We live in a constantly-connected era. Consumers interact with brands more than ever before – across various channels and devices, and at every step of the shopper journey. We use devices to research items, read reviews, compare prices, and seek advice. All of these interactions produce significant amounts of data that retailers could use to improve shopping experiences, create more customer loyalty, and boost margins. However, many retailers are struggling to gain value from these new heaps of customer information. Data often lies in disparate, siloed systems, and can’t be effectively matched or used in a timely manner, or simply isn’t being exploited at all.
More data does not necessarily equal more value. Retailers need to put the right technology and processes in place to ensure that they make the most of the mountain of customer data they are faced with. To fully maximize the benefits that come from using customer data more effectively, retailers need to consider how that data can be used at every level of the organization: from the enterprise (or head office) to the store and store associates, and ultimately, to the customer.
Also Read: Defusing GDPR Landmines Before It’s Too Late
Laying a strong centralized foundation for their customer data is perhaps the most important step retailers can take to make their data accessible and usable. From a centralized repository, the data can then be analyzed to forecast trends, make predictions, and adjust strategies based on consumer response. Many retailers are finding themselves with multiple systems cobbled together, struggling to find a single source of the truth. Job number one is to build a solid data foundation upon which the business can operate efficiently.
Predictive analytics allow retailers to see into the future and stay one step ahead of the trends. A business intelligence system that supports actionable analytics is the ultimate tool for optimizing the customer experience, using data to take immediate actions that will drive smarter, more targeted, and more effective campaigns – moving beyond basic segmentation to true personalization.
Does personalization really matter, or is it just a gimmick? A recent McKinsey & Company study found that personalization reduces acquisition costs by as much as 50 percent, lifts revenues by 5-15 percent, and increases the efficiency of marketing spend by 10-30 percent, so personalization definitely has important business benefits.
At the store level, equip associates with customer data enabling them to deliver personalized service and tailor the in-store shopping experience based on each customer’s unique interests and desires. Clienteling software can be used to aggregate customer data from multiple channels – from past purchases to pages they browsed online, to items they desire on their wish list.
The best associates use this clienteling data not only to enhance the shopping experience while customers are in the physical store but also to proactively reach out to them in-between visits. Clienteling can be used to create alerts about anything from birthday reminders to stock alerts (i.e. call the customer when a shipment from her favorite brand arrives). This type of one-to-one proactive outreach about highly relevant topics is remarkably effective in driving return store traffic and sales of high margin, full price items.
Another way customer data can be used to enhance the in-store customer experience is with intelligent product recommendations. Machine learning is the secret ingredient for transforming mounds of customer data into highly relevant, personalized product recommendations. With machine learning, every page view, every like or dislike, and every purchase feeds into the intelligent engine that produces increasingly smarter output.
Everything that happens at the enterprise and store levels, of course, has the ultimate purpose of serving the customer better, but can retailers also use data to improve the relationship customers have with the brand outside of its physical stores? With the increase in popularity of e-commerce and, more recently, mobile commerce, customers are getting more and more accustomed to self-service shopping. They may spend thousands of dollars without ever setting foot in a store or interacting with a human associate. How, then, can brands make the online shopping experience a tailored and personal one? Forward-thinking brands are designing immersive, curated online destinations for shoppers, where they can shop in their own virtual store, catered just for them. It’s an online space with the customer’s own purchase history, wish list, access to their favorite associates, control over account information and loyalty data, and more. This personalized commerce experience includes intelligent product and promotion information for a truly unique and highly relevant digital experience.