• Tom Rothfischer, Author |
  • Gavin Lubbe, Author |
3 min read

It sounds obvious, but it's true: the strength of your data strategy is tied to the signals you choose to follow. Organizations can embed all the data-harvesting systems and talent they want, but actionable insights come from curated and relevant data sources.

Otherwise? It's just noise.

You've likely heard the term "data signal" before—especially if your organization has been on the path to becoming a data-driven real estate company. In short, a "data signal" is any statistic, measurement, metric, or piece of information that can be used by business leaders to make insight-driven decisions.

There are many data signals out there for the taking. They range from regional weather stats to customer spending habits, retail activity to crime statistics, asset performance to energy usage . . . and the list goes on.

What makes for an effective data signal? It depends on what your goal is. The real estate sector is home to many different players, each with their own unique clients, portfolios, and success indicators. Once you know what you want to achieve with your data, finding the most relevant data signals isn't difficult: you just have to know where to look.

Not just any signal will do
It would take more than a blog post to list all the data signals that are available to the real estate community, especially when you factor in various jurisdictions and range of public/private data sources. We think it's more useful to review a few examples.

Consider a small bookstore in a mall. Using data about nearby foot traffic, customer buying preferences, and activity from nearby stores, it's possible for a landlord to piece together insights that can help the bookstore maximize flow to its location, distinguish itself from online retailers and, ultimately, boost its revenue.

Now think bigger. Similar data signals (e.g., mall traffic, shopper wi-fi usage patterns, local demographics, sales trends) can also help retail landlords determine the best possible location for their tenants. Suppose a store attracts older customers. In that case, it may make more sense to place it closer to an entrance and near other retailers and service providers who cater to the same demographics.

Office and commercial property stakeholders can also wield internal and external data signals to find the optimal configuration for their tenants. And perhaps more importantly, they can use publicly sourced data to home in on the sorts of tenants that would bring the most value to the property.

As for the restaurant and hospitality community, there are plenty of reasons to "read the signals." Recently, KPMG's Lighthouse team combined several data sources and signals to help a quick-serve restaurant narrow in on the best possible location for its café. They looked at everything from traffic patterns to public transit routes and even which locations had public seating to offer several locations that would be best match the café's operations and target customers.

There are countless examples of how real estate organizations benefit when they turn data signals into testable, value-increasing decisions. And whether the intent is to maximize retail activity, optimize properties, maximize revenue from your tenants, or simply find the best tenants to begin with, there are many signals to inform the journey.

Spirit of investigation
It may take time to find the right data signals for your purposes. That's to be expected. Part of being an effective data-driven organization is having the capacity and willingness to hypothesize the kind of insights you're looking for and putting them to the test. It's about going one step beyond merely "looking" at the data and generating accurate and timely insights that benefit portfolio managers, their tenants, and tenants' customers alike.

Remember: data is a raw enabler. It's what you do with that information that counts. Real estate organizations that extract full value from their data strategies are the ones that know how to turn stats on a page into value-driving actions. And a large part of that is knowing what signals will point the way.

If you're looking for an even better understanding of how to leverage data and analytics, intelligent automation and artificial intelligence to make faster and more confident business decisions, contact KPMG in Canada's Lighthouse team.