Understanding Customer Data: Types, and How to Collect and Segment
From website visits to emails, reviews, purchase history, psychographics, and support tickets, it’s likely your business accrues a slew of customer data. This data is incredibly rich with actionable insights just waiting to be collected, segmented, and managed.
As a business owner, you know that understanding your customers is essential to the success and longevity of your B2C business. But what types of customer data are there? Where and how can you collect it? And what does it take to uncover the most valuable insights within it?
In this post, we’ll explore the world of customer data. By the end, you’ll have a better understanding of how different types of customer data accelerate the growth of your business.
What is customer data?
At the most basic level, customer data is any information about the people your company serves. This includes contact information, demographic data, customer preferences, and online interactions.
Collecting and analyzing customer data helps you understand your target audience more deeply. It reveals their needs, wants, and even the beliefs that drive those needs and wants. This enables you to make data-driven decisions to attract and retain more customers.
Types of customer data
There are four main types of customer data:
- Demographic data
- Psychographic data
- Behavioral data
- Transactional data
Here’s a closer look at each one:
1. Demographic data
Demographic data is a set of characteristics by which you can identify your customer base. This includes things like age, gender, income, and education level.
This type of data is useful for understanding who your customers are and what their needs may be. It can also be used to segment your customer base for marketing strategies and full-blown campaigns.
For example, if you’re selling an anti-wrinkle cream, you may want to focus your marketing efforts on the age groups most likely to purchase your product. Gathering demographic data on your customer base will make your campaigns more targeted and improve results.
2. Psychographic data
Psychographic data—made up of a customer’s values, personality traits, opinions, attitudes, beliefs, and lifestyle—can shape your selling approach and messaging. It’s no longer enough to target a part of the market with demographic data. Think of psychographic data as the next step up.
It’s simple: while demographic data may help you appeal to a customer’s logical or analytical side, psychographic data helps you appeal to the emotional component that goes into a buying decision.
Consider how Bryan Kramer, marketer and author of Human to Human: H2H, puts it: “The fact is that businesses do not have emotions. Products do not have emotions. Humans do. Humans want to feel something.”
What motivates your customer? What kind of messaging will they respond to? What brand voice or attitude will push them to hit the buy button? All these questions are easier to answer once you’ve gathered enough psychographic data to paint a more comprehensive view of the customer.
3. Behavioral data
What actions and behaviors do your customers take? Behavioral data includes anything from purchase history to website interactions or opting in to your newsletter in exchange for a discount. This type of data helps you understand what your customers want and need, and how they interact with your business.
For example, continuing with the wrinkle cream scenario, users of a certain age that land on your homepage and click through some of the featured product pages show some level of brand awareness as well as buyer intent. Buyer intent insights strengthen when you track user behavior data and see that they came back a day later to sign up for your brand newsletter.
That example is just a small scenario illustrating how analyzing behavioral data helps you further optimize the touchpoints throughout your customer journey. You’ll learn as you begin to understand what actions your customers are most likely to take, when they’re likely to act, and most importantly, why they’re doing what they do. This will also improve your lifecycle marketing efforts as you re-engage return customers.
4. Transactional data
Transactional data is information about a customer’s financial transactions, such as purchase amounts, purchase frequency, how long it takes the customer to make those purchases, and how many items they’ve returned.
This type of data helps marketers understand spending patterns and trends among your customers. It’s especially important as market forces shift, new technology is introduced, and new variables enter the buying equation.
How do you collect customer data?
There are many ways to collect customer data. The most important thing is to ensure the information you’re collecting is accurate and up to date.
Software: CDPs and CRMs
Today, the most effective approach to data collection and management is using software designed to ingest, organize, and manage customer data at scale.
The right platform will optimize your data collection and even data orchestration with a combination of features and functions that include the following:
- Email marketing (ESP) features
- Audience management
- Predictive modeling
Customer data platforms are a streamlined solution for collecting and using your customer data. CDPs help you automate marketing tasks like sending emails, orchestrate cross-channel marketing, or create more targeted ads.
The beauty of customer data platforms is that you can enhance your campaigns with hyper-personalization and real-time messages.
Customer Relationship Management (CRM) software is yet another option that helps you manage your relationships with customers and prospects. It also helps you track important information like contact details, purchase history, and communication logs.This is information that can be stored within your CDP.
Surveys and focus groups
Another way to collect customer data is by sending surveys. You can either give customers a paper survey or use an online survey tool like Survey Monkey.
Old-fashioned focus groups can also be a great way to get detailed feedback from your target audience.
Collecting direct feedback
Finally, you can collect data by speaking to your customers directly. This could be done over the phone, through email, or in person. If you speak to customers directly, you will better understand their needs and wants. This approach can also uncover objections, attitudes, or behaviors that weren’t so apparent before.
