3 Ways Retail Brands Can Make the Most of Customer Data
Customer data is the pivotal component that offers retailers the insights and tools to meet — and exceed — shoppers’ expectations.
Consumers have become increasingly expectant of a seamless retail experience, and they now require high-caliber personalization and a hassle-free shopping journey. They are spread thin across retailers, which is driving companies to invest in new operations to win business. AI, machine learning and APIs all offer retailers the ability to harness millions of data records and turn them into multifaceted value propositions.
For all of these reasons, data is an invaluable commodity to retailers. Below, we’ll share three ways companies can make use of the data breadcrumbs their customers leave behind — and set themselves apart in the retail landscape.
1. Smarter Marketing
Data can help you understand customers, their shopping history, preferences and what makes them decide to purchase. This data can be used to split your audience into different target groups for campaigns or even power individualized campaigns that encourage your consumers to shop products that are most likely to delight them. It can also inspire them to return to products they had previously viewed, leading to a conversion. This can look like:
- Retargeting product ads on social media or search engines.
- Sending emails that encourage a customer to return to finish their purchase.
- Serving personalized site promotions of categories the customer is interested in.
- Identifying missed purchase opportunities with customers who would likely buy products together, which allows you to market additional items and increase the cart value.
It is also important to understand the purchasing channels that most benefit the customer, which can be clearly identified through data analysis. Do the customers like to spend through social media? If so, you can stretch the marketing budget and increase their purchases by optimizing social media content, ads and promotions to inform them about the latest products and discounts available.
2. Predicting Your Customers’ Needs
You can forecast future decision-making and provide basket-building opportunities by using data to pinpoint the customer’s purchase timing and affinity categories. These kinds of predictions tell retailers a great deal of information about the likelihood of closing the sale.
For example, if a consumer purchases several pieces of clothing for an infant, the retailer then knows to serve up diapers, baby toys and formula products — and also when to start serving ads about items for toddlers. Add-to-cart (ATC) data predicts the needs and wants of the consumers and allows the retailer to be there to meet their needs. This increases revenue and builds brand loyalty with the consumer.
3. Personalizing Recommendations
The third and final way customer data can be utilized to benefit shoppers is via custom-made experiences. An Epsilon Research survey found that “80 percent of consumers are more likely to do business with a company that offers personalized experiences.” By leveraging customer data, retailers can make personalized recommendations to enhance the user’s shopping journey.
Personalization elements can include a range of things — from a unique homepage experience featuring only the categories and promotions that are relevant to an individual customer to specific fit and style recommendations on the product details page. These curated experiences make finding and falling in love with items simple. When customers are presented with products that are relevant to their purchase history or their style and fit preferences, they are more likely to make a purchase and return to that retailer to shop again.
Better understanding customer data allows retailers to meet their shoppers along every step of their journey and, ultimately, improve the brand’s bottom line. By taking advantage of AI, retailers can automate critical operations and personalization processes. These capabilities give retailers the power to adapt and keep pace with ever-evolving consumer demands.