When done correctly, customer segmentation can:
- Increase your conversions
- Boost overall profitability
- Expand brand awareness and capture a wider audience
In this guide, you’ll learn how to create customer personas, collect data and insight into your audience, and use it to optimize your marketing and forecasting.
Chapter 1: What is Customer Segmentation?
Customer segmentation is a method of dividing buyers and consumers into different groups determined by specific characteristics.
These groups are built of “psychographic,” “demographic,” and “behavioral” variables.
Examples of consumer variables can include age, income, interests, and previous engagement/purchasing behavior with your brand.
From a B2B perspective, these variables might also include the number of employees, industry, location, and the kinds of products and services the organization uses.
Why is customer segmentation important?
Brands who are serious about customer segmentation all understand one thing: every customer is different.
Have you ever ignored an email or social ad because the content didn’t speak to you as an individual? The answer is likely “all the time.”
How about the marketing that grabbed your attention? The ads which stopped you in your tracks, forcing you to read it all the way and take action.
It’s likely this was because that brand knew what your pains and desires are. They understood you as an individual.
This is the power of customer segmentation.
Customer segmentation helps you direct the way you communicate with your email subscribers, the messaging on your website, and your entire content strategy. There are two core elements to effective segmentation:
- Personas: Documentation that represents different customer groups using demographic, psychographic, and behavioral values. You’ll learn how to build personas in Chapter 3.
- Lifecycle Stages: This defines where in the decision-making process a customer is. The message you serve to a brand-new website visitor is very different to what you would say to a customer who has been with you for several years.
By using technology, data, and a strong understanding of your customers, brands can allocate their marketing resources to target, attract, and sell to their customers effectively.
What customer segmentation means for your business
Great segmentation = better personalization. Personalizing your marketing message towards specific groups encourages them to buy.
Because you’re serving them with marketing and offers that cater to their specific needs.
Good customer segmentation also assists with customer service, contributing to retention and brand loyalty. As you collect more data on specific customers, the more personalized your marketing message can be for each of them.
Segmentation can also help you stay a step ahead of the competition. Part of the customer segmentation process includes continual conversations with your customers.
These insights can involve uncovering new product ideas, allowing you to capture a greater share of the addressable market.
And the insights don’t just stop at marketing. Both customer service and finance teams can benefit from customer segments. This data can provide profit potential and value-based forecasting, allowing you to adjust your budget accordingly.
Chapter 2: Customer Segmentation Groups
So, we’ve covered what segmentation is and how it affects your business.
It’s time to get into the meat of the topic. The question is, where do you start?
First, you must understand the components that make up good customer segmentation. These segmentation groups will help you collect the right data, insight, and information on your customers.
In Chapter 3, you’ll learn how to use this insight to build out customer personas: a method of documenting your different customer segments.
Segmentation Group 1: Demographics
Demographic segmentation utilizes easy-to-acquire information to get a broad, yet specific, understanding of your audience. You can collect this information with a variety of tools, such as using census data and analytics software.
While it’s a stepping stone to more granular data, the information is very broad. Here are five of the most common variables that make up demographic segmentation:
- Age: A quantifiable variable segmented into age groups (babies, adults, etc.) and generations (baby boomers, millennials, etc.)
- Gender: Typically categorized as male or female
- Education/Occupation: Certain products and services can cater for those with a certain education (high school, college, etc.) and occupation (sales executives, doctors, etc.)
- Income: The average annual income of your target market.
- Family status: Single, newly married, and the number of children falls under this variable.
Geographical segmentation can also be considered a demographic variable. For many industries, the country or territory of their audience is a key factor for the addressable market.
It’s also important for brands who serve customer internationally, as cultural differences will define the marketing message they create.
Segmentation Group 2: Psychographic Segmentation
Psychographic segmentation covers the interests and motivations of your audience.
Here, you’ll get a better understanding of your audience’s beliefs, interests, and challenges, in business, life, and everything in-between.
Psychographic segmentation helps you understand how your customers think, as well as their favorite products and brands.
Here are the five variables that make up psychographic segmentation:
- Interests, hobbies, opinions: Impacts purchasing behavior. These range from political beliefs, sports, art, critical issues and activities (e.g., gym, tennis, etc.).
