Customer Data | 5 mins read

The Different Forms of Customer Data & How to Extract Value from Them

the different forms of customer data how to extract value from them
Michelle Jaco

By Michelle Jaco

Analyzing data can help a company understand the customer journey, client acquisition, client retention, and satisfaction.

No matter which industry a company is operating in, customer data will always be one of the most critical aspects of building and satisfying its customer base. Without understanding how to analyze and use customer data correctly, companies are missing out on more business than they realize, and they are losing massive opportunities to please their customers.

Customer data indicate their relationship with a business or product. This data includes basic information and behavioral, interactive, and attitudinal tendencies. When a company understands and successfully extracts value from this information, it increases the likelihood of solving its target audience's problems. If data is mishandled, it can threaten the relevance and longevity of the company.

Here we will go deeper into the four primary types of customer data and how a company can use it to create a positive impact on the marketplace.

4 Primary Types of Customer Data

The term "customer data" covers a broad spectrum of information, beginning with basic info, and spanning to the ways a customer behaves and interacts with a product or service.

All data collected from a customer is essential to understanding how to service a client base better. However, the different types can be used in various ways to propel a company's success in customer retention and satisfaction. Here are the four primary types.

1. Basic Data
Basic information pertains to the surface level data from a customer. When a new client enters a name, email address, phone number, or home address, they enter basic information. It can also include targeted info such as annual income, geographic location, and associated organizations.
Basic information helps separate audiences and allows a company to segment a customer into a preliminary profile. Doing so will give an organization a way to reach a customer, kickstarting marketing efforts, and eventually narrowing down the best ways to interact with them along the customer journey.

2. Interaction Data
Interaction data digs a little deeper into how the customer is engaging with a product or service. It reveals how a customer acts when presented with a website, email, or marketing campaign.
Pageviews, link clicks, bounce rates, email opens, and downloads are all considered interaction data. When a customer engages with content, the customer's action is tracked and can be used to optimize landing pages to increase customer acquisition and retention rates.

A business can optimize content and marketing strategies to revitalize customer engagement along the buyer's journey, making the customer's experience more enjoyable.

3. Behavioral Data
Behavioral data is very similar to interaction data, except behavioral information specifically seeks to understand what a customer does with a product or service, and when they take measurable action.

What products or services is a customer using, and how are they using it? At what point along the customer journey does a customer typically register, add to cart, buy, abandon checkout, or complete a purchase?

Behavioral data includes any instance in which a customer takes any action step to engage further with a company's product or service. This data category helps a company hyper-target its ideal customer and create lookalike audiences to enhance marketing efforts.

4. Attitudinal Data
Attitudinal data is what people think, want, and feel about a product or service. A customer's attitude tells a business a lot about what they want, which pain points a company can solve, and whether or not their service satisfies the customer's needs.

Often, to find attitudinal data, surveys, focus groups, and A/B testing is used to gauge the target audience's opinions.

Ways to Extract Value from Customer Data

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There are eight main ideas of how a company can extract value from data collection. It is great to have the data, but if a company doesn't know how to read, analyze, and implement strategies based on it, it will not solve any problems. Here are the eight ways to extract value-

Understanding Big Data
A large company is going to have access to mountains of data that can feel overwhelming. The ability to sift through massive amounts of data often requires a specialized team to understand what is useful and what isn't. Accepting the fact that suitable data is buried somewhere in the pile is essential to beginning to glean helpful information. They just have to find it. This is why it's also best to consider data management platforms, as this will make the storing and sorting of data seamless and efficient.

Analytics
Analytical tools can make the data reader's job indescribably easier. Manually sorting through information and trying to group it together to draw conclusions is tedious and time-consuming, which costs a business money.

The best way to save time and ensure accuracy for a company is to invest in analysis tools. Doing so may have a slight upfront cost but will keep data analysis organized, accurate, and, most importantly, complete.

Historical Data
If a company is working in a field with case-studies from previous years, it can draw on conclusions made by previously tracked historical data to predict current and future trends. Customer acquisition and satisfaction is based mostly on psychology, and what has worked before will likely work again.

Using Data to Streamline Processes

A business, in most cases, wants to increase profits. Usually, this is done by increasing sales. However, if information about customer behavior can help cut unnecessary costs and streamline efficiency, money can be saved while potentially increasing sales. A business should always look for ways to improve efficiency along the customer journey.

Customer Churn and Retention
The best customer is a loyal customer. Using the proper analysis tools, a company can pinpoint where they are losing customers and why. By analyzing what services, products, or processes are pleasing and displeasing customers, a business can increase retention and ultimately spend less on marketing cold leads.

Social Media Data
Social media engagement can tell a business a lot about what customers like, what gets them excited, and what they are looking for. It can also help a company understand who their most loyal customers are, where they come from, what they like, and when they engage. All of these interactive and behavioral information can be extremely useful.

Accessible Data
Ensuring that each person has access to user data across the board is crucial. Various departments may need to communicate with each other to create a more seamless customer experience. Customer service is one of the most significant pain points for customers. Sharing data and keeping it accessible helps curb miscommunications.

Automation
Data analysis software exists and sells to make a business operator's job much more manageable. Time is money, and every moment spent manually analyzing information that the software could have done is money lost.

Investing in software to automate data analysis can save a lot of time, money, and headaches.
Making the most out of data collection is vital to a business's growth and success. Using the proper tools and resources can make a company's operations run smoother as well. Luckily, the software makes data collection and analysis a lot easier, allowing a company to focus on more hands-on issues.