Transforming Real Estate Management with Big Data

In an era of Big Data, retailers are finding new ways to leverage that information to improve processes and consumer engagement. However, there’s one area where Big Data can have a big impact that companies in the retail space may be missing: real estate.

Mark Ledbetter, global VP retail strategy for SAP, recently spoke with Chain Store Age about the promise of Big Data for retail real estate, and how retailers can best take advantage of it.

Where does retail real estate data originate?

There are three primary sources for the data for managing retail real estate. First is the retail store or shopping center itself. This might include energy-consumption data down to the sub-meter level for managing energy use. It might also involve sensors on equipment that can improve service and reduce downtime, minimizing disruptions that affect shopping. This data can improve retailer operations, lift tenant satisfaction, and provide mall owners with opportunities in areas like buying and selling energy.

Second is shoppers. Both retailers and mall owners can use video cameras, Wi-Fi, cellular signals and other technologies to measure shopper traffic to understand consumer behavior, reduce bottlenecks and optimize staffing. A lot of this data gathering can be done anonymously, protecting shopper privacy.

Third is customer sentiment data, gleaned primarily from social media. Sentiment data lets you see in near-real time what people are saying to their friends about your store or your mall, and offers clues to how you can better engage them. Shopper and sentiment data can help retailers and retail property owners evaluate the best places to open a store, or to acquire or develop a retail facility.

What technologies do retailers need to gather and analyze real estate data?

Machine-to-machine (M2M) sensors and communication can capture facility and equipment data. Mobile technology provides insights into customer behavior and sentiment. In-memory databases allow you to pull together this enormous volume of structured and unstructured data in a single place. Advanced analytics enable you to quickly analyze that data to uncover hidden insights and even predict future trends. Cloud platforms can make the resulting insights available to the right people at the right time and at an affordable cost.

What advantages can retailers obtain from in-depth analysis of real estate data?

Retail investments have generally been based on location and demographics. But today you can add actual behavior of actual consumers, helping you make smarter decisions about where to open a store, where to acquire or develop a property, which products and services should be offered where, what kinds of rents are appropriate, and more.

Beyond real estate, all the new data you’re acquiring can help you better attract and engage consumers, long an explicit goal for retailers and increasingly one for mall owners. This is a win-win for both the retailer and mall owner, with retailers finding ways to maximize revenues and mall owners able to increase rental income and better retain tenants.

What is the financial benefit?

Previously, retail finance was always in reactive mode, waiting for the monthly close to make adjustments. Today, with real-time capture and analysis of new data streams, finance can respond dynamically to changes as they’re occurring. Even better, finance can perform what-if analyses to get ahead of the curve.

For example, as you do budgeting and planning, you can analyze store profitability and understand why a particular location is under- or over-performing compared with forecasts. Even better, you can run scenarios to proactively decide to open a store at this location or divest yourself of a retail property at that location.

For retailers and retail property owners, Big Data means you’re no longer operating in a vacuum, making decisions based on best guesses. You have the insights you need to better manage your properties, deliver a superior consumer experience and run your business more profitably.

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