Customer Data: What you should know about the Gold Standard for Real Estate Network Planning
Data comes in many forms, and any retail or real estate professional knows that good data is the cornerstone of making sound site selection decisions. Most professionals begin with identifying a retail trade area and compiling demographic information about the potential customers in that area. Although this is a good start, it lacks specificity about the actual customer profile of the trade area, including their preferences and shopping behaviours.
Customer data fills this gap, providing a rich, holistic view of the people who shop in the trade area. Here, we look at the different types of customer data, why customer data is so powerful, and how easy it is to leverage customer data to inform your retail and site selection strategy.
Types of customer data
Different types of customer data tell you different things about your customers, from where they live to their shopping behaviours and spending patterns. Customer data moves the foundation of your retail strategy from simple demographics of a trade area to more nuanced and granular customer profiles.
Many retailers collect the postal codes of their customers at the point of sale. Postal codes are an easy and useful piece of customer data that allows retailers to identify with greater accuracy the size and shape of their trade area.
Customer loyalty and rewards programs are a veritable gold mine of useful customer data. While the main purpose of these programs is to improve customer engagement and ultimately increase sales, they can also tell you where your customers live, how often they visit your stores, how much they typically spend, and what they like to purchase. This customer data can identify customers who haven’t visited a retail location in a while and may need an incentive – a coupon, for example – to come in and shop.
The best part about this type of customer data is that loyalty and rewards programs also collect customer addresses, which means businesses can tie specific customer spending patterns to geographic areas increasing the specificity of information in a given retail trade area.
Geosocial data is a newer type of customer data that provides even more insight into customer preferences and behaviours in a particular location. Geosocial data is another term for location-based social media data, and it works by analyzing publicly-available social media posts in a particular trade area to build customer profiles that include what types of products they spend their money on.
Piinpoint has partnered with geosocial data provider Spatial.ai to help retailers and real estate professionals identify whether a particular store concept – a vegan bakery, for example – will perform well in a proposed location based on the customer profiles of the trade area. Spatial analyzes the data from billions of social posts and organizes them into more than 70 social segments, such as Pet Lovers, Dating Life, and Fitness Obsessed.
Mobile Location Data
Mobile location data is another type of customer data that can be used when other types of data aren’t collected or readily available. Mobile location data allows retailers to see when a customer enters a store, how long they stay, and what other stores or locations they visit. Mobile location data helps retailers approximate customer travel patterns to determine their willingness to travel a certain distance to get to a specific brand or type of store. Mobile location data is readily available from Piinpoint through our partnership with Near, the global leader in data intelligence curation.
Why is customer data so powerful?
Customer data allows retailers to understand their clients on a much deeper level so they can better pinpoint the most profitable locations in a trade area. It moves beyond the simple demographic profile of age, income, and education and includes hyper-specific and, more importantly, up-to-date information, including their interests, where they shop and how often, how much they spend, and what they buy.
Often, businesses make assumptions about their customers, but without solid customer data to back those assumptions, retailers may find themselves “missing the mark” on who their customers really are and what they really want. Vague information leads to too many missteps and miscalculations that threaten the health and viability of any business, while using customer data and consistently “hitting the mark” enables businesses to optimize and ultimately thrive – particularly in competitive markets.
Who benefits from using customer data?
Customer data is a powerful tool for all types of businesses, from smaller niche markets to large retailers with a wide trade area – but it’s utilized in different ways and for different reasons, depending on the business.
A small, niche business, like a vegan bakery, can’t open a store just anywhere, because it has a much higher chance of failure if it’s not located in a neighbourhood where vegans live. Using customer data to understand which neighbourhoods have high concentrations of people who would be likely to patronize a vegan bakery – and even the hours their customers are most likely to visit – ensures the bakery sets up shop where it has a high likelihood of success.
A much larger retailer, such as a wholesale club store, has a wide variety of customers and a much larger retail trade area. Customer data can tell this retailer where to focus their expansion efforts, what hours of operations are optimal, and what products their customers most often purchase. For large retailers accustomed to high volume and traffic, this information is invaluable for informing how they should stock their shelves, minimizing waste and moving more products out the door.
The beauty of customer data is that its usefulness isn’t limited to one type of retailer or one use case. The same customer data that tells one business where to locate its brick-and-mortar tells another business what their customers are most likely to purchase. What matters for any retailer is that robust customer data contribute to its ultimate success.
How easy is it to collect customer data?
Customer data is easier to collect than you may think. In fact, you might already be collecting informative customer data and not even realize it. If you do any sort of online retail or offer curbside pickup services, you already have access to customer addresses – combine that with mobile location or geosocial data available from PiinPoint and the publicly available demographic information of your trade area, and you can easily construct detailed customer profiles. Add a loyalty or rewards program, and integrate it with your Point of Sale system, and you’ll gain dynamic, real-time insights into your customers’ buying behaviours.
The more data points you collect about potential customers, the greater your edge in understanding their habits, their preferences, and your trade area as a whole. Customer data helps you tighten and optimize your operations for higher traffic, more sales, and a top-tier customer experience.