How Can Fashion Brands Collect Data?

Fashion brands collect data (PDF) from internal systems, which is known as first-party data, as well as from data aggregators, known as third-party data. Among the sources of first-party data are:

  • Point-of-sale systems: Retailers use POS systems to take customer payments, accepting either cash or digital payments (credit/debit cards, digital wallets, and so forth). Businesses also use POS systems to gather limited amounts of customer information. Modern POS systems can connect payments to a customer using store loyalty identifiers, such as a phone number or loyalty number.
  • Customer relationship management (CRM) applications: CRM systems collect and manage pertinent information about customers and their connections with a company, including contact information, interactions with company representatives, purchases, service requests, and quotes or proposals. CRM systems help businesses develop stronger relationships with their customers. They let salespeople and their managers do tasks such as generating reports on how many customers are being contacted at any given time and estimating their likelihood to make a transaction. Fashion brands can use CRM to manage data on basic characteristics about a customer, including location, buying preferences, periodicity, and lifetime value.
  • Customer experience (CX) applications: More holistic than CRM, CX systems go beyond collecting and compiling information about customers and their interactions with a company. These applications help sales and service agents make offers and launch marketing campaigns and online ads. CX systems generally are designed to help organizations track their interactions with customers from the time they first connect, through the sale, and as customers receive services, get support, or engage in a new sales cycle.
  • Enterprise resource planning (ERP) applications: ERP systems let businesses bill customers and collect payments from them, track production and inventory, manage transactions with suppliers, perform risk management and compliance activities, and maintain their general ledger. A complete ERP suite also includes enterprise performance management, which is software that helps teams plan, budget, predict, and report on an organization’s financial results. ERP systems tie this multitude of processes together and enable the flow of data between them. By collecting an organization’s shared transactional data from multiple sources, ERP systems eliminate data duplication and provide data integrity with a single source of auditable truth.
  • Online shopping carts: In ecommerce, online shopping carts take orders and collect payments, and they can also track what customers have browsed but decided not to purchase. This creates a data source that’s particularly ripe for applying machine learning and other AI algorithms to spot trends in these abandoned digital carts and posit theories as to why an item wasn’t purchased.
  • Loyalty programs: Loyalty programs let retailers track customers across any channel (online, phone, catalog, in-person) by assigning them a loyalty number they can use every time they shop. Customers have incentives to use loyalty numbers because of the promotions, discounts, and other financial and nonfinancial rewards they receive. In exchange, businesses get a better understanding of their customers’ needs and preferences. For example, loyalty program members can receive early access to new products in exchange for filling out a survey or spending above a certain threshold. e.l.f. Cosmetics, a beauty brand popular among Generation Z consumers, for instance, rewards loyalty program members for contributing content, giving feedback, and voting on contests . Members earn points they can redeem for cash, gift cards, and other perks.
  • Customer call logs: Businesses can use AI to review customer call logs and identify specific areas of concern, such as a repeated product failure, as well as to understand customer sentiment trends through analysis of tone, word choice, and other indicators.
  • Online chat logs: Businesses can also use AI to review chat logs to understand why customers are reaching out to them and whether they’re frustrated or happy, all of which can be used to improve services in the future.