customers questions about their skincare regimen and preferences, Olay may gather data that can affect product development, allowing the company to release goods that are most desired and relevant to its clients.
DavidsTea is a Canadian special tea retailer looking for a unique approach to communicate with its most loyal consumers. The chronological layout of their emails has received universal acclaim, making them one of the greatest examples of email marketing to date.
When a client achieves a specified anniversary, they receive a “look back” email that includes the occurrence of the first transaction, data such as their most purchased teas.
Consumers will be more likely to continue purchasing if they receive this email, which makes them feel special and cherished throughout their customer experience.
They employ machine learning to derive insights from user evaluations and are prominently featured on the website so that it is the first thing a visitor sees when they arrive at their home page. They match hosts and guests based on behavioral data and customer interests. This is made feasible via AirBnB’s customized search algorithm. They also employ different tracking technologies, such as cookies, to guarantee that the correct match occurs.
Behavioral segmentation is the technique of categorizing your consumers based on the natural behavior patterns they display while interacting with your company. Businesses that use behavioral data include Starbucks’ incentive program and Sephora’s loyalty program.
Companies may discover gold by leveraging behavioral segmentation data with the appropriate goal and technique. If you can use AI and ML with your marketing, it will be much more effective, and you will be able to make your messaging/offer stand out as much as possible.