Ben Teerlink of MMI: Quality over Quantity–Using Data to Build Strong Referral Partnerships

Ben Teerlink is founder and CEO of Mobility Market Intelligence, Salt Lake City, Utah, a provider of data intelligence and market insight tools for lenders, real estate agents, real estate brokerages and title companies. With a background in both real estate and data analytics, he uses his breadth of experience to expand the mortgage and real estate industries’ understanding of how the right data can be used to influence growth and positively impact business operations..

Lenders with an eye for success will need to rely on strong referral partnerships as the mortgage market cools, stiffening competition for leads and loans. Simply put, the key to referral partnerships is to aim for quality, not quantity. Maintaining a broad network of referral partners requires a significant time investment, and there is little to no benefit in having 15 partners that only sometimes send a referral. Instead, cultivating a handful of referral partners who consistently refer quality leads would serve loan officers better.

Thus, the question becomes, “How can loan officers ensure they are pursuing the right referral partnerships?” Like many things, the answer lies in data.

Living in a digital age can be a blessing and a curse, depending on the person and situation, but the human race never had access to more data than we do today. In fact, 90% of the world’s data has been created in the last two years.

Given the massive amount of data that exists, it stands to reason that data can be used to gather insights about nearly everything, but to gain those insights, the data must be collected and analyzed correctly and in its totality. In 2020, 60% of enterprises in the banking sector used their products and services to drive insights and monetize data. Yet, the average company only uses roughly 40% of its data, and 60% or more of the data collected is unanalyzed and unused. With a plethora of available real estate and mortgage data, gaining actionable intelligence can be easily accomplished by collecting and analyzing data from the right sources.

Real estate and mortgage transaction data can provide a wealth of information and insights to loan officers seeking reliable referral relationships. For example, determining which real estate agents are active in a particular geographic area is relatively simple. However, this information alone does little to indicate if a particular agent would be a good referral partner. Loan officers can identify agents whose activity matches their goals by layering in transaction-level data to determine “best fit” partners.

Once the right referral partner targets have been identified, the next step is to take action and convert the lead into a referral partner. Having scripts for these interactions is helpful, and loan officers should have several of these on hand to tailor the conversation to the partner in question. One of the keys to initiating these conversations is to have a catalyst for reaching out to the real estate agent rather than cold calling.

Three strategies loan officers can use to successfully strike up a warm conversation with a potential real estate partner include:

• Congratulating the agent on recent activity, such as a new listing or sale;
• Inquiring about an upcoming open house for a pre-approved borrower; and
• Introducing the real estate agent to a borrower in need of an agent.

Once the conversation is underway, loan officers can use the opportunity to plant the seed for what could become a thriving referral relationship. Obviously, loan officers need to identify the value they can bring to the relationship because always being available to answer the phone is no longer a differentiator. Loan officers can provide value to real estate agents by introducing agent-less buyers or helping to increase listing exposure, to name a few examples.

By using transaction data to identify a potential referral partner target, loan officers can glean helpful information about the agent and use that information to find the overlap in interests. Maybe the loan officer has a qualified borrower that wants to buy in the agent’s geographic area of specialty, or perhaps the loan officer has a client pre-approved for a VA loan who would prefer a real estate agent with ample experience working with members of the armed services. No matter the situation, loan officers with access to the correct data and analysis can ensure they are approaching the right referral partner for the job.

The bottom line is loan officers can use data intelligence and market insights to become more proactive in their quest for reliable referral partnerships. It just takes a combination of the right data and the right analysis.

(Views expressed in this article do not necessarily reflect policy of the Mortgage Bankers Association, nor do they connote an MBA endorsement of a specific company, product or service. MBA NewsLink welcomes your submissions. Inquiries can be sent to Mike Sorohan, editor, at msorohan@mba.org; or Michael Tucker, editorial manager, at mtucker@mba.org.)