As any seasoned broker will tell you, long-term success in commercial real estate is built on having strong relationships. According to Buildout’s 2018 DNA of CRE survey, 73 percent of brokers cite relationship building as one of the most important characteristics of any successful firm.
Unfortunately, managing relationships in 2019 is no easy task. Simply having a “Rolodex” isn’t enough in this day and age; firms must manage sprawling databases of user profiles, track ongoing correspondence, and deal with multiple digital contact points. CRE firms must also account for specialized connections between stakeholders, including buyers, sellers, tenants, landlords, developers, investors, and many more. Combined with deal cycles that are more complex than those of prior generations, maintaining connections across your network can be a cumbersome and time-consuming task.
It’s no wonder then that many commercial real estate firms are turning to artificial intelligence solutions to help manage their networks. After all, AI is being used to drive our cars, control our thermostats, even cook our cheeseburgers; so why not use it to improve our relationships as well?
Some realtors might balk at the suggestion that AI can improve their professional networks. After all, we have social media platforms like LinkedIn and Facebook that place all of our relationships beneath our fingertips. Unfortunately, while social networks show that you are connected to other people, they can’t measure the relationship’s strength or identify hidden professional connections that you didn’t know existed. There is simply too much data relating to hundreds of potential relationships to quickly evaluate the most relevant contacts.
Fortunately, finding hidden connections is exactly what machine learning systems were designed for. Computers are simply better than humans at sorting through vast amounts of data and identifying insights that humans might miss. AI is being used today to help CRE professionals map out a firm’s entire relationship graph (with no manual data entry, mind you). By offering a clearer and deeper view of their network connections, AI enables these professionals to more easily identify the best person in their network for a specific task or find the right person to ask for a referral.
And pattern recognition is just the beginning of AI-based professional networking. Our increasing technological capabilities have granted CRE professionals access to a wide range of essential features, including:
Flagging “At Risk” relationships
Relationships take time to develop. Establishing rapport, building trust, and generating respect doesn’t just happen overnight. In order to build an effective network, professionals have to put the work in to keep in touch with the people who matter and build relationships one correspondence at a time. Managing these relationships can be particularly challenging in CRE, where few deals are ever precisely the same. This puts the onus on firms to maintain semi-regular contact with valuable clients to ensure they don’t fall out of touch.
Automated solutions assist in this task by keeping records of correspondence with each client. If you haven’t been in touch with an important contact for a certain period of time, the AI system might flag that relationship as “At Risk” and encourage you to reach out. Many platforms can go an additional step by keeping tabs on your communications with important contacts and if you’ve failed to reply to one of their emails, nudging you to get back to them promptly.
Tracking clients in deal pipelines
In CRE, communications certainly don’t end once you’ve partnered with a client. You’ll need to work alongside buyers, sellers, investors, developers, and other parties across all stages of the deal pipeline. These relationships and communications also need to be tracked and stored with care, which is another example of how automated solutions can assist CRE firms.
Take the commercial real estate firm T3 Advisors. As its business scaled and the team grew to more than 50 employees, it began using an AI powered CRM system to better track its pipeline and manage communications with all of its clients, partners and prospects. By applying AI, T3 was able to break down the data silos that exist within most CRM systems. This ensured everyone on the team had access to all of the information they needed about a contact or organization, from a full history of communications to a list of all of teammates to have reached out—all in real-time. This level of team-wide transparency enables T3 to more effectively develop and coordinate strategies for pursuing new deals, not to mention avoiding duplicate work.
Reducing false positives when choosing clients
As a professional network grows, the data it contains inevitably becomes more complex. Even with careful organization and attention to detail, this will eventually create inefficiencies within deal workflows. In their most benign form, these inefficiencies make it take longer to find the right client for a given task. At their worst, they will generate false positives of people prove unsuitable for the task, forcing you to start from the beginning.
AI-based relationship solutions can address this problem by highlighting the strongest connections between a firm’s needs and a client’s capabilities. This allows firms to narrow their focus on the most relevant relationships, increasing their efficiency and reducing the likelihood of false positives.
Real estate will always be a relationship business. Digital technologies have helped us create larger professional networks than ever before, but they’ve also made it challenging to manage one-to-one relationships at scale. For property professionals to get the most out of the networks that they work so hard to build, they need to embrace technology. AI solutions help by taking the data entry and guesswork out of the equation, allowing firms to focus on high-value client partnerships (and the subsequent deals) that matter most to your organization. For an industry that relies on connections, it can often seem like a race to collect more and more people into your network. But is the amount of good connections you have, not just the overall total. The bigger a network gets, the harder it can be to maintain, the good contacts often get lost with the bad. That is why a new era of AI-powered interactions is upon us. In the near future, we will see tech-enabled brokers, managers and advisers being able to do more than ever thought possible using AI—and the rest of the field wishing that they had followed suit.