Retail data collection is gathering information about your retail store performance as well as your customers and their demographics, behaviors, attitudes, and actions. Retailers can use this data to tailor their purchasing, marketing, and pricing decisions to better meet their customers’ needs and drive sales.
If you’re intimidated by the idea of gathering and leveraging shopper data, don’t be. There are plenty of ways—from the approachable to the very technical—to use knowledge about your customers.
We’re demystifying customer data to help you maximize your business’ potential.
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What is customer data in retail?
“Retailers should collect information about who their customers are and what their shopping patterns are, so as to develop demographic and psychographic segment profiles,’ says Akshay R. Rao, General Mills Chair in Marketing at the University of Minnesota’s Carlson School of Management.
Collecting data is always useful to develop insights about consumer behavior and segmentation. If certain types of consumers shop on certain days of the week and certain times of the day, then, for example, prices could be adjusted to cater to those consumers.
Akshay continues, “For instance, price insensitive consumers may shop late at night and buy few items, so prices can be raised during those times, and price-sensitive consumers might shop on weekends, so prices could be lowered at those times.”
Types of customer data
With so much information you could be collecting about your customers, where should you begin? Personal, preferential, and behavioral data are most pertinent to retailers.
Personal data, also known as demographics, includes things like a customer’s age, ethnicity, income, socioeconomic status, education, marital status, and where they live. These data points provide a basic profile of a customer, and often influence behaviors and preferences.
This type of data has to do with a customer’s preferences. What do they like? What do they value? How loyal are they to brands? Do they choose where to shop based on brand loyalty or do they price shop? How sensitive are they to prices?
Behavioral data is all about how a customer interacts with your shop. This includes information like purchase history and what, when, where, and how a customer shops with you.
How often do they frequent your store? Do they shop online or in-store. Do they only buy full-price items, or do they wait for sales and use coupons? How much time do they spend browsing your app? What kinds of items do they purchase?
Know your customers better with Shopify
Use Shopify’s customer profiles to get a complete view of your customers. Collect contact information, see what they buy online and in-store, how many orders they’ve placed, which channels they prefer, add notes to their profile, and more.
Benefits of customer data management
The ultimate goal of collecting customer data is helping you reach the right business decisions faster, resulting in more sales. Akshay names “optimizing pricing and product assortments, as well as shelf displays” as some of the ways retailers can use shopper data.
Other benefits of gathering and managing customer data include having a better understanding of the customer journey, being able to personalize marketing efforts, improving customer loyalty, and increasing sales.
Improved understanding of the customer journey
Data can give you a clearer vision of the path a shopper takes, from browsing to making a purchase. This understanding can drive business decisions that make it easier to turn a window shopper into a customer.
For example, when you discover that customers tend to find out about new products via your newsletter and ultimately make purchases in-store, you can display the products featured in your newsletter at the front of your brick-and-mortar shop to increase foot traffic.
Or, if you notice that customers abandon their carts online after learning shipping costs, you could decide to introduce free in-store pickup or free shipping (while adjusting prices to accommodate your new costs).
More effective personalization
Cookies and other tracking systems can help you better understand your customers’ habits and preferences. With these insights, you can create more effective marketing campaigns by personalizing your efforts and sending the right offers to the right customers at the right time.
Research shows that shoppers are more likely to take action on promotions or offers that are personalized to their likes, needs, and interests. According to research by McKinsey & Company, personalization can increase conversion rates by up to 15%, boost sales by 2%, and reduce marketing costs by up to 20%.
When you spoon-feed shoppers the products they’re looking for, you’ll be able to drive sales.
For example, if a customer has looked at a specific bed frame on your website dozens of times, has put it in their cart, but hasn’t pulled the trigger, they may be price sensitive. You could send them an exclusive offer for 10% off bed frames to help them make the purchase.
Improved customer loyalty
Returning customers are worth more than one-off customers because they’ll spend more with you over a lifetime. Harvard Business Review says that just a 5% increase in customer loyalty can increase sales by up to 95%.
The more you know about your customers, the better you can curate their shopping experience, which can boost loyalty and repeat business. For example, with a customer loyalty program in place, you can send customized flash deals to incentivize sales and boost purchase frequency.
