16
min read

Email Segmentation: How to Personalize Your Campaigns for More Conversions

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Thanks to machine learning and other predictive algorithms, 80% of consumers now expect personalized experiences in their interactions with companies—including email. 

Segmentation can help with this. In email marketing, segmentation is the practice of splitting your email list into different groups so that you can provide contacts with more personalized content.

With more targeted campaigns, your emails will see better performance—higher open rates and click-throughs, plus lower spam reports and unsubscribe rates. This, in turn, will lead to:

  1. Increased email deliverability. (More of your emails land in inboxes over spam folders.)
  2. Increased conversions.

In fact, marketers generate 760% more email revenue from segmented campaigns. 760%. That’s not a typo.

Most marketers understand the importance of segmentation—but few actually execute it correctly. 

Why?

There are many different ways to segment your list—to the point it’s overwhelming. Decision fatigue kicks in and some marketers don't take the time to actually build and execute a segmentation strategy. Even the marketers who do set it up make critical mistakes that weigh down ROI.

Most companies—from small businesses to venture-backed startups—simply get segmentation wrong.

In this post, we'll simplify email segmentation so you know which strategies actually matter. You'll have everything you need to use segmentation the right way:

What is email segmentation? How does it work?

Segmentation involves dividing your email list into different groups using data collected from your subscribers. 

Since each of your subscribers has different needs and motivations, it doesn’t make sense to blast them all with the same emails. Instead, with email segmentation, you design messages to appeal to different buyer personas.

A quick example: 

Say you own an ecommerce store that specializes in pet supplies. A subscriber that clicks on an email link to a resource titled “The Best Dog Beds of 2022” would get added to a “dog owners” segment—then they’d receive emails specific to dog owners, like a coupon for dog food. 

Meanwhile, someone who clicks on a cat-related link would get added to a “cat owners” segment and receive only cat-related content.

You can automate all of your segmentation by setting up groups with simple if/then statements in an email service provider (ESP) like Mailchimp, Customer.io, or Klaviyo. All you need is user data connected to a specific email address. Then your email workflows—the series of emails designed for a specific audience segment—send on your behalf.

You automatically deliver the right message to the right person at the right time.

One important note: Good segmentation requires personalizing emails in a respectful, not creepy, way. As more people become hyper-aware of how companies use their private data, a message that’s too personalized can scare them away from becoming loyal customers.

A quick example of how NOT to do it…

Target used customer data to identify pregnant women, and then sent them coupons for baby products. Customers weren’t just uncomfortable—they were creeped out.

The bottom line: Segmentation is a great strategy for converting more users, but you need to do it tactfully.

Create an effective segmentation system

You can create an effective email marketing segmentation system in five simple steps:

  1. Set goals.
  2. Identify relevant data points.
  3. Automate data capture.
  4. Create your segments in your ESP.
  5. Write emails for each segment.

More on each step below.

1. Set goals

Your email strategy will probably have multiple campaigns, each with different objectives: onboard new users, collect feedback, promote new products, and so on. Pick one email campaign to start with. Then identify its goal.

At its core, segmentation is all about converting users through more relevant email content—so your goal-setting should focus on defining the exact conversion you want.

Is your email campaign trying to:

  • Increase sales of a specific product?
  • Drive more app downloads?
  • Get users to upgrade to another tier of service?
  • Register more users for an event?

It’s important to clearly define this goal because it determines what data points you actually need.

Here are examples of goals for two different kinds of companies:

  • A B2C lifestyle brand like Under Armour wants to launch an email campaign to sell more women’s products.
  • A SaaS company with a freemium model like Trello wants to get free users to upgrade to a paid subscription.

2. Identify relevant data points

Once you’ve laid out your campaign’s goal, the next step is to identify the relevant data point(s) needed to create your segments. 

You can use this data to split your list in four major ways:

Definition Example Criteria Best for
Demographic Segmenting by traits describing users’ socioeconomic profiles Age, gender, geographic location, marital status, income, education level Companies that sell a variety of products, B2C companies
Psychographic Segmenting using qualitative info about a user’s thoughts and beliefs Lifestyle, interests, intent Companies that sell a variety of products, products that serve multiple niches, products with different use cases
Relationship Segmenting based on your relationship with contacts Funnel stage, type of customer, length of relationship Companies that  serve different tiers/personas, products with long sales cycles, repeat purchase products
Behavioral Segmenting using metrics that show interaction between subscribers and your business Email engagement, website behavior, purchase history, product activity Complicated products, companies with long sales cycles, products that naturally collect data

We’ve defined these four categories to provide a simple framework for understanding segmentation—but the reality is that you can use multiple datapoints to combine strategies. 

