Customer Behavior Segmentation | Segment
An in-depth explanation of customer behavior segmentation.
What is customer behavior segmentation?
Behavioral customer segmentation groups people based on their actions – or lack thereof. In business, you form such groupings from the interactions between a brand or product and its customers.
Typical examples of customer behavior segmentation are categorizing people by purchasing behavior, customer journey stage, or engagement. We’ll look at these groupings in detail later.
The main difference with a former marketing darling – demographic segmentation – is that a behavioral approach looks at what your customers do, not just who they are. That is not to say demographic information or other forms of market segmentation are useless – far from it. The most successful companies blend several segmentation strategies to deliver outstanding, highly personalized customer experiences.
Why is customer behavior segmentation important?
Customer behavior segmentation allows you to organize your customer base into smaller groups based on their actions across your touchpoints and platforms. You can use this information to predict their future behavior and address each group’s needs with personalized marketing campaigns, tailored product journeys, and spot-on customer service.
You can also use your company’s resources more effectively with behavioral segmentation. Say you group different customers by their likelihood of making repeat purchases. You can then focus your marketing efforts on loyal customers with the highest chance to buy instead of wasting effort and money on people that are unlikely to do so.
Six types of behavioral segmentation
Here are six common customer behavior patterns you can use for segmentation.
Purchase-related segmentation categorizes customers by their likelihood of buying from you, purchase frequency, or buying considerations.
Say you create groups based on the elapsed time since their last purchase. You can then tailor special up and cross-sell offers or other reactivation campaigns for those segments. That information and other historical buying behavior can also help predict when specific customers are likely to make their next purchase.
Another way to segment purchasing behavior is by creating groups around different buying considerations during a purchase decision. For example, create one segment for price-conscious shoppers versus another for folks likely to make impulse purchases.
You can infer purchase behavior from various customer data sources, like the timing of purchases, how much people spent, and the products they look at on your website.
Segmenting by customer satisfaction groups people according to how satisfied they are with your products or services. You can create such segments based on data you collect through NPS scoring, surveys, and reviews.
Other customer satisfaction indicators can come from analyzing the sentiment of support interactions and social media posts. You can also include engagement or inactivity metrics to calculate a customized satisfaction score from multiple data points.
Whichever approach you take to determine customer satisfaction, you can then use these groups in several ways:
Target satisfied customers with cross- and up-sell opportunities.
Invite satisfied customers to your brand advocate or loyalty programs.
Analyze causes of high and low satisfaction. Use those findings to remove friction while adding nudges that lead to improved conversion rates, higher retention, and customer happiness.
Create campaigns, personalized sales or service outreach, and other interventions to avoid churn and re-engage customers that are neutral or have decreasing satisfaction.
Customer loyalty, engagement, and usage
Usage, engagement, and loyalty are similar but not the same. While there’s no fixed definition for each approach, businesses generally measure:
Usage based on activity within your product or platform. Often, usage behavior helps predict other factors such as churn, brand loyalty, or satisfaction.
Customer engagement through usage and other interactions with or about your brand, like website visits, social media mentions, or email click rate.
Loyalty through spending frequency, amount, and annual or customer lifetime value.
Say a loyal customer makes big purchases infrequently. Assuming your loyalty program is based on annual or lifetime spending, that person is then a loyal customer, but not an engaged or high-usage one.
Conversely, a daily user of your free app who talks about it on social media goes into the highly engaged and heavy user segments. They don’t classify as a loyal customer since they’re not spending anything.
When you use the customer journey for segmentation, you organize people by journey phases, like awareness, consideration, decision, retention, and advocacy. Doing so lets you tailor communications and the experience to each stage to increase conversions. You can also figure out who isn’t progressing from one phase to the next and launch initiatives to remove obstacles and move them along.
The challenge with journey segmentation is that these days, it’s often hard to tell at which stage someone is or where they might go next.
Some industries, like SaaS, have pretty linear journeys, so this approach still works. But in many others, like eCommerce, the modern, omnichannel nature of the customer experience means people can roam touchpoints with multiple devices.
Customers traverse – and sometimes skip – the traditional order of journey phases, jumping almost in real time from awareness to decision and even advocacy. Within minutes, they discover a product, buy it, and post a picture on social media.
If your business operates in such an unpredictable, omnichannel environment, other behavioral segmentation strategies like status, purchasing behavior, or usage are better choices.
Customer status segments people by their relationship to your business at that particular moment in time. A SaaS business, for example, might define their user status groups as Free, Trial, Basic, Pro, and Churned, reflecting their subscription status.
Status segmentation can overlap with other approaches but does give a different and helpful perspective, especially when you combine it with other groupings.
Staying with the SaaS example, most Pro subscribers are likely engaged. Still, some might have gone inactive and are close to churning or downgrading. This combination of status and engagement segmentation helps you discover trends within different subsets of your customer base.
You can figure out customer interests from behavioral data. The pages people view on your site, the topics they click on in your emails, and the type of products they buy tell you about their interests. By segmenting customers in this way, you can provide many personalized experiences, such as the marketing messages you send them, the products you recommend, or the content you create for your blog.
Say someone always reads articles on your website related to running. You can then add them to a segment of people that are likely interested in that sport and send them special offers for shoes, apparel, and marathons.
How do you build behavioral customer segments?
You create behavioral segments from first-party data – customer information you collect across your own channels and platforms. A customer engagement platform like Twilio Segment helps you capture all that data and synthesize it into personas and customer segments.
You can use Twilio Segment to group customers based on almost any data point imaginable, including information from uncommon sources like store visits, transactions, and custom sources you connect through our APIs.
Once you have your customer data stored and organized in this way, you can send it to hundreds of downstream tools, for example, for further analysis and marketing campaigns. And no matter how many sources and destinations you connect, Twilio Segment synchronizes new and changed data across your entire ecosystem in real-time.
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