4 Types of Customers and How Retail Data Analytics Can Help You Market to Them

Knowing exactly what a customer prefers is critical to creating the perfect shopping experience. Research for our 2018 Shopper Survey Report detailing the modern path to purchase revealed almost half of North American shoppers approve of retailers collecting data to enhance their customer experiences – and retail data analytics can help you discover what customers want so you can deliver those experiences.

Identify Different Types of Customers

When it comes to delivering a personalized shopping experience, your point of sale (POS) or retail management system can help you segment your customer list. Grouping customers together by distinguishing characteristics, for example, by age, gender or geographic region, isn’t a new idea. It’s been used for some time to target a specific demographic that would be most likely to respond to an offer, such as a grand opening sale at a specific location or a senior citizen discount.

Retail data analytics, however, lets you take this idea further, segmenting lists based on shopping behaviors and browsing or purchase histories. If you have integrated retail system that encompasses systems including POS, eCommerce, and loyalty, you can begin to develop a clear picture of customers beyond basic demographics. Then you can use this intelligence to target specific types of customers with offers and marketing messages they will find most relevant.

Delivering a Personal Experience Depending on Profile

Retail data analytics will help you identify which customers fall into these categories so you can engage them using the best strategies:

Newbies. When a customer makes a purchase for the first time, you don’t want it to be the last time. Sales associates can take a few extra minutes with these customers to help capture contact information or enroll them in your loyalty program. Push messages to their smartphone the next time they are nearby or in your store, encouraging them to take advantage of special offers and let them know you’re happy they’ve returned.

Long-Lost Friends. Retail data analytics can also help you determine which shoppers haven’t made a purchase in a while. When you run a promotion or sale, find ways to sweeten the deal to entice these customers back to the store.

Discount Savvy. You can identify shoppers that only respond to discounts by tracking offer or promotional code redemption. Once you know who they are, give them the discount offers they want, and perhaps also direct them to merchandise that is offered at prices they may find too good to pass up.

Brand Advocates. These are your regular, loyal customers — the ones your sales associates know by name and who sing your praises on social media. Reward your best customers with loyalty rewards that they truly value, by analyzing their purchase histories to see what appeals to them. You can also mobilize them to help build your customer base by giving them rewards points or discounts for referrals. These customers may also welcome a product recommendation based on their shopping history, whether emailed to them or offered by a sales associate using mobile POS to assist them in the aisles.

This list of customer types, of course, isn’t exhaustive. You may want to segment your list even more granularly, identifying shoppers whose interest is focused on a particular type of product (e.g., men’s wear, toys, golf equipment, etc.) or targeting a very specific demographic. Once you’ve sorted your retail data analytics and know who your customers are, create shopping experiences they will feel are truly their own.