For instance, based on their goals, here are the data points and strategies the example companies mentioned in step 1 might use:

  • B2C brands like Under Armour could use gender and purchase history to target female subscribers (demographic and behavioral segmentation). For female subscribers who’ve bought something in the past, it’ll send personalized product recommendations. 
  • Trello and other SaaS companies focused on getting free users to upgrade might look at type of customer and product activity (relationship and behavioral segmentation). It could identify and target free users who’ve used its product five days in a row.

There are plenty more segmentation possibilities for each example, but the key is relevant data. Choose meaningful data points that align with your campaign goals—they’ll determine your segmentation strategy, plus how you should tailor your content.

3. Automate data capture

Good data is a non-negotiable in your email segmentation strategy—after all, it determines how you split your list and personalize content.

Almost all data collection can be done within your ESP. If you’re just starting out with segmentation, keep it simple and set everything up inside Mailchimp, Customer.io, Klayvio, or your ESP of choice.

For more complicated data points, you might need an all-in-one marketing platform like Hubspot or a customer data platform (CDP) like Segment. These can collect more nuanced info about subscribers.

There are two types of data that give insights about your audience:

  • Explicit data is information your subscribers give you directly, like their name, date of birth, and address. This type of data is useful for demographic and relationship-based segmentation; you can collect it through form submissions, audience surveys, product ratings, and user profiles.
  • Implicit data is information that subscribers unintentionally give through their behavior or your analytics tools, like the pages they visit or resources they download. It can also come from your product—for example, Netflix and Spotify collect implicit data about the movies and music their users like. Implicit data is useful for psychographic, behavioral, and relationship-based segmentation. 

Since people don’t like filling out long forms, ask for only what’s critical in your signup forms. Then collect additional explicit and implicit data in other ways (covered later in this article).

For our example companies, here’s how that data collection process might look: 

  • For subscribers who check out and create a user profile, Under Armour could include fields asking for birthday, gender, and even clothing sizes (explicit data). It could look at which product pages users visit to find out what they’re interested in (implicit data).
  • In its signup form, Trello could include fields like “How many people will you be working with?” or “Please tell us what industry you work in” (explicit data). It might look at product usage or newsletter engagement to find out what users find most valuable.

In general, segmenting with implicit data is harder than with explicit data. 

Why? Implicit data requires you to make assumptions about your subscribers, so you risk getting something wrong about them. For example, your segmenting might put someone who bought a luxury rug in a group of customers with extravagant furniture tastes. So you send email recommendations of products at the same price point or with the same look. But the reality is, they were buying that rug as a gift for their boss—they don’t like that style for themself! 

Again, be mindful about the data points you segment by. 

4. Create your segments in your ESP

You’ll use the data you collected earlier to create different segments in your ESP. 

The exact setup depends on which provider you use, but most ESPs use conditional logic like if/then statements and and/or functions. For instance, here’s how a segment for subscribers who joined your email list on Twitter would look like in Customer.io:

Customer.io screenshot of a segment of Twitter subscribers
Using Customer.io, you could create a segment for people who subscribed from Twitter.

Most ESPs even allow you to combine segmentation criteria, so you can narrow in on a very specific group—like customers who’ve spent $200 and have a high contact rating.

Screenshot of creating a segment in Mailchimp
(Image credit: Mailchimp)

Once finished, you’ll have your segments—all you need now are your personalized emails and workflows. Then marketing automation will take care of the rest.

5. Write emails for each segment

This is where you work on writing the best emails for each of your unique segments. You can personalize them through their:

  • Subject lines
  • Body copy
  • CTAs
  • Send time

Create them all in advance. Then, in your ESP, set up separate workflows for each segment. 

Remember that whenever you segment with implicit data, you’re usually making some assumption about your audience. To avoid making incorrect ones, think carefully and logically as you write your emails.

Avoid making big leaps of judgment about your subscribers based on certain traits. For instance, don’t assume that all subscribers beyond a certain age are married. Or that all subscribers who are married are heterosexual. These assumptions don’t only hijack your marketing efforts—they can come off as downright offensive.