Ultimately, all of these benefits lead to one thing: generating more money for your business. Knowing your customers empowers you to bring them what they want (and things they didn’t know they wanted), when they want it.
Customer data can help you present upselling and cross-selling offers that shoppers will be more likely to accept, helping you increase the value of each purchase.
If, for example, you find that customers typically purchase a specific toolkit and TV mounting set from you, you can cross-sell these products online and in-store. You could bundle these products, feature them in the “Others also bought” section of your online product pages, or place them next to each other in store displays.
With the right tools, such as electronic shelf labels, Akshay says you can implement dynamic, individualized pricing. For example, if price-insensitive customers shop with you late at night, you could raise prices in the evenings. And, if price-sensitive customers shop on the weekend, you could decrease prices then to stimulate sales.
How to collect customer data
So, where can retailers go to gather data about their customers? Here are some great sources of customer data:
Let's look at each of these data sources closer.
Point-of-sale (POS) system
Your store’s POS system is a treasure trove of customer data. It collects consumers’ personal information, payment data, purchase history, and much more. Refer to your POS system’s reports and analytics to get started. You can also export raw data to use in more advanced business analytics tools.
💡 PRO TIP: Sending digital receipts via email is a great way to organically collect customer contact information at checkout and build an email list to fuel your retention marketing. Just make sure they’ve opted in to hearing from you before sending them anything.
If you have one, your store’s app is a great source for data about consumer behavior and preferences.
With the advent of smartphones, retailers can incentivize consumers to download shopping apps and then track individual behavior at the micro level, including how much time consumers spend browsing [or] searching in a particular category.
In your ecommerce platform’s analytics feature, you’ll find a combination of data found in your POS and on your app. You can discover customer behavior, purchase history, payment data, and lots more.
Surveys are fantastic tools for collecting qualitative data, such as customer sentiment. Send surveys to your email subscribers periodically and ask them things like what they like about your store or website, what kinds of products they want to see more of, or how the returns process could be improved.
You could even automate feedback surveys after customers make an online or in-store purchase if their payment method is linked to their email address.
Social media polls are an informal, easy alternative to email surveys. Use them to crowdsource product ideas, vote for in-store displays, and more.
Aside from being a great marketing tool, in-store events are also an opportunity to collect anecdotal data. They can help you brainstorm new products, observe how customers interact with a new store layout, or feel out sentiment toward opening new locations.
Take things a step further by making your branded events ticketed and asking for customers’ email addresses in exchange for entry. You can then use their email addresses to send them newsletters and other marketing offers.
Instagram, Facebook, Twitter, TikTok, and Pinterest can be useful tools for both collecting customer data and targeting customers with ads.
Some of these social media platforms provide reports and even raw data if you have a business profile. Use this information to understand customer behavior and interests.
Focus groups and mystery shopping surveys help you collect metadata about customer behavior, rather than individualized information about your consumers.
Focus groups are ideal for getting feedback on products you’re considering developing, while mystery shopping is a good option for monitoring employee behavior and getting feedback on the overall shopping experience.
Make a habit of regularly reviewing your business’ online reviews to understand trends in customer sentiment and make changes accordingly.
Leverage your retail customer data
Data is critical to running a modern retail business. Leverage tools like POS reports, app and website data, and surveys to gather personal, preferential, and behavioral data to gain a comprehensive understanding of customers on a collective and individual level. Equipped with this knowledge, you can reach the right business decisions faster and make more money.
Fuel your retention marketing with Shopify
Only Shopify lets you create customer profiles that unify online and in-store order history, preferences, and contact information. Use tags to build segmented mailing lists and increase customer lifetime value, make more relevant product recommendations, and more.
What is customer data FAQ
What is meant by customer data?
What is an example of customer data?
What type of data is customer data?
What are the 4 main customer data types?
- Demographic data - This includes customer age, gender, ethnicity, marital status, and income.
- Behavioral data - This includes customer preferences, purchase history, website visits, and online searches.
- Psychographic data - This includes customer values, attitudes, interests, and lifestyle choices.
- Contact data - This includes customer email, phone number, mailing address, and other contact information.