How Oxford Properties uses retail analytics data to illuminate tenant leasing & tenant engagement

Every leasing decision, tenant relationship, and development project can shift multi-million-dollar outcomes, leading retail analytics data to emerge as the north star. Yet for many, the industry still operates in what can only be described as “data darkness”. Disjointed systems, siloed teams, and limited sharing lead to decisions made without a full view of the truth.

Not so at Oxford Properties.

We spoke with Manil Wagle, Director of Data, Analytics & Research at Oxford Properties Group, to explore how the Toronto-headquartered global real estate investor and developer is using data not just to survive, but to thrive. From footfall sensors to dynamic rent modelling and AI-enabled decision-making, Oxford’s journey sheds light on what a forward-thinking CRE data strategy really looks like.

Developing retail strategies from macro insights and micro data

Oxford approaches retail analytics data at two distinct levels: macro and micro.

This hyper-local insight is essential in current market conditions within retail, office and particularly mixed-use developments where creating high-density, live-work-shop communities is a core growth strategy.

Oxford’s granular approach includes everything from analysing traffic in specific mall corridors to historical CapEx trends, retailer density, and sales productivity, data points that directly inform leasing strategies.

“We can’t make a leasing call based on one source of data,” says Wagle. “It’s about trade areas, average spend, even the number of retailers in the same category, . We simulate scenarios based on the investment size, whether it’s a 200-square-foot kiosk or a flagship Apple store.”

For Oxford, even foot traffic counts – literally. For every mall corridor we understands the traffic flows, building retail analytics data, helping to determine rent premiums based on traffic volume. High-traffic areas demand higher rent brackets, while quieter spaces are priced more competitively.

The data sharing dilemma: Good tenant relationships win

Tenant data, specifically retail sales data, remains one of the thorniest issues in the landlord-tenant relationship. Despite the challenges, Oxford is making headway.

“We’ve completed over a dozen joint projects where retailers shared full sales and traffic data, and we provided them with mall-wide performance insights in return.”

This collaborative model is a promising path forward—but still, adoption is uneven.

Taming data sprawl: Prioritizing data that impacts retail sales

With data sources multiplying, another issue emerges: information overload.

“We focus on quality over quantity. Before we tackle any problem, we ask: what are we solving, who benefits, and what’s the impact? If we can’t answer that, we don’t proceed,” says Wagle.

Oxford works closely with different departments to ensure that dashboards and insights align with actual needs, not just nice-to-haves.

Commercial real estate AI isn’t the future. It’s already here

While AI dominates headlines, Oxford has already embedded it into daily operations.

“We’ve been using regression, forecasting, simulations, and clustering models for over a decade,” says Wagle. “Now, we’re leveraging advanced AI solutions built in-house to automate internal reporting and drive smarter, faster decision-making.”

Oxford draws a clear line between using off-the-shelf macro data (from different CRE data providers) and building proprietary models for micro insights. It’s a strategic blend of buying and building that lets them stay lean and focused.

The focus on AI follows global trends with Deloitte’s finding​ a staggering 81% of real estate leaders say data and technology will be their top investment priority this year, outranking even capital improvements.​

Yet, in a recent KPMG report, 3 out of 4 top AI challenges for retailers were related to data, including data silos, poor data quality, and lack​ of standardisation.

Experiential retail, not e-commerce, is driving recovery. Oxford is adapting by evolving mall environments into destinations where people can connect, not just consume.

The retail landscape is undoubtedly changing, the notion that brick-and-mortar stores are obsolete is unfounded. Forbes recently reported five myths about the “death of retail”:

• Myth 1: D2C will cannibalize brick-and-mortar stores
• Myth 2: E-commerce meets all of a consumer’s needs
• Myth 3: Retail is a low-skill job
• Myth 4: Retailers can achieve faster growth online
• Myth 5: Stores are only for selling products

Retailers and property owners who embrace innovation, focus on customer experience, and integrate digital strategies are not only surviving but thriving in this new era.

Building tenant communities and relationships is core

Behind all the dashboards, SQL models, and AI chatbots lies a very human goal: better decision-making.

That ethos drives Oxford’s commitment to continual learning, alignment, and simplification. Whether it’s running customer surveys twice a year, benchmarking NPS scores, or helping teams cut through the noise—data is always in service to the people who need it.

And in an industry still struggling with data darkness, that’s a powerful beam of light.

See also

• eBook: Commercial real estate data – Are you operating in data darkness?
• Podcast: CRE Corner Ep#2 | Mark Bruce – The role of retail data