Enhancing Client Service with Data Visibility
At JLL, we see a brighter way through the delivery of our data strategy. That strategy enables business users to make sensible, data-driven decisions in all areas of our business.
Whether advising clients, managing buildings, or increasing operating efficiencies, we present timely insights to decision-makers through data fusion and analytics. In JLL’s leasing business, we use data to increase customer satisfaction and make brokers more effective.
At its most fundamental level, leasing requires matching tenants and spaces. A simple view of this matching has two primary dimensions: Timing and Suitability. Timing is intuitive – the tenant and the space must be available simultaneously, or there can’t be a match. The earlier matching candidates are identified, the better. Suitability covers multiple factors, including price, size, location, etc. The greater the alignment on suitability items, the closer to a “perfect” fit and the more satisfied the client.
Leasing brokers must know their market – including client requirements, property information, and when spaces will be needed or available. Historically, a broker could keep track of this information in their head. Today, clients and markets are more complicated, and the avalanche of available data makes it nearly impossible for a broker to track it all individually.
JLL uses data and technology to tackle this problem.
To begin, we collect data from our internal systems about properties and spaces, including their size, price, location, amenities, etc. We also collect the preferences, lease expirations, and needs of our clients. We collect timing data about when spaces will be available from our property owner clients. That’s a lot of data, but there’s more.
We supplement internal data by adding external sources. Those sources include publicly available information, announcements, socioeconomic data, and data from third-party vendors.
All that data is brought together into JLL’s Enterprise Data Platform, or EDP. The EDP is a cloud-based, curated data lake developed and operated by JLL Technologies, the division of JLL driving innovation in commercial real estate with tech and digital initiatives. Data visibility is ensured through a data-driven automated tool that we’ve built. Data stewards and researchers further extend and refine the data, making it complete and dependable.
Once prepped, we perform analytics on the data. The analytics provide our brokers with detailed market information and potential matches. When we first started doing this, the matching was rudimentary. Timing was limited to those spaces that were either open now or very soon. Suitability was limited to minimal attributes such as price and size.
Over time, we have increased the suitability matching to incorporate more components like walking scores, vehicle and pedestrian traffic volumes, and socioeconomic information. All resulting in better-matched tenants and spaces. The matches are of higher quality and come closer to what tenants consider “perfect.”
And we aren’t stopping there. We continue to sharpen the algorithms and introduce functionality. Similar to how we have grown the suitability components, we are also expanding capabilities around timing.
Recently we deployed AI models that predict possible client needs before they are formally announced. The models look for signals in publicly available information and bring likely opportunities to the broker’s attention. This pulls the timing dimension earlier and allows the broker to be in front of prospective tenants sooner, giving all parties a better chance to find the perfect match.
Results from the analytics show up in two ways. First, brokers can identify and focus on “best fit” tenants, increasing their success and maximizing the return on their efforts. Second, clients are presented with superior matches, reducing the stress of finding an appropriate space and increasing client satisfaction.
This is just one of the many ways we use data and technology at JLL to enhance real estate services for our clients.
Written by Michael Norton, Chief Data Architect, JLL Technologies
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