EasyBroker is the #1 real estate CRM in Mexico, helping real estate professionals manage leads, publish and share property listings, collaborate with other agents, and keep deals moving. The company serves everyone from independent agents to large real estate businesses. More recently, EasyBroker expanded into the consumer side of the market with Pincali, a marketplace for people looking to buy or rent a home.
For a platform used by more than 35,000 real estate professionals, EasyBroker runs a remarkably lean operation: 14 people across the company, with five dedicated to customer success. For Vicky Maldonado, head of customer success, the size of that team is intentional. She has built the team around experienced people who understand both EasyBroker and the real estate professionals they serve.
As EasyBroker has grown, AI Answers has helped the five-person customer success team keep pace. Since introducing it in August 2025, AI Answers has handled roughly half of EasyBroker’s support volume, with a 63% all-time resolution rate. Vicky estimates that handling the same volume with people would require at least two additional junior customer success hires. At roughly 80,000 Mexican pesos per month for each employee, that would add up to 1.92 million pesos, or about $102,000 USD, in staffing costs each year.
More than knowing the product
EasyBroker's customers are real estate professionals, and their days are already filled with the work of managing leads, listings, clients, and transactions. Learning the ins and outs of a CRM is only one part of running their business.
For EasyBroker’s customer success team, supporting those customers means helping with the product as well as the business around it. Customers need help navigating the product and solving everyday technical questions, but they also need guidance on how to use EasyBroker to run their businesses more effectively.
That might mean reviewing a customer’s listings, advising them on how to manage their properties and leads, or helping them get more from EasyBroker. By combining their product knowledge with their understanding of the real estate market, the team can help customers become more successful real estate professionals.
Making a five-person team go further
“I never wanted to build a call center,” Vicky says.
For her, growing customer success means building a team where people can develop real expertise and build long-term careers at EasyBroker. It’s something she has experienced herself over 14 years with the company, and several of her teammates have been there for more than a decade as well.
With AI Answers handling a significant share of support volume, Vicky has more flexibility in how she grows the team. She can make hiring decisions around the expertise EasyBroker needs and the meaningful, long-term roles she sees people playing as the company evolves.
EasyBroker has also adapted its Help Docs to make AI Answers more effective. The team writes documentation around how customers actually ask for help, accounting for common misspellings and the language customers use when they don’t know the official name of a feature. That gives AI Answers more ways to connect a customer’s question to the right information.
Keeping that documentation current is especially important as EasyBroker ships new features. The team built an internal AI bot that maps changes in the product, identifies updates that are relevant to its documentation, and generates draft copy for the team to review. That helps EasyBroker keep its knowledge up to date alongside the product, giving AI Answers better information to work from.
Bringing product updates into the flow of work
EasyBroker has also learned that reaching busy real estate professionals requires catching their attention at the right moment. The company has an Updates tab in the product where customers can see what’s new. But with customers focused on managing leads, listings, and transactions, Vicky saw an opportunity to bring important product updates more directly into their flow of work.
EasyBroker uses Messages in Help Scout’s Beacon to surface updates while customers are actively working in the platform. Messages give new features and important announcements more immediate visibility, and Vicky’s team has found that customers are much more likely to notice and react to them.
That has made Messages a useful part of EasyBroker’s launch strategy, giving the team a more direct way to introduce new capabilities and encourage customers to try them.
Connecting customer conversations to product decisions
Customer conversations at EasyBroker reach well beyond the five-person customer success team. All of the company's employees have access to Help Scout, including members of product and marketing who use those conversations to understand what customers are asking for and how they're responding to new features.
EasyBroker uses Tags to organize those conversations and identify recurring feedback, questions, and product requests. The team pairs that qualitative feedback with behavioral data from Mixpanel, connecting what customers tell them with how they actually use the product.
That combination is especially useful around launches. When Mixpanel shows that a customer has tried a new feature, the team can follow up to learn about their experience, using their previous Help Scout conversations for additional context. They can also identify groups of customers who may benefit from a capability and tailor their outreach accordingly.
That shared view keeps customer feedback close to the people making product and marketing decisions. Together, Help Scout and Mixpanel help the team see what customers are asking for, which features they’re using, and where a follow-up conversation could help EasyBroker learn more.
Keeping customer