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It's a cliché, but knowledge is power—and that's certainly the case when it comes to your customers and your ability to understand what they want, as well as when, how, and where they want it.

In a 2022 survey by Econsultancy and Adobe, 74% percent of leading marketing organizations consider themselves effective at collecting first-party customer data, and 68% are using this data to personalize experiences. 

In this article, we'll look at 4 key types of customer data and how you can leverage them to provide a better customer experience and take advantage of new opportunities to grow loyalty and customer lifetime value (CLV).  

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What Is Customer Data?

Customer data is any information that you have about customers. 

It can be collected from multiple touchpoints and the goal is to produce actionable insights and ideas for experimentation. 

At the highest level, data comes in two types:

  • Quantitative data – Data sets comprised of numerical values related to quantifiable metrics. An example would be the percentage of customers who have renewed their subscriptions this year.
  • Qualitative data (or non-numerical data) – Observed and recorded from sources such as reviews, interviews, focus groups, and surveys. An example would be a comment like "great customer service" on your Google My Business reviews page.

Much of the data you collect will be first-party data i.e. personalized data that you collect yourself from your customers’ interactions and behaviors, or zero-party data, that customers provide you directly through form fills and other methods. You can also purchase second or third-party data collected by other companies on your behalf. 

With the advent of big data and AI, data collection is now becoming increasingly sophisticated with more granular insights. 

People's online activity is mapped into little data points ready to be drawn into your brand's orbit. However, as we've seen with the implementation of GDPR in Europe, it's important not to overstep the line here.

4 Types Of Customer Data

A strong foundation in CX data literacy allows teams to better understand customer needs. When it comes to data, the more the better. Regarding customers, there are four types of data you can collect.

1. Basic or Identity Data

As the name suggests, basic or identity data is pretty meat-and-potatoes.

Name, phone number, email address, IP address, LinkedIn profile, as well as gender, income, and industry are all examples of basic data.

It can also include more specific aspects of their life, such as the ages of their children, their household’s annual spending, their ethnicity, or whether or not they have pets.

On its own it's useful, but, when enough basic data is collected, you can start to piece together the demographics of your customers. Demographic data is useful because you can use it for customer segmentation, or grouping customers based on shared attributes.

2. Engagement Data

Engagement data shows how your customers engage with your brand across the various touchpoints.

Some common examples of engagement data include:

  • How customers are interacting with your e-commerce website
  • How often they like, share, or reply to your posts on social media.
  • Total website visits
  • User flow
  • Clickthrough rate
  • Conversions
  • Email opens, forwards, and bounce rate

This type of data is also called interaction data because, at its core, it measures how customers (and potential customers) interact with your brand.

Usually, this is applied at a macro level, zooming out to assess click-through rates or how many shares you’re getting on social media.

3. Behavioral Data

Many people lump engagement or interaction data and behavioral data together, and the differences between the two are very nuanced. 

Behavioral data focuses more on the way the customer interacts with your service or product directly. This can include things like: 

  • Purchase history 
  • Abandoning shopping carts 
  • Renewing subscriptions 
  • Using free trial offers
  • Mouse movement data tracked by heat maps
  • Average order value
  • User attention
  • Devices used for browsing

Who’s following through with making a purchase or signing up for a subscription service? Who isn’t? Why not? Looking at this data can help you figure all that out.

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4. Attitudinal Data

While the previous types of data are more objective, attitudinal data is provided by customers as a first-hand opinion about what customers think about your brand, product, or service. 

There are many ways to collect this data. Some you have a little more control over, like surveys or comments from interactions with customer service, while others, like online reviews, are completely out of your hands.

Attitudinal data can also include things like your customer’s motivations or challenges, purchase criteria, and preferences, or the desirability of your products. 

The main issue with this type of data is that it’s harder to assess. Why? Because not every customer shared their opinion in the same way at the same volume. 

If you have multiple five-star reviews that are short but sweet, do they outweigh one lengthy, scathing one-star review from an angry customer? What about all the customers that don’t leave a review?

This is precisely why it’s so important to seek out all customers and encourage them to leave a review. A popular method of simplifying attitudinal data collection is by assigning customers a Net Promoter Score (NPS). This is a metric often used by businesses to rate the likelihood that a customer will promote your business to a friend, which is an effective way to predict company growth. 

