Customer Segmentation Models: The What, Why & How
Learn about the different models of customer segmentation and how to use them for more granular targeting.
For marketing campaigns to be effective, they need to be delivered to the right people, in the right places, and at the right times in the customer journey. The only problem is that your audience consists of real people with individual values, needs, and habits. So how can you personalize your brand’s messaging to create a unique, end-to-end customer journey for each of your users?
By using the right customer segmentation model.
Before we dive into the specific types of segmentation models, let’s get more clarity around customer segmentation as a whole and identify why it’s such a powerful strategy.
What is customer segmentation?
Customer segmentation is the act of grouping your audience into sub-categories based on similarities in user profiles. Segmentation allows you to find the best content, channel, and timing for your campaigns to be sent to potential leads or current customers. It empowers you to provide personalized experiences along each touch point across the user journey. As you create user profiles and segment your audience based on similarities within those profiles, you’ll get a better sense of each segment’s unique pain points. That way, you can create messages that resonate more deeply with that group to improve brand authority and increase conversions.
For example, Mailchimp found that segmentation led to 14.31% higher email opens and 100.95% more clicks than non-segmented campaigns. DigitalOcean found that creating user personas for hyper-targeted messaging led to a 33% improvement in cost per conversion. And there are countless other studies that demonstrate how powerful customer segmentation can be. Despite its benefits, though, ElevationB2B reports that: 15 percent of B2B companies feel they have a complete view of their customers (versus 20 percent of consumer companies), and only 19 percent say they understand the customer journeys that matter most to core segments (versus 31 percent of consumer companies).
That means many marketers don’t feel as though they confidently understand who their customers are and what they want. With the right customer segmentation model, though, you can focus your attention on a specific subset of your audience to improve the results of your marketing campaigns.
What is a customer segmentation model?
A customer segmentation model is a specific way of dividing your audience into groups based on shared characteristics. For example, demographic segmentation would involve creating audience sub-groups based on their demographic similarities, like age, gender, location, job title, and income. The goal is to personalize your messaging to resonate more deeply with each segment of your overall audience.
The different customer segmentation models
There are several options when choosing a customer segmentation model, which vary in importance based on your industry and brand. Let’s look at several common segmentation models in more detail.
In behavioral segmentation, you tailor your marketing efforts based on how a user interacts with your brand.
One of the best examples is setting up an automated email or SMS series when someone downloads an ebook from a website. The act of downloading the ebook is a specific and trackable behavior. That lets you know what kind of content these subscribers are interested in. This way, you can personalize the follow-up messaging to deepen the relationship with your new lead and, eventually, bring them to your product or services.
Demographic segmentation is when you group your audience into sub-categories based on their demographic information. This would include things like:
Demographic segmentation is incredibly powerful, and it’s usually one of the first places businesses start when they create a customer segmentation strategy. In a B2B context, for example, it would be valuable to know your recipient’s job title so you can tailor messaging to their unique professional pain points. In B2C marketing, other demographic information (particularly age, gender, interests) allows you to present personalized offers, like an apparel company recommending different products to customers of different genders.
Geographic segmentation is based on where your audience is physically located. This is typically most helpful for B2C businesses for whom local climate and custom have a big impact on demand. A retail shop, for example, might advertise swimwear to people in Florida, but, at the same time of year, they may build a different campaign that advertises winter clothes to users in Canada. Geographic segmentation can also be helpful for local services that deliver in specific regions, such as a food delivery service, or it can be helpful to email/SMS marketers who want to send emails at a specific time across multiple time zones.
In value-based segmentation, you look at the overall financial value of your audience segments to see which one makes the best use of your marketing budget. If you find one group is consistently more valuable than another, for example, you can focus your efforts on the more profitable leads. Though it may seem a bit cold in nature, value-based segmentation is a necessary process for businesses looking to maximize their marketing ROI. With data collected around the lifetime value of customers, you can see which subgroups of your target audience cost the least to attract, maintain, and bring back for future sales.
Needs-based segmentation is exactly what it sounds like: dividing your audience for personalized messaging based on their current emotional, physical, and financial needs.
For example, let’s say you run an online store that sells furniture. After doing some research, you find that a low-cost desk fills a need for both college students and professionals working from home. But you also have a children’s coloring desk that fills a need for stay-at-home parents by giving their child a productive, screen-free activity (and giving the parent a much needed coffee break). This kind of information would guide your next marketing strategy, as you would target people based on the needs your products fulfill: college students and young professionals would be targeted for the low-cost desk, and parents would be targeted for the kid’s coloring table.