- Lifestyle: Values include the food they buy and the clothing they wear. Understanding lifecycle variables can help you uncover which lifecycle stage they currently sit in.
- Values: These are attitudes formed by culture and upbringing.
- Social status: Defined as buying power, influence by income or region, and spending habits.
- Personality traits: Fueled by lifestyle and social status. This is where “brand personality” comes from.
While this data can come from sources like Google Analytics, you should look towards more sophisticated methods. We’ll cover these soon.
Segmentation Group 3: Behavioral Segmentation
You must also segment customers by the way they interact with your business and the products or services they buy. Known as behavioral segmentation, you can react to customer interactions in an automated manner.
This form of segmentation sits in the sweet spot between customer behavior and consumer needs:
Here are five variables that make up behavioral segmentation:
- Occasion: Consumer purchases based on a specific need or occasion. Some are universal while others happen at specific points in a customer’s lifecycle (e.g., wedding)
- Usage: Grouping customers by how often your customers use your products or services (light, mid-level, and heavy use)
- Loyalty: Ties occasion and usage together. While occasion and usage indicate the need for what you offer, loyalty is the affinity for your brand over others.
- Benefits sought: Different customer segments will yield different benefits from your offering. Some may buy Red Bull for the energy boost, while others associate themselves with the lifestyle they stand for.
- Customer activity: The variables above make up granular characteristics of your addressable market. Customer activity relies on the data you own.
There’s much value in measuring customer activity, from the emails they open, the content they view on your website and the products they purchase. This data helps you create better, personalized marketing.
For example, using this data, you can send emails based on triggers such as cart abandonment and pages viewed. You can also send them based on inactivity, or to welcome them to the shopping experience.
Collecting the data
So, you know the variables that make up your customer segments.
The question is: how do you collect the data to inform your personas?
Several tools and approaches can help you collect the right data. To wrap up this chapter, I’ll share four of our favorites here at SpotRight:
1. Google Analytics
When used correctly, Google Analytics can yield a tremendous amount of high-level insight into your audience.
For broad insight, simply head to the Audience menu and select “Demographics,” “Interests,” or “Geo.”
Above, you can see affinity categories and in-market segments of users across a specific data-range. You can then further segment this based on user behavior.
Speaking of which, the pages and content your audience spends the most time on is a great indicator of their interests and needs. For example, by heading to Behavior > Site Content > All Pages, you can order each page by the number of users and avg. time on page:
Using this data, you can tailor your content strategy and marketing message based on the most popular topics/pages.
2. Customer Surveys
Your existing customers are a treasure trove of quantitative insight. You can get a general understanding of your customers using surveys to yield information like the following:
- Where they hang out online
- What topics they’re most interested in
- How they feel about your brand
- Why they buy from you
- Products and services they desire
And much more. When building a survey, make sure to keep the number of questions in mind. More questions bring more insights, but also creates more friction and therefore a lower completion rate.
The best approach is to test with small segments of your audience first. A good rule-of-thumb is to send five multiple-choice questions and one open-ended one. This allows you to collect both qualitative and quantitative insight at scale.
3. Customer interviews
While surveys can provide large amounts of insight, having real conversations will allow you to understand true motivations.
The principle here is simple: schedule interviews with your customers with the clear intention to understand more about their needs, challenges, and desires. The objective is to understand their true motivations.
Prepare three simple questions. Make sure to keep them broad. Dig deep into their responses.
Don’t ask leading questions and be prepared to listen. This means leaving your biases at the door before making the call.
Consumer data is available across all corners of the web. Of course, pooling them together is the real challenge.
While I may be biased, the SpotRight platform is perfect for accessing huge amounts of consumer data on specific customer personas.
For example, let’s say you were leading the marketing for Urban Outfitters and wanted to learn more about the brand’s audience. Using the consumer data within SpotRight, you can uncover the interests, influencers, and other brands your customers have an affinity with:
Use this data to direct your paid media, content marketing, and influencer engagement efforts.
Chapter 3: Building Customer Personas
Now you understand how to collect data on your customers.
It’s time to group them into segments in a practical way.
Enter customer personas.
Also known as marketing personas or buyer personas, customer personas are detailed documentation of each key segment of your market.
