Listing Manager: A National Real Estate Listings Platform

01National MLS Platform

Listing Manager: A National Real Estate Listings Platform

Agents Reached10K+ Agents MLS Partners7+ MLS Markets15 Markets ApproachPhased, MLS by MLS

Outcome6 Days per MLS, Was 6 Weeks

Reduction~86% Faster Onboarding

Team26 Across 6 Disciplines

SystemLBC System of Record

ComplianceNAR Clear Cooperation Policy

IntegrationRPA for Non-API MLSs

Status7+ MLSs Live Nationwide

DeliverableAgent Self-Serve Listings Platform

The Scenario

No centralized way existed for agents to submit listings, and every MLS had its own rules for how a listing needed to be entered. This was new ground for the organization and the industry, so it had to be built from scratch: an industry and enterprise platform where agents and brokers could create, publish, and manage their own listings, reviewed and published to the MLS on their behalf. Every submission is also bound by NAR's Clear Cooperation Policy, which requires a listing to hit the MLS within a set window of being publicly marketed, across 500+ MLSs nationally.

02Challenge

This wasn't a rollout of an existing tool. It was building the tool, and the credentialing process behind it, from nothing.

Aligning Engineering, RPA, Data Science, MLS Credentialing, and the LBC team on one roadmap, with dependencies running in every direction
Replacing manual, error-prone MLS website scraping with data science and AI, after months of business analysts doing it by hand
Every MLS required its own set of required and optional fields, so no single entry form worked across markets
MLS credentialing could only be done by one trained person with access to that MLS's staging site, a single point of failure
Building operations support into the go-to-market plan for the moments RPA failed and an agent needed a person in their metro or region office

03Action

Led a cross-functional team of 26 across 6 disciplines through a phased rollout: pilot MLS, measure adoption and support volume, then expand, scaling MLS by MLS across 15 markets.

Managed a 26-person team across Engineering, Data Science, RPA, Architecture, UX, and the LBC team.

Ran joint sprint planning across Engineering, RPA, Data Science, MLS Credentialing, and the LBC team to align five groups on one roadmap and manage the dependencies between them.

Built the platform from the ground up: one place for agents and brokers to create, publish, and manage their own listings, with single-point access to Anywhere's affiliated services: mortgage, title, insurance, RealVitalize, Exclusive Look, and Listing Concierge. Every listing published to the MLS on their behalf. Centralized listing management for internal Anywhere products, EL, LC, and Dash, too, so those teams worked from the same listing data instead of their own copies.

Launched an MLS pilot, then scaled to 7+ MLSs across 15 markets, reaching 10K+ agents in Florida metro markets and Minnesota.

Replaced manual, business-analyst-driven MLS scraping with automated data extraction, and used generative AI for listing content only where it cut real manual typing, not as a showcase feature.

04Results

10K+real estate agents reached

7+MLSs integrated and live

6 Daysto onboard a new MLS, down from 6 weeks

~86%reduction in MLS onboarding time

Listing Manager didn't exist before this team built it. Going from 3 sprints to 6 days per MLS wasn't a tweak, it was proof that manual, one-person-at-a-time credentialing could be replaced with a system that scaled. It also gave the organization something it didn't have before: one owned source of listing data instead of five disconnected systems, built to keep up with wherever the market went next.