Retailers handle an enormous amount of data. And in an era of Big Data, they’re finding new
ways to leverage that information to improve processes and consumer engagement.
But there’s one area where Big Data can have a big impact that companies in the
retail space may be missing, and that’s real estate.
The promise of Big Data for retail real estate couldn’t come at a better time.
Consumers continue to be tight-fisted with their diminished disposable income.
Competition for consumer dollars and attention comes from a growing number of
rivals, channels, and venues. Retailers and retail property owners alike need
to maximize their revenue per square foot like never before.
To meet those challenges, companies should take three steps to leverage Big Data to
transform the way they manage real estate. First, they need to identify sources
of Big Data they can act on. Second, they have to invest in the technologies
that will position them to take those actions. And finally, they must apply
their Big Data insights in ways that show up on the bottom line.
1,000 Points of Light
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, WiFi,
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.
The last type of information 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.
Act and Engage
All these data sources produce information that, with the right analysis, give you
new insights, enabling you to take action to improve your business. Gathering that
actionable information requires investment in several key technologies.
Machine-to-machine (M2M) sensors and communication can capture facility and equipment data. Mobile
technology can give you insights into customer behavior and sentiment. In-memory
databases can 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.
While cloud platforms can make the resulting insights available to the right
people at the right time, and at an affordable cost.
This new analysis can transform the way retailers and retail property owners manage
their real estate. 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 retailer and mall owner, with retailers
finding ways to maximize revenues and mall owners able to increase rental
income and better retain tenants.
Finding the Payoff
Ultimately, the benefits from these data sources need to show up on the bottom line. In the
past, 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
to 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, delivery a superior consumer experience,
and run your business more profitably.
Want to learn more about how Big Data is transforming retail real estate? Look for the SAP Big Data Bus while you are at ICSC RECon, May 18 – 20 at the Las Vegas Convention Center (it is parked just across the street).