They help you serve the right products to the right people and direct your marketing strategy to deliver the most relevant content possible.
In this chapter, you’ll learn how to create your own.
Begin with broad definitions
Most businesses will have several customer personas. The number will depend on the industries and niche markets that you serve. There’s no right or wrong answer to the amount you should create.
Begin by defining your customer personas on a broad level. Let’s go back to our Urban Outfitters example in the previous chapter. We know that they serve both millennial men and women, giving us two very broad personas:
- Millennial women
- Millennial men
Self-explanatory, right? Now it’s time to break them down further. Looking at the data, women make up the largest part of their audience. Let’s break this segment down further.
From here, you can use characteristics, interests, or even age range to break down each persona. For example, the data shows their audience is heavily made up of people aged 26 to 30:
Using data like this, we can create personas such as:
- Millennial women in their late 20’s
- Millennial women in LA
- Fashion aware millennial women
Now you have your broad personas. It’s time to dig deeper.
Fleshing out your personas
Now it’s time to put data from the previous chapter to good use.
First, there’s quant-based information. This comes from the data you can collect at scale – from your analytics to consumer and social data.
Here’s a list of attributes you should collect:
- Location: where do most of your customers live?
- Age: what is the average age range of your customers?
- Gender: what is the typical gender of this persona?
- Education: what level of education did they graduate?
- Job title: Which industries do they work in, and which job titles go with them? (Useful in B2B organizations)
- Income: what is the average income range?
- Interests: what are their hobbies, values, and belief systems?
- Relationship status: are they married with children or mostly single?
- Language: which languages do they speak? What’s their mother tongue?
Then there’s qualitative insight. Gather this using surveys and regular conversations with your customers or analytics tools like SpotRight.
They can be used to give more granular insight on extra and existing attributes, such as:
- Interests: find out what they’re truly passionate about.
- Favorite brands: uncover which brands they shop with most and why.
- Favorite websites: blogs, news outlets, and online communities. Find out where they hang out online.
- Influencers: which online thought leaders and celebrities do they follow?
- Why they buy: what is the true motivation for buying your products or services?
- Why they don’t buy: what concerns them about your product or the way you do business?
You may find some of these are more relevant than others. Indeed, you may also wish to include information that you feel is important to your audience and your brand.
The objective is to gather a true understanding of your audience. This means your personas can evolve on an ongoing basis. In other words, don’t be afraid to update them regularly.
Creating your personas
With all the data available, it’s time to bring everything together.
Going back to the data we have for Urban Outfitters’ audience, here’s an example persona:
- Location: Los Angeles, New York, Philadelphia
- Gender: Female
- Age: 26 – 30
- Interests: Fashion, Beauty, Reality TV, Wellness
- Education: College
- Job Title: White Collar, Health, Management
- Income: $125K or more
- Family: Single
- Why they buy: Quality products in line with fashion trends
- Why they don’t buy: Concerns around XXX
With this data in hand, we can bring the data alive. Use persona documents to do this. Here’s an example persona for shoe brand Munro (courtesy of Alexa):
Here, the information is presented visually. This helps your teams visualize the kind of person you’re talking to and “humanize” your customers.
Once you have your personas created, you must update them on a monthly or quarterly basis. This is how you stay on the pulse of your market.
Chapter 4: Personalizing Your Marketing Campaigns
It’s time to put those customer segments to good use.
Using the power of personalization, you can send more targeted marketing for higher conversion rates. Indeed, 86% of consumers say that personalization informs whether or not they buy from a brand.
In this chapter, we’ll use email marketing as a vehicle for learning personalization principles. Remember, you can apply personalization to all of your marketing – from your content to the messaging on your homepage.
Why one-off emails are no longer good enough
Historically, email personalization involved using the right fields. For example, “Hi $FNAME” would be sufficient to get the attention of consumers.
But this is no longer the case. Personalization has moved beyond variables. It’s now about sending the right content at the right time. You must demonstrate an understanding of specific segment needs.
Accessibility is no longer the hard part. Deliverability is where the challenge lies. The likelihood of a single email broadcast generating a sale is low. You need multiple touch-points to build trust and generate a customer or sale.