Methods of Customer Data Collection

With so many different types of customer data to collect, it comes as no surprise that there are several research methods to choose from. Here are some common approaches you can take.

Assessing Digital Behavior

Data aggregation platforms can help you to collect and analyze information on a customer’s digital behavior across social media or other web platforms. Social media platforms themselves also have features for measuring and tracking customer behavior. 

Customer Interviews

Conducting customer interviews gives you access to a goldmine of insights. This is a great way to collect a range of data types including basic information, behavioral data, and customer satisfaction. Use this information to determine what you need to change to improve customer experience.  

Online Surveys

There are plenty of online survey services that you can integrate into your website or email platforms to collect user data. These are most effective when distributed immediately following a transaction or service. Online surveys are especially useful for collecting behavioral data.

Offer Sign-Up Forms

By providing an offer sign-up for customers, not only can you collect basic data like email, phone number, location, age, or gender—you can also find out whether they’re interested in the type of product you’re offering. 

Focus Groups

Conducting a focus group with three or more people representative of a target demographic can help you gain detailed insights into their needs, experiences, and opinions. Assign a moderator to ask questions and keep the conversation on topic.  

Documents and Records

Creating a customer profile database can help you track purchase history, and you can add notes in their files for future reference. 

Website Analytics

Examining customer behavior on your website can help you gain valuable information which you can apply to SEO processes or design and layout changes. Here are some things to look for when assessing website analytics:

  • Web traffic
  • The most popular pages or products
  • What people are typing into search bars
  • What keywords people typed into a search engine to find your page

Other Marketing Analytics

In addition to website data, there are many other communication channels providing analytics that can give insights such as:

  • Email response and clickthrough rates
  • Social media engagement
  • Mobile app views and clicks

Putting Customer Data To Use

Now that you have a better idea about the types of customer data you can collect, you might still be wondering how you can wield it to your benefit. 

Here is how you can use your newfound customer intelligence to take your business to the next level. 

Improve Marketing 

Customer data can improve your marketing efforts considerably.

You can leverage your data to learn who your customers are and figure out the best way to reach them. By aggregating basic descriptive data, for example, marketers can create specific strategies to target these demographics.  

Who is your ideal customer? Young, single people? Career-driven women, or married men with families? 

Once you know who your target audience is, you can start fine-tuning your marketing strategy accordingly. Simply, you’ll be able to hit the right people at the right time, lower your customer acquisition cost, and increase lifetime value.

Improve the Customer Experience 

There are a few ways to use customer data to improve the customer experience. Dig deep into engagement data to figure out people are interacting with your website. 

Are they looking at the first page and leaving quickly? Is there a particular section that doesn’t attract any traffic? By collecting data on customer behavior on your site, you can find ways to improve the customer journey.

Another approach is to examine attitudinal data you get from customer reviews, surveys, and social media to see where you can improve your product or customer experience. The customer journey is more cohesive with big data in CX.

Figure out where there are problems and take their advice about how to fix them. For example, maybe your product is amazing and your customers love it, but the website is difficult to navigate and they have a hard time knowing where to look for their favorite items.

Boost Sales 

Generating more sales is the ultimate goal, but how can you use customer data to do it? 

The strategies we’ve already mentioned, when implemented correctly, are likely to increase sales. 

If you target the right customers with ads or through email marketing, they’re more likely to make a purchase. If you improve the customer experience, more people will purchase and your retention rate will improve.

Your sales team can also put customer data to good use, using it adjust pricing or create new products personalized to customers.

Customer Data Management

Customer data, both quantitative and qualitative, has historically been stored in a customer relationship management application (CRM) where it can be utilized by multiple departments. 

Data is often collected and stored by your web platform, email marketing provider, and social media platforms. As there is now so much data from multiple sources, customer data platforms (CDPs) have become more prominent in their usage over the last decade. 

These are like souped-up CRMs that allow companies to more easily collate disparate consumer data and offer greater personalization.

Letting the Data Drive

Digital marketing relies heavily on data for optimization and reducing customer acquisition costs. You can also be used to improve your customer experience and boost sales.

To paraphrase Winston Churchill, think of data collection as your “geese that lay the golden eggs.” 

Some further reading to help you collect these golden eggs:

What types of customer data have been surprisingly helpful to you? Let us know in the comments. And, for more insight and support, sign up for The CX Lead Newsletter.