The key to any successful business is understanding what your customers want. The thing is, it's sometimes difficult to know what customers actually want.
Enter customer data. Information that helps you to understand your customers so you can improve your business to serve them better. Customer data comes in many forms, and, in this post, we'll take you through the different types, give you ideas for how to collect data, and take you through some best practices.
What is customer data?
Customer data is a broad term that refers to any information collected about customers. It can include anything from customer addresses and contact information to customer buying habits and interests in specific products or services. Ecommerce brands need to analyze customer data in order to better understand their customer base, inform digital marketing campaigns and customer service efforts, improve customer experience, and ultimately increase sales.
Types of customer data
When it comes to customer data, there are a variety of different customer data points that you can track and analyze.
Personal information about customers can be split into two main categories: personally identifiable information (PII) and non-personally identifiable information (non-PII).
Personally identifiable information (PII) is data that can be used to identify an individual, such as their name, address, email, or phone number. PII also includes financial information, health records, and biometric data.
Non-personally identifiable information (non-PII) refers to customer information that cannot be used to identify an individual, such as demographic data like age, gender, or location. It also includes IP addresses and customer device data.
Most brands already collect identity data because it's necessary for allowing customers to complete purchases. However, both PII and non-PII are also valuable as they allow brands to gain deeper insights into customer behavior and preferences. For example, information about a customer's location can help brands tailor their marketing efforts to local customers. Similarly, customer device data can help brands understand customer browsing and buying habits, which in turn can inform their customer service efforts and customer experience.
Customer preference data refers to customer information about their preferences for specific products or services. This can also include customer interests, such as in fashion products, books, music, and movies.
Opt-in data about whether or not customers are happy to be contacted by you, for what reasons, and via which channels also falls under preference data.
Customer preference data can help ecommerce brands understand their customer base on a more personal level and create customer experiences that are tailored to customer interests. Let's say you are an activewear brand. If you have data on the activities your customers like, you can group them and send one set of marketing materials to the group that likes yoga, another to the group that runs, and so on.
Behavioral data refers to information that you gather about customer activities, such as browsing behavior — like what people look at and click on while shopping on your site — and orders customers place. Ecommerce brands can use behavioral data to gain a more in-depth understanding of customer behavior, preferences, and purchasing patterns.
With that enhanced understanding, you can optimize your site and marketing to drive revenue. For example, if you notice that most customers are making purchases at a certain time of day, this information can inform your marketing efforts by targeting your customers with offers and promotions during the times when they are most likely to buy. You can also optimize the design and copy on your site based on what encourages people to buy.
Qualitative customer data, which comes from things like customer feedback forms and reviews, has several strengths. Customer feedback provides direct customer perspectives about their experiences with the brand and its products or services.
For example, customer feedback may include customer comments about the quality or effectiveness of a product, which are crucial for brand success. This allows ecommerce brands to understand customer preferences from first-hand accounts and make informed decisions about their products and customer service efforts.
Qualitative customer data has its limitations; it's difficult to quantify and is often subjective because it can be influenced by external factors such as customer attitude or customer expectations. This makes it difficult to measure and track customer feedback, though it's still an important type of customer data.
Benefits of customer data
There are several benefits of customer data collection and analysis for ecommerce brands and their customers. Customer data provides valuable insights into what customers like and the way they behave, and you can use that information to make smart business decisions about product development, customer service, and marketing activities.
Consumers tend to respond well to personalized marketing. A 2022 study by Unsupervised found that 58% of Americans approved of personalized ads. Support is even higher among Gen Z, with 81% in favor of personalized ads. Customer data provides brands with valuable customer insights that can inform targeted and personalized marketing efforts. Brands can segment customers based on purchasing history or customer preferences and then target different customer segments with specific campaigns and promotions.
Data about how customers behave online is also useful for optimizing your customers' online shopping experience. By looking at which types of copy, images, and layout lead to conversions, you can adjust your online store to make the experience easier for your customers and more effective at bringing in revenue. Reviews and responses to surveys let you know what kind of support you should offer to customers, like whether they prefer to call, text, or live chat with customer service representatives.
Analyzing customer data also informs your decisions about which services and offers to prioritize. On a very basic level, you learn which types of products perform well with your customer base, so you can make informed decisions about the selection of products you sell. But it can also help you craft offers that drive conversion. For instance, if you notice many people abandon their cart once they see the shipping costs, it might be time to offer free shipping for orders over a certain order value.
How to Collect Customer data
Customer data is categorized as zero, first, second, or third party, depending on how you collect it:
Zero and first-party data is customer data that is collected by an organization about its own customers. This includes personal information, qualitative data from customer reviews, as well as behavioral data you gather from your owned channels, like your website.
Second-party data is customer data that is collected from a partner or supplier. It's essentially first-party data that's gathered by another organization about its customers and shared with you.
Third-party customer data is data that is collected through external sources. It's possible to purchase data from organizations such as market research firms, social media platforms, or customer data aggregators.
First-party data is often considered to be the most valuable type of customer data. It's collected through methods that are controlled directly by the brand itself, so it offers more accuracy, control, and reliability than other types of customer data.
Aside from the data you'll gather during transactions, you can also implement various strategies to gather even more data and learn from your customers. Use web analytics software to analyze customer interactions on your website. Monitor reviews that customers leave on your product pages. Track responses to and clicks in email campaigns, social media posts, and ads.
Prompt customers to share their preferences and opinions with you. Survey your list of subscribers with product quizzes and feedback forms. Set up conversational pop-ups on your site. Send post-purchase surveys to people who have ordered from you.
Read more ideas for gathering zero and first-party data
Best practices for collecting customer data
Collecting customer data can provide valuable insights into customer preferences and behaviors. However, data collection must be done responsibly in order to protect customer privacy and ensure you collect high-quality customer data.
Ensure that all customer data is collected in accordance with laws in your area, like the GDPR guidelines
Use secure technologies such as encryption to ensure that all collected customer data remains confidential
Establish clear rules for how you will use any data collected and make sure that anyone in your organization who comes into contact with customer data is aware of those rules
Regularly review your procedures for collecting, processing, storing, and deleting customers' personal information
Use a customer data platform (CDP) or customer relationship management (CRM) system to eliminate data silos in your organization and ensure data protection
SMS: a direct line to your customers
Of course, the best way to learn about your customers — and to help them feel understood — is to talk to them. SMS gives you a direct line to your customers. Texts, which tend to have higher engagement and open rates than emails, allow you to engage with customers one-on-one.
Emotive is an SMS platform designed for ecommerce brands that want to grow. Book a demo today.