Personalization, when done right, looks like this:
- Sending the right messages to the right customer segments, based on their interests and consumers behavior.
- Dynamic websites that personalize messaging, offers, and calls-to-action for the customer who is visiting.
- Serving messaging and creative across several touch-points that focuses on their needs and stage in the customer lifecycle.
Marketing personalization can be applied to several marketing channels like your social media ads, landing pages, and mobile marketing efforts.
But email marketing is where the low-hanging fruit lies. It’s likely you already have a tremendous amount of insight into your current customers – the emails they open and the products they purchase.
With that in mind, here are five email personalization techniques to apply to your marketing today. You can easily implement these with the insight generated in chapter 2.
1. Leverage time & location
Timing has always been a huge factor in email marketing. Certain times and days of the week have been proven to yield better results than others.
The problem is, your audience is likely distributed all over the world. Even if you’re in the US, you still have different time zones to contend with.
To get more sophisticated with timing, start with A/B testing to find the optimal sending time.
Do you generate a better open rate and CTR at 8:00 AM or at 5:00 PM? It’s important to start this process by uncovering the best sending time for your audience.
Once you uncover this information, use your customer data to segment your audience by location and time zone. This is exactly what BustedTees did to overcome this challenge.
By personalizing the send time for each demographic segment of their audience, they increased revenue from their emails by 8%. Furthermore, they boosted response rates by 17% and overall CTR by 17%.
This experiment took them on a personalization journey, optimizing everything from email design to post-purchase communications.
2. Trigger emails on behavior
Triggered emails are sent based on user’s behavior with your website or brand. They can be fired off from content viewed, products purchased, and even inactivity.
As a result, they’re perfect for customer retention. If you’ve ever received an email from a social media platform like Twitter, you know how well they get your attention.
For example, MeUndies use behavioral emails to send blog subscribers a discount on their first purchase. This helps convert those at the very top of the funnel into real customers:
Check out our guide on behavioral marketing for actionable information and advice on how to implement this tactic.
3. Email to landing page match
Personalization is key, but so is consistency. The design, copy, and overall “feel” of your emails should match the landing pages that you lead your users to.
This provides a unified experience for your customers. Keep messaging and calls-to-action consistent to optimize your conversion rate.
And here’s the landing page it leads you to:
The layout and calls-to-action are almost identical. The layout of the calls-to-action are in the same place, training users to know where to look without cognitive dissonance.
Take advantage of this technique by applying similar experiences throughout all touch-points with your business.
4. Focus on the subject line
The subject lines of your email will decide whether they get opened. Testing personalization in this area is key.
Using split-testing tools (such as the example below by MailChimp), you can personalize subject lines by age, location, interests, as well as other demographic and psychographic variables:
The style and content of your subject lines will vary depending on your industry and the nature of your audience. Test different styles against each other to see which generate the highest open rates.
5. Use content to power personalization
We’ve talked about triggered emails based on user actions… but what about the content they view and the products they buy?
Amazon is the poster boy for this technique. Every part of their emails includes recommendations based on past purchases:
Don’t just use this for product emails. For example, instead of sending blog updates to all subscribers, send them to those who have expressed an interest in that topic. This way, you’re more likely to reduce unsubscribes and boost your CTR.
Of course, this tactic works even better when you offer discounts for those relevant products. It’s an approach that works in any industry and provides an extra layer of personalization that shows you understand your audience.
Chapter 5: Empowering Consumers with Customization
As you know by now, every customer has a unique set of needs. In the words of Jeff Bezos, “If we have 4.5 million customers, we shouldn’t have one store. We should have 4.5 million stores.”
Personalization often goes only as far as marketing messages. But it also has its place in the world of product marketing.
Customization as a marketing strategy can help increase efficiency, optimize resources, and cut down on wasted time and effort.
Here are three practical ways to implement customization into your marketing efforts.
1. Customized live chat
Live chat has been around for years. The challenge is in using it as a cohesive part of your marketing.
Let’s say a user receives an email and clicks through to your landing page. A live chat widget greets them. The message says something like “Hi there, how can we help you today?”
This is not a very personalized approach. Instead, what if it said, “Hi Sam, any questions about product X?” Not only does it continue the conversation from the email, but also addresses the specific product they’re looking at.