Email list segmentation strategies

Earlier, we mentioned four strategies you can use to split your email list: demographic, psychographic, relationship-based, and behavioral segmentation. 

Remember that depending on the data point(s) you choose, your segmentation might be a combination of these strategies. Some data points can even be used for more than one category. 

For example, you could use purchase history to get an idea of people’s product interests (psychographic segmentation) or to classify them based on their average spend (behavioral segmentation). 

The point here: you can use your data to segment your list in many creative ways

Below, we’ll dive into these different strategies in more detail, including specific segmentation ideas and real-life examples.

Demographic

Demographic segmentation is the simplest and most straightforward way of splitting your email list. That’s because the info needed is usually more readily available and easier to get. For example, many ecommerce stores often ask customers to create a user profile and fill out info like birthday and gender (explicit data).

Demographic data also tends to be more stable or predictable. While someone’s style preferences may change over time, their date of birth won’t.

Because of this, demographic segmentation tends to work best for B2C companies and companies that sell a variety of products, like:

  • Retailers that sell women’s and men’s clothing
  • Banks and lenders that offer loan preapprovals 
  • Local service businesses like tutors and makeup artists

Here’s an example of demographic segmentation using location.

In an email announcement about adding more grocery stores to its app, DoorDash used different subject lines based on subscribers’ location. The reasoning: different grocery chains are popular around the U.S. So while Texas residents received a message with a subject line about the Texas-based supermarket Randalls, Florida residents got one about their local Winn-Dixie.

A screenshot of an email announcement from DoorDash
Texas residents received a message with a subject line about the Texas-based supermarket Randalls.

For B2B companies, there’s a concept similar to demographic segmentation but at a company level: firmographic segmentation. Using firmographic segmentation, you’d split your email list based on company-defining criteria like industry, number of employees, location, and revenue.

Again, segmenting by demographic (or firmographic) data is the simplest way to split your list. This also makes it the least effective since you’re classifying users based on basic criteria that doesn’t really explain their needs or motivations.

Whenever possible, we recommend layering demographic data with another type for stronger segmentation—keep reading for ideas of how to do this.

Psychographic

If demographic segmentation revolves around the “who” behind your subscribers, then psychographic segementation is all about their “why.” It dives deeper since you split users based on their thoughts and feelings.

Compared to demographic data, psychographic traits are more fluid—after all, someone’s beliefs may change over time. You can capture this data through both explicit (a survey or quiz asking for someone’s interests) and implicit methods (the category of products someone buys most often). 

Although every company can use it, psychographic segmentation works especially well for:

  • Companies that sell a variety of products
  • Products that serve multiple industries or niches
  • Products with different use cases

Strategies here include segmenting by lifestyle, interests, and subscriber intent.

Lifestyle

A single product can be used in dozens of ways, which is why some companies segment based on lifestyle. 

For instance, runners, bikers, and swimmers all use Fitbit trackers to measure their health and physical performance. So do casual recreationalists and people who don’t play any sports. With lifestyle segmentation, Fitbit might tailor emails for each group.

But how do you collect lifestyle data? Here’s an email example from the sports equipment company Brooks.  

Screenshot of an email from Brooks about subscribers' running preferences
Brooks sends an email asking new subscribers about their running habits.
Screenshot of an email from Brooks about subscribers' running preferences
Users can click on the option that best describes them.

Brooks’ email does double duty by collecting demographic information (gender) as well as subscribers’ running habits. It’s useful explicit data for segmenting—so if a subscriber clicks on the male trail runner photo, they’ll enter an email workflow that caters to this persona.

Interests

Interest-based segmentation separates customers with different preferences—but you don’t need to offer a lot of products to use this strategy. 

For instance, writer Lawrence Yeo uses a similar technique to Brooks in his newsletter but with only one clickable option. It’s an easy way to see who from his existing subscribers might be interested in something specific—he can then create an email workflow just for this group. 

A screenshot from Lawrence Yeo's newsletter
To gauge interest in a particular topic, Lawrence Yeo's newsletter asks subscribers to click on a link.

Depending on your product, you might even naturally collect data about your subscribers’ interests. For example, Netflix use viewing history to make announcements about new content on its platform—so people who watch a lot of reality TV will receive an email about similar shows. The same goes for every other genre.

A screenshot of a Netflix email with personalized recommendations
Netflix can segment its customers based on their viewing history and use the same email template for each group.

