Most loan officers building a referral pipeline make the same early decision: follow as many real estate agents as possible and hope volume turns into business. But Mike Simon, founder of AgentBrief, says that instinct is backward and is one of the most common reasons a real-time data tool ends up underused. AgentBrief built its platform on hourly MLS monitoring, giving settlement service professionals a live feed of agent activity instead of a historical report. However, Simon says the data only pays off if you’re following the right agents in the first place, not just the most active ones.
The obvious signal to chase is listing volume. An agent with a lot of new listings looks busy, and busy looks valuable. Simon says that’s only half the picture. “How many new listings are they able to acquire every year? That’s a big one,” he said. “But second to how many listings they acquire, it’s really important for a loan officer to be paying attention to how many they actually close.” In a slower market, a high number of listings can be misleading. Some may be new construction, some may sit unsold for months, and a loan officer chasing volume alone can end up spending time on agents who never close the deal that made them look attractive to begin with.
Simon points to a third metric that gets even less attention: who the agent represents on the buy side. That’s a smaller, more finite number, but it tells a loan officer something a listing count can’t. A closed buy-side deal is confirmed business, not activity that might or might not turn into a transaction. Put together, the three signals Simon flags are listing volume, closing rate, and buy-side representation. None of them is useful on its own. An agent who lists constantly but rarely closes is not the same opportunity as an agent with fewer listings and a consistent close rate.
Simon has heard the counterargument many times from customers: invest early in newly licensed or low-volume agents, the thinking goes, and they’ll be loyal later. He pushes back on that every time. “You got to feed your family. You got to pay your rent,” he said, describing the instinct to focus on producing agents rather than potential ones. Investing time in agents who aren’t currently doing business, he added, isn’t wrong as a small part of a strategy, but it shouldn’t be the strategy. That distinction matters more in a real-time system than it does in a traditional CRM. When data arrives on a delay, the cost of following the wrong agent is diluted across weeks of missed context. When alerts are hourly, every notification a loan officer acts on is time spent on that specific agent instead of someone else. Following agents without transaction volume to back them up means spending real-time attention on stale opportunities.
Simon argues the shift to real-time alerts has changed how loan officers should behave once they get a notification. In the past, delayed data meant a more passive response. Now, with alerts landing within an hour of MLS activity, the same information demands a faster, more deliberate move. “This is real. This is new that just happened. I can move fast and move first,” Simon said, describing the mindset a loan officer needs once they trust the timing of the data they’re acting on. That trust only holds up, though, if the agent behind the alert is worth the response. A loan officer who filters for listing volume, closing rate, and buy-side activity before they follow an agent is positioned to act on every alert with confidence. One who follows broadly and reactively ends up with a feed full of noise, no matter how fast the data arrives.
For loan officers weighing how AgentBrief’s real-time signal compares to the historical data most lenders have relied on, the platform’s title and escrow solution shows how the same filtering approach has already worked in a settlement services vertical built on the identical referral dynamic. AgentBrief services are currently available in select markets.