Ultimately, it’s all about getting closer to your customers and creating a brand that appeals to more than just their logic.
A note on compliant customer data collection
We’d be remiss not to touch on a few best practices for data privacy in this guide. Now more than ever, customers are wary about sharing their personal data. Marketers must respect customers’ privacy and ensure their data collection processes comply with data collection laws and regulations.
Here are three essential practices to follow:
- Right to opt out: Provide customers the option to opt out of providing their data.
- Legal compliance: Ensure your data collection practices comply with all relevant laws and regulations, such as GDPR and CCPA.
- Transparency: Be transparent about how you will use any customer data you collect. Make sure your website’s Terms and Conditions page explicitly details how you collect customer data, what you do with it, and how visitors or users can opt out.
While the conversation about ethical customer data collection goes well beyond the scope of this post, following these best practices will set you on the right track to collect valuable customer data without crossing any lines.
How do you segment customer data?
There is no one-size-fits-all way to segment customer data. Ultimately, how you segment your data will highly depend on your end goal.
Let’s look at a few examples:
Segmenting by demographic data
The most common way to segment your customer data is by using demographic data such as age, gender, location, or income level. With this information at your fingertips, it’s easier to learn what products or services interest your target market.
Middle class income couples who have a driveway, are between the ages of 23-60, and live in southern California won’t be interested in buying high-quality snow plows—it doesn’t snow in southern California. That’s an example of why segmenting by demographic is essential if revenue is the goal.
Segmenting by behavioral data
Another way to segment your customers is by behavioral data—which includes information on what kind of customers are more likely to make a purchase, how often they purchase, and what products they tend to buy.
For example, buyers searching for “best crockpot” are running that search query with buyer intent. They want to find the best crockpot for their use. That behavioral data can be a key part of shaping how, when, and why you’ll run certain marketing campaigns, like paid ads.
Segmenting by psychographic data
You can also segment your customer data by using psychographic data. This includes information on your customers’ values, beliefs, and attitudes. This type of data can be helpful in understanding what motivates your target market and how best to appeal to their needs.
Suppose you’re a religious retail store and you’re looking to pinpoint who is more likely to buy your religious items. In that case, you’d want to segment your audience by beliefs or religious subcategories. If, for example, you’re running an email marketing campaign, you’ll know not to send a particular religion’s products to a segment that doesn’t identify with it.
Segmenting by transactional data
What if you wanted to run a remarketing campaign? This is where segmenting by transactional data can be useful. By segmenting your audience by customers who have made several repeat purchases in order to target them, your remarketing campaign has a bigger chance of creating more revenue.
Why? Because it’s more targeted to an audience that’s familiar with your brand and primed to buy. This is infinitely better than running a remarketing campaign that includes customers still on the fence about making their first purchase (or haven’t at all).
Validating and analyzing customer data
Once you’ve created your customer database, you need to validate it and ensure it’s usable within your data systems. It’s critical to note that data analysis can’t happen before data validation.
To validate data, it’s important to run it through a set of rules against your existing database. The rules and even your approach to data validation will depend on the solutions you use as part of your marketing data collection and management process.
For example, with a data platform like Simon CDP, all the data you ingest—whether it’s first- or third-party data—goes through a validation process that checks for items like the following:
- Empty data fields
- Accurate timestamps
- Unique field names
- Appropriate identifiers
- Unauthenticated users
Any errors or omissions detected during this process will either be flagged or updated automatically, depending on the validation rules you’ve set.
Once the data is validated, Simon CDP analyzes it for marketing insights. For example, you can match website visitors to first-party data to create unified customer profiles. You can also pinpoint customers with unique identifiers that plug them into the right conversion campaigns.
Benefits of customer data analysis
One of the most important benefits of customer data analysis is that it helps businesses to understand their customers more deeply. Customer data analysis enables businesses to group their customers into segments, understand their needs and wants, and develop more sophisticated selling strategies.
Additionally, customer data analysis helps businesses identify trends and patterns in customer behavior, which improves the products and services they offer.
And there are many other benefits:
- Accurately gauging customers’ satisfaction with your products or services
- Gathering accurate metrics to measure the health of your business
- Increasing revenue and profit margins
- Improving customer retention rates
- Developing more successful marketing campaigns
- Increasing customer lifetime value
Do more with Simon Data
At Simon Data, we know that customer data is an important part of understanding your target market, meeting their needs, and providing a stellar customer experience. That’s why we enable marketing teams with the tools and features they need to create a better-rounded view of their customers.
Simon CDP centralizes, unifies, and manages all customer data so you can easily track your customers’ interactions with your business. You can gather contact information, demographic data, customer preferences, and more. Whether you’re looking for a more comprehensive way to execute data orchestration or you want to improve your lifecycle marketing efforts, Simon Data helps you get there.