Subscriber intent

Many companies send new subscribers the same welcome email and add them to one big workflow no matter how they joined their email list.

But how people end up on your email list often reveals why they subscribed and what they expect: some sign up for a newsletter; others share their contact info to get a lead magnet; and customers opt in as they check out. 

Segmenting by subscriber intent acknowledges these differences. Here are a few ideas for personalizing your content based on how subscribers join your email list:

  • When new subscribers sign up for your newsletter, include a sample of the newsletter in your welcome flow. It’ll help get them acquainted with your newsletter while it's fresh in their minds. This way, they'll be more likely to notice and open it when you send your next issue.
  • When people sign up through your blog content, tailor your welcome flow to send blog posts relevant to the one they signed up on. So if they signed up while reading a keto blog post, send them more keto content.
  • If people signed up through a specific event, include a calendar of related events in your welcome email. Chances are these subscribers are interested in checking out similar events.

Relationship

Segmenting by relationship involves dividing your email list into groups based on your relationships—new customers, premium subscribers, churned customers, and so on. The idea here: You don’t want to overwhelm new or unfamiliar prospects. And along the same lines, you want to build on existing customer relationships.

This type of segmentation works especially well for:

  • Companies that serve different tiers or buyer personas, like SaaS products
  • Products with long sales cycles, like B2B software
  • Products that are renewed or conducive to repeat purchases

To leverage this type of segmentation, you can split your email list based on type of customer, length of relationship, or sales funnel stage.

Type of customer

For companies that offer multiple pricing plans, it makes sense to segment by type of customer. After all, if some services or benefits only apply to your premium tier of customers, it doesn’t make sense to email everyone about them. 

The same strategy applies if you serve distinct buyer personas. Consider how Uber’s user base includes both drivers and riders. Or how both vacationers and corporate travelers use Expedia to book flights and hotels. Your email content should be tailored for each persona.

One real-life example: Grubhub sends informational content about the benefits of client lunches and meal perks to its corporate customers—these come from its “corpmarketing” email address. But to individual consumers, Grubhub sends coupons and notifications about new restaurants on its app.

A side-by-side comparison of two emails from Grubhub
Grubhub sends very different emails to businesses and individual consumers because each group has different priorities.

It’s a good example of how different audiences get value from your company. To its business clients, Grubhub wants to emphasize how its service can help close deals and retain employees—something an individual consumer has no interest in. Instead, consumers are probably more interested in getting their favorite foods quickly and affordably.  

Besides pricing plans and customer personas, you can also segment your email list into user categories like:

  • Free trial subscribers
  • Non-converters
  • Churned customers

Length of relationship

On a simpler note, you can segment subscribers based on the amount of time they’ve spent on your email list or have been a paying customer. 

Here’s an example of the different emails you could send:

  • 0 Days (first-time customers): Send educational resources to help explain your product. 
  • Less than 90 days: Follow up to ask for feedback or resolve any issues. 
  • More than 90 days: Send an email asking for a testimonial or social media share. 

The cashback app GetUpside takes this approach. It sends instructions to new users early on, plus tips on how to get more from its app; it doesn’t ask for reviews until much later.

A side-by-side comparison of two emails from GetUpside
GetUpside doesn't ask users for a rating or review until much later in its relationship with subscribers.

Funnel stage

Not everyone on your email list is a paying customer. Some might be new subscribers because they downloaded a lead magnet or signed up for a webinar. Others might have your product in their cart right now.

In other words, your subscribers are all probably at different stages of the sales funnel. To segment them based on stage then, look at implicit metrics like:

  • Amount of time on your email list
  • Lead magnet downloads
  • Event signups
  • Number of page views
  • Amount of time since last purchase
  • Ad clicks
  • Email stats like open rate and CTR

Combining criteria for segmentation works well here, since it’s hard to figure out someone’s stage with just one piece of data. Some example workflow triggers might look like:

  • Downloaded an ebook AND viewed five blog posts → Send an email about a related webinar
  • Attended webinar AND viewed FAQ page → Send a case study
  • Requested a demo AND viewed pricing page → Add to sales workflow

This is one of the harder segmentation strategies to implement because it really depends on having a well-developed funnel. Companies that invest in content marketing—think newsletters, webinars, and other gated content—have a lot more info than companies that don’t. Stick to segmenting by type of customer or length of relationship if you don’t have much content to work with.