This is a simplified example, and, in practice, needs-based segmentation often requires large amounts of qualitative and quantitative data to identify the many needs of your audience. That said, it can be a powerful tool once you understand the specific pain points of each of your user segments.
Psychographic segmentation relies on dividing your audience based on how people “think” about certain values or products. This kind of segmentation requires data on things like:
Imagine, for example, that you own a company selling athletic gear. You have many options for shoes, so you research your audience’s lifestyle and hobbies. You find that some people in your audience are into marathon running, others are into basketball, and some enjoy the latest pair of expensive Nikes as a status symbol. With this information, you can target the right pair of shoes to the right individual. And every few months, you can more appropriately follow-up with new recommendations (a marathon runner, for example, might need new shoes every two months, whereas a college basketball player only needs one pair per season).
Psychographic segmentation is particularly difficult to pull off without the help of specialized software, though it’s not impossible. You can learn a lot about how your audience feels by monitoring their online activity (in forums, social media platforms, purchase behavior, reading reviews, etc.) or conducting your own research (surveys, focus groups, reviewing call transcripts, etc.). In the past, companies were able to rely on third-party data to increase the accuracy of their paid advertisements using psychographic data. However, as third-party data is slowly being phased out by Google, businesses are taking their first-party data collection and organization more seriously.
Technographic customer segmentation
Technographic segmentation has become more popular in recent years, and it refers to dividing your audience based on the technology they use. For example, imagine there’s a SaaS company that wants to send personalized emails to new users. Some of these users work with the customer management platform HubSpot while another segment uses Salesforce.
When contacting users with an enticing offer, technographic segmentation would let you personalize the message for each of these subgroups. For the first group, you might send an SMS that says, “Save 15% on X product – the perfect addition to your HubSpot marketing strategy.” And for the second group, you’d write the same message but reference Salesforce. The added touch of personalizing your message to include the software the recipient already uses can play a major role in improving the ROI of your marketing campaign.
How to choose the right customer segmentation model(s)
Before you start creating a customer segmentation game plan, you need to define what types of customer data have the biggest impact on conversions. This will help you fill in the gaps between the data you already have and the data you need to build a stronger segmentation strategy. Fortunately, this can be done in two steps.
1) Define the types of customer data that can support your growth
This step is going to be different for each business. Identify your marketing goals and determine which customer segmentation model would be best for reaching those goals based on the campaign you’re running.
For example, you’d likely choose a different customer segmentation model if you were trying to get more people to attend a webinar than if you were trying to book a 1:1 sales call. For the webinar, you might target people with a specific job title (demographic segmentation). But for the 1:1 call, perhaps you only want to message people who have already attended the webinar, downloaded an ebook, and/or clicked on a particular advertisement (behavioral segmentation).
Define the concrete marketing goal you have for a specific campaign to better understand the data you’ll need to reach a specific segment of your audience.
2) Identify the right tools to collect the data you need
You already have access to some customer data, but you might not always be able to use it for segmentation. With a tool like Google Analytics, you can collect a wide array of demographic data on your customers and learn how people are engaging with your website. For example, you might find that 67% of your audience visits your site from a mobile device. This is valuable information, but it won’t identify exactly which users to send your message to.
The best option is to use software that automatically translates customer data into actionable strategies. Twilio Engage, for instance, is the first growth platform built on top of a customer data platform (CDP). This software collects your first-party customer data and creates user profiles. You can then build custom audience segment models for a completely personalized, end-to-end customer journey.
Personalized experiences for a more engaged audience
The impact customer segmentation has on your overall marketing efforts can’t be overstated. (Check out how Grofers grew exponentially in just two years by focusing on their customer segmentation.)
When you choose the right customer segmentation model, you’re able to personalize your messaging at a more granular level. As a result, you can expect more engagement from your campaigns, an increase in leads, and a higher ROI from your marketing campaigns.
While customer segmentation can be done manually (to a limited extent), many businesses are investing in specialized software that lets you collect, organize, and implement customer data. Interested in seeing first-hand how one tool can drastically improve your segmentation efforts? Check out Twilio Engage and learn how simple it can be to segment your audience for more personalized messaging.
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