Behavioral segmentation

Behavioral segmentation divides customers into groups based on observable behaviors, such as pages visited, purchasing behavior, preferred engagement channels, and loyalty.

Behavioral segmentation is a good starting point for B2C brands that want to implement or scale personalization.

Marketers can use behavioral data to deliver the right marketing message on the right channel at the right time within each buyer's journey. For example, some customers like to browse and buy in one web session, while others research for weeks online before purchasing a product at a store.

How do industry leaders segment their audience for personalization? Find out in our report on industry segmentation patterns.

Grouping customers through behavioral segmentation helps companies:

• Predict future customer behavior.
• Prioritize customers with the highest customer lifetime value.
• Target customers with messaging designed to influence behavior.
• Identify upsell and cross-sell opportunities.
• Improve products and customer support.
• Increase brand loyalty.

The benefits will depend on which behavioral factors you target and how you use them to enhance your marketing strategies.

Segmentation based on purchasing behaviors

Factors used to segment customers based on purchasing behaviors include:

Frequency of purchase: Identify your most loyal customers and target them with special offers or loyalty programs.

Type of product(s) purchased: Target customers with offers for related products and accessories.

Channels used to make purchases: Close the sale through their preferred channel.

Occasion or time-based behavioral segmentation

Occasion-based segmentation focuses on how customer behaviors change during special occasions, life events, and seasons. This form of segmentation enables businesses to understand and predict customers' buying cycles, enabling them to target marketing efforts and increase sales.

Bloom & Wild Group, Europe's leading online flower- and plant-delivery company, uses occasion-based segmentation to delight customers with holiday-specific content and offers.

By combining data on purchasing behavior with customer preferences, Bloom & Wild Group delivers the perfect content arrangement for each customer.

Read the case study.

Benefits sought segmentation

Behavioral segmentation based on benefits sought categorizes audiences based on the benefits each customer values the most.

For example, if you sell health insurance, you might have one group of people looking for the cheapest possible plan, and another group more concerned with getting the best coverage. With this knowledge, you can target customers with marketing materials highlighting the benefits or features that matter most to them.

Customer loyalty segmentation

Loyalty-based segmentation assesses a customer's degree of loyalty based on factors such as how often customers make purchases, how much they spend, and how long they’ve been shopping with the company.

Companies can target loyal customers with personalized marketing campaigns and reward programs to strengthen the relationship.

See how global brands like Ruggable, Breitling, Affirm, and Help Scout use loyalty-based personalization to lift conversion rates and increase revenue in this downloadable guide.

Product usage behavior segmentation

Product usage shows what types of customers use your products the most and can be a strong indicator of loyalty. You can segment users into:

• Super users: Spend the most time on your product or services.
• Average users: Use your product regularly, but not like super users.
• Light users: Use the product or service very rarely.
• Ex-users: Customers who have stopped using the product.

Customer journey stage segmentation

Customer journey stage segmentation looks at how customers behave during different journey stages and allows marketers to tailor content specific to the customer's needs at each stage.

For example, using the AIDA model to divide the buying journey into four stages reveals how the customer's needs progress from high-level content to more detailed information about how a product or service will benefit them.

The AIDA model divides the buyer's journey into four stages:

1. Attention: Also called the awareness stage, this is when the customer becomes aware of the product or service.

2. Interest: The customer develops a deeper interest in the product or service.

3. Desire: The customer starts thinking about how they would use the product or service.

4. Action: The customer is ready to take action or purchase the product or service.

Segmentation based on engagement

You can measure customer engagement in many ways, including frequency of purchase, level of interaction with a company's website or social media accounts, and whether or not a customer recommends a company's products or services to others.

Engagement data helps identify what messages and channels work best with different audiences so you can personalize experiences to cater to their preferences and increase engagement across segments.

Segmentation based on customer satisfaction

Customer satisfaction data helps marketers understand how well products and services meet expectations, who will likely recommend you to a friend, and where showing extra love or added support could improve retention.

Here are some examples of how you can use behavioral segmentation to enhance your marketing initiatives:

Increase sales with upselling and cross-selling

The most basic usage form of behavioral segmentation is targeting customers who have completed a purchase with a related offer. For example, you might recommend luggage tags, travel pillows, and other travel-related products to a customer who recently bought luggage.

Retarget customers based on their last action

Knowing a customer's last action enables you to use retargeting campaigns and personalized messages to reconnect and move them forward. For example, many retailers send a friendly reminder when you leave items in your cart to help reduce cart abandonment. Retargeting campaigns can also let returning visitors pick up on the page where they left off for a more seamless experience.

Personalize product recommendations

Companies like Amazon, Netflix, YouTube, and Spotify use behavioral data to build highly accurate recommendation engines that deliver personalized recommendations that increase sales.

Dial-in message timing

Everyone has different daily routines. Some people check emails and social media first thing in the morning, and others might catch up on messages over lunch. Segmenting customers based on when they engage on various channels, use your products, or like to shop lets you personalize the timing of push notifications and other content to increase engagement.

Build effective loyalty programs

Tailor loyalty programs to appeal to different behavioral segments. For example, you can offer personalized offers based on purchase behavior or let people customize their loyalty rewards based on their interests.

Identify your best traffic sources

Behavioral segmentation enables companies to understand where their best customers come from based on conversion rates, customer lifetime value, and time spent on a website or app.

Like most forms of customer segmentation, behavioral segmentation works best when combined with other data. Other challenges include:

Acting in real time: To make the most of behavioral data, companies need the ability to act on the data in real time — for example, personalizing product recommendations based on what products a customer looks at in that browsing session.

Privacy: While a lot of behavioral data can be collected through customer interactions, it’s important to get consent, enable customers to opt-out, and protect their privacy.

Combining qualitative data and quantitative data will provide the most accurate customer view for behavioral segmentation.

Qualitative data includes first-party data gathered via surveys and interviews that can provide more insight into how people use your products, what channels they prefer, and how satisfied they are.

Quantitative data includes website and mobile tracking (with consent), shopping data from your ecommerce systems, and product analytics.

See how easy it is to set up segments and start delivering personalized experiences with AI-native personalization, or contact us to see how Contentful can help your business scale personalization faster.

Up next: Firmographic segmentation

Learn how businesses use firmographic segmentation to target clients by industry and company size. Discover how to collect data for personalized outreach.