Behavioral 

Finally, behavioral segmentation revolves around how contacts have interacted with your business, like on your website or with your past emails. 

It relies mostly on implicit data to understand how engaged subscribers are. Because of this, it feels like a combination of psychographic and relationship-based segmentation. 

While any company can benefit from behavioral segmentation, it’s especially useful for:

  • Complicated products that need more explanation, like new cybersecurity technology
  • Companies with long sales cycles, like Salesforce
  • Companies with products that collect data, like Spotify and Netflix—these have a natural advantage in segmenting by behavior.

As long as it can be recorded, any touchpoint between your business and a consumer can be used for behavioral segmentation. That includes what channel your subscribers signed up on, the type of device they use, and lots more behaviors. 

However, in our experience, email engagement, website behavior, purchase history, and product activity are the most effective behaviors to segment by. These give a lot more clues about someone’s probability to buy than other activities that could be influenced externally. For instance, even if someone became a subscriber through Twitter, it doesn’t mean they’re a mega Twitter user—someone could’ve simply shared your tweet with them.

Email engagement

Some subscribers are more engaged than others—these are your “warm” subscribers who show more interest in your content through email metrics like open rate and CTR.

Why is it worth segmenting subscribers based on this behavior? 

Higher email engagement can signal higher purchase intent—people more likely to convert if you send special offers and coupons. 

You can also use this segmentation strategy for customer research. For instance, by only asking your most engaged subscribers to take a survey, you can get a better understanding of who’s more likely to be interested in your product.

Website behavior

How people behave on your site—like what landing pages they look at and the lead magnets they download—can reveal what they’re looking for.

Take cart abandonment for example. Visitors often add an item to their shopping cart and then bounce without purchasing. This behavior is perfect for triggering an abandoned cart email campaign, like the ecommerce brand Nomad does below.

Abandoned cart email from Nomad
Nomad follows up with users who left its site without purchasing by sending an abandoned cart email.

Similarly, anyone who’s interacted with your site’s live chatbot could be entered into a specific email workflow based on their responses.

Purchase history

For paying customers, consider segmenting based on purchase history. You can categorize them using useful metrics like:

  • Time since last purchase
  • Average order value
  • Purchase frequency

These data points are especially useful for curating more targeted product recommendations and sending relevant cross-sells and upgrades. 

You can even use purchase history to ask customers if they’d like to re-purchase something, like Reebok does here.

A Reebok email asking customers if they'd like to buy something again
Reebok uses purchase history to send targeted emails asking if customers would like to re-purchase something.

Product activity

As we mentioned, companies with products that collect data have a natural advantage in using behavioral segmentation. One example: Spotify collects data on the amount of time users spend listening to music and podcasts. 

Using this data, you can segment your email list into different levels of activity, like non-users, light users, moderate users, and heavy users. You can then hit non-users with messages emphasizing your biggest value props, light users with guides explaining how to get more from your product, and so on. 

Or, you could use product activity to identify and target churned customers with a reengagement workflow. For example, Uber emails inactive customers with a message reminding them of its benefits. 

Screenshot of a re-engagement email from Uber
Uber's initial email to inactive users is a reminder of its value props.

If customers still haven’t reengaged, Uber sends a discount later on.

Screenshot of an email coupon from Uber
For inactive customers who still haven't reengaged, Uber offers a 10% discount on their next five rides.

Cheat sheet

Though once thought of as an advanced email marketing tactic, email segmentation is now the norm. 

By segmenting your email list, you can deliver more personalized content to your subscribers. This creates not only a better user experience, but can also drive more conversions in the long run.

To recap, there are four main types of segmentation, although some data points can be used for more than one. You can even combine segmentation criteria to hone in on narrower audiences. Here’s a quick recap of these strategies and the data points that can be used for each:

  • Demographic: age, gender, location, income, marital status, education level. Best for companies that sell a variety of products and B2C companies.
  • Psychographic: lifestyle, interests, subscriber intent. Best for companies that sell a variety of products, products that serve multiple niches, and products with different use case.
  • Relationship: type of customer, length of relationship, funnel stage. Best for companies that serve different tiers/personas, products with long sales cycles, and repeat purchase products.
  • Behavioral: email engagement, website behavior, purchase history, product activity. Best for complicated products, companies with long sales cycles, and products that naturally collect data.
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Content marketer and writer. Also illustrator, dog lover, and pun enthusiast.

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