Six super useful segments from customer behavior data
You get customer behavior in marketing and common types of customer segments from data.
However easy it seems to do, the reality is that customer segmentation's execution to gain value is still hard. This challenge is not new. Over ten years ago, Bain & Company surveyed executives about their experiences with customer segmentation, and 81% said it was a critical tool for growing profits. Still, fewer than 25% believed their companies used it effectively. I have seen that number has merely risen to about 35% these days. But regardless of the current difficulties, customer experience in the driver's seat, and personalization as the destination, segmentation is a must-have for businesses, especially eCommerce.
Customer segmentation and buyer types have always been important, but effective segmentation is even more critical now that personalization and customer experience determine a business's success. Entering into a more traditional marketing team, you will recognize these six main types of behavioral segmentation.
1. Occasions Driven
Probably the easiest to implement because you don't need a lot of historical data on your customer. Occasion and timing-based behavioral segments refer to both universal and personal events. From biggest to niche:
Universal occasions apply to most customers or target audiences and consist of holidays and seasonal events when consumers are more likely to make special purchases. In the United States, Cyber Monday is still the biggest eCommerce day of the year, for example.
Recurring personal occasions may depend on your product or service, but looking for a repeat purchase is a big part of retention. Recurring-personal purchasing occasions can be found in your user journeys and transaction history. Also, look for individual customer attributes that consistently repeat over some time. For example, birthdays, anniversaries or vacations, monthly purchases, or even rituals like the Sunday morning lottery tickets.
Rare-personal occasions are also related to individual customers or very niche segments but seem spontaneous or special, and they can be surprises- thus more challenging to predict. For example, you buy a bridesmaid dress for your best friend's wedding.
2. Feature Seeking Segments
You understand your product offering and break it down by the features or purchase reason. A customer buying a new sofa can look for four bases: comfort, fashion, function, or price.
When customers research your product or service, they reveal valuable insights regarding the most important benefits, features, values, use cases, or problems. These motivating factors influence their purchase decision. In eCommerce, you can analyze the most common search terms, categories, and survey answers to get the data you need.
When a customer places a much higher value on one or more benefits over the others, these primary benefits sought are the defining motivating factors driving that customer's purchase decision.
3. Customer Status
Here is a list of common customer statuses in email applications like MailChimp and SendGrid or customer relationship management (CRM) solutions like SalesForce. It is essential that sales and marketing stay aligned on the meaning of these statuses. These statuses are defined based on the individual business needs:
Non-users
Prospects
First-time buyers
Regular users
Recent Purchase
Asleep
4. Usage Scores
Product or service usage is another common way to segment customers by behavior based on the frequency at which a customer purchases or interacts with a product or service. I have seen these segments get defined by rules within transaction or order data. Usage behavior can be a strong predictive indicator of loyalty or churn and, therefore, lifetime value.
Heavy Users
Super Users
Trial Users
Seasonal Users
5. Loyalty participants
Loyalty programs are the best way to get key customer information. And loyal customers are a business's most valuable assets. They are cheaper to retain, usually have the highest lifetime value, and can become brand advocates.
By analyzing behavioral data, customers can be segmented by their level of loyalty so marketers can understand their needs and make sure they satisfy them.
Loyal customers are the ones who should receive special treatment and privileges, such as exclusive rewards programs to nurture and strengthen the customer relationship and incentivize continued future business.
6. Customer journey based
Segmenting the audience base on buyer readiness allows marketers to align communications and personalize experiences to increase conversion at every stage.
Moreover, it helps them discover stages where customers are not progressing to identify the biggest obstacles and opportunities for improvement, even on postpurchase behaviors.
Besides these traditional ways, another type of segmentation is the RFM model.
RFM comes from Recency, Frequency, and Monetary Value. Here are the components.
Recency = how recently a customer placed the last order on your website
Frequency = how many times a customer purchased something from your website in the analyzed period
Monetary value = how much each customer has spent on your website since the first order.
The RFM model analysis can be more powerful with automated RFM dashboards that technology vendors like VIEWN provide with a CDP.
From the RFM segmentation and analysis, you can not only reveal what your most loyal and profitable customers or less profitable customers are but also:
Reveal what brands and products are costing your business
Build custom recommendations and reviews for your customers
Solve specific Customer Experience problems mainly related to the customer journey.
Before making decisions based on instinct or that gut feeling regarding your customers and your audience, observe their behavior, collect the data, and listen to them via surveys and interviews.