To implement this, check out Drift. The technology is a blend of CRM and live chat to send highly-targeted messages to website visitors.
2. Customize your customer data
Of course, to serve the right message to the right customers, you need your CRM data in order. This is powerful in any industry – from ecommerce to sales-led organizations.
According to IDC, only 0.5% of the data held by organizations is ever used. This is an opportunity for both small and enterprise businesses alike can take advantage of.
Let’s break down five ways to utilize existing customer data to discover new sales opportunities:
- Analyze old data: Look at your historical sales data. Which tactics, scripts, and techniques have worked best in the past? What are the most frequently asked questions? Use this data and turn it into content. Segment the data in line with your customer groups and focus on the most promising sales opportunities.
- Optimize your message: As explored earlier, each customer segment has their own set of needs and desires. A/B test different elements of your messaging for each segment. Use the customer insight gathered in chapter 2 to fuel this.
- Customer stories and case studies: Don’t simply tell people how you can help them, show them. Use CRM data to communicate tangible value to potential customers. Use visual elements such as graphs or even photography to illustrate the benefits of your products and services.
- Pricing optimization: Use CRM data to gather price data for each segment. Use this to narrow the ideal price range for each customer group. Use a combination of behavior, demand, and price tolerance to test new price points across products and customer segments.
- Data visualization: It can be hard to communicate raw data, especially at a boardroom level. Use visualization tools like Klipfolio or Geckoboard to share real-time insights in a visual manner. This will make decision making a breeze for teams.
3. Product customization
With globalization at its peak, larger brands are having to pull out all the stops. Even bootstrapped companies can steal attention using the right products and a strong marketing campaign.
Software and design have made this even easier and is seen across all elements of the business – especially product design. Indeed, customers are more empowered than ever to get the exact product they like.
Product customization, from a retail perspective, allow customers to tailor the color, size, functionality, and add-ons to the products they buy. Customization must be a seamless part of the customer experience.
For example, everyone knows that the entire Nike experience – both in-store and online – is a delightful one. The same amount of care and attention to detail is in their product customization process:
In the image above, Nike use product customization to boost online retail sales. They succeeded, capturing PR attention at the same time.
On top of the extra publicity, this level of product customization allows you to charge higher prices and capture a bigger share of the market. Furthermore, the data yielded is invaluable, allowing you to generate trends on customer needs.
Chapter 6: Forecasting Future Demand
In the previous chapter, we talked about how Nike used customization to boost not only sales but also perform market research on future customer needs.
By measuring past consumer behavior, you can better understand how they will purchase in the future (as well as how they will respond to marketing campaigns).
What alienates your customers? What are the mechanisms that create loyal customers? These are the questions customer segmentation can answer.
Determining product demand
What time of the year are products in most demand? And which customer segments buy them?
Determining the demand for your product is key for planning inventory, marketing, and growth initiatives.
Accurate forecasting leads to stronger business process management. Get it wrong, and you’ll suffer a host of supply chain, logistical, and technical issues that may hurt your bottom line and customer satisfaction.
Different products will have varying degrees of demand. In true 80/20 fashion, a certain number of products will generate the highest share of sales volume. As mentioned above, if you have low forecasting accuracy, this can affect several stages of the sales cycle and supply chain process.
So, how do you set yourself up for success? Start by analyzing and assessing products every 6 to 12 months. There are four categories as illustrated in the matrix below:
Let’s break each segment down into characteristics:
- Turtles: Products with low volume and low forecasting error. Do not require much attention, unless there is a promotional push from marketing.
- Jack Rabbits: These have a low volume, but a high forecasting error. Use statistical planning and time your promotional activity.
- Work Horses: High volume and low forecasting error. Can be held in high volume with much reliability.
- Race Horses: Lots of volume with a high chance of forecasting errors. These present a serious risk to the business. They’re incredibly profitable but highly unreliable. Losses may come from lack of stock or a decrease in sales.
Marketing and sales teams must work together to segment and plan each product category. The matrix above provides insight into how each product will perform, and how it contributes to the bottom line.
From here, it’s all about planning promotional activity. Using customer segmentation, you’ll be able to market to the right groups with accurate timing and targeting.
Four Ways to Forecast with Segmentation Principles
The method above will help you use available data to forecast product demand properly.
But what about the data and insight on your customers? There’s no point in grouping customers if it won’t contribute to long-term success.
The following techniques will take the principles covered in this guide and apply to them in a forecasting context. With them, you can amend your segmentation strategy to understand the long-term demand of each customer group.
1. Test your marketing
Experiment with different marketing approaches on a small scale to measure consumer response. Sell low amounts of product (or limit access to your app/software) to assess its demand.
Execute this approach across several segments. You must consider geographical location, customer lifecycle, and psychographic variables.
After the test period is over, see how conversions and product movement performed across each segment. This will provide a strong indicator of success when rolling out a full-blown go-to-market strategy.
2. Use leading indicators
Leading indicators use a mixture of business and economic elements to predict demand.
For example, certain regulations might become lax, meaning good news for margins and supply chain resources. However, those same regulations may affect the demand for that product across certain customer segments.
These elements can be effective for predicting long-term success where certain market conditions are in flux. However, you need historical sales data to make use of this approach, as it requires the analysis of patterns of purchasing behavior.
3. Use intention analysis
When conducting surveys and customer interviews, use this opportunity to understand the purchase intention and lifecycle of your customer segments.
The lifecycle stage, demographic, and psychographic variables for each customer will determine product demand. Many leading companies use data to determine when an existing customer might change their purchasing behavior.
Not everyone has a lot of transactional data. This is where surveys and interviews come in. Ask your customers how often they buy different products, the price at which they’re willing to consider buying and use this information to challenge your own biases.
4. Previous sales data
If you have at least 12 to 18 months’ worth of sales records, use this data to forecast demand across each segment. Take factors such as time series and economic analysis to capture an accurate picture of future demand.
Using this data, you can boost sales by appealing to a broader audience. Every quarter you can refer to your sales data to create or pivot your promotional strategy.
Bonus Chapter: Customer Segmentation Success Stories
In the previous chapter, we got technical by exploring how to use economic and business data to predict demand.
However, this is just one benefit that proper customer segmentation can bring. No matter how advanced your approach, it’s important to understand each group and customer persona – what motivates them and the pains they’re looking to alleviate.
To wrap this guide up, let’s look at some more examples of customer segmentation in action, and the results they bring. Take the inspiration here and apply the lessons to your own business.
Like all things Dell does, they took a slightly different approach to customer segmentation. While it started as a sales practice, it didn’t take long until they expanded segments as standalone business functions.
They expanded each segment into units such as finance, IT, manufacturing, and sales. This was because each customer had a unique set of needs, which informed product and go-to-market strategy.
And they don’t just stop at the characteristics of the customer. The depth of analysis goes as far as how they use their products and services. They took behavioral segmentation to a whole new level.
Indeed, Michael Dell puts it best himself:
“Whether it’s anticipating their technology needs or supporting them with fast, reliable delivery and on-site service, we’ve been able to create a feeling of personalization – of a relationship – that comes with buying a PC from Dell.”
eBay uses customer segmentation to drive some of their biggest strategic decisions. The research informs everything from the products they create to the services they offer their buyers and sellers.
As Meg Sloan, former Director of Market Research, says:
“Segmentation, in combination with our own internal data, allows us to understand and think about what we are for whom, how we are going to move the business forward, and what we choose to do in terms of changes to the site or the business model in general.”
Because of this, eBay appears to understand their customers better than most dot-com businesses of their size.
The German car manufacturer uses customer segmentation like most other business. It informs their paid media, content, and digital strategy across the board.
However, what’s most impressive is that they managed to reduce the average age of customers from 57 to 46, tapping into a whole new demographic segment.
They did this using a variety of approaches:
- They created micro-sites for each product line, including their own social presence
- Aggressive social ads targeting the millennial and generation x demographic
- Worked with key influencers, such as Casey Neistat, to bolster their earned media strategy and tap into the power of influencer marketing
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Furthermore, this strategy led to an 82% “conquest rate” (the number of new buyers who previously purchased from another brand).
As you can see, the power of customer segmentation can yield better conversions, more sales, and higher profitability.
So, how are you going to use it to supercharge your business results?
Share your plans, stories, and results in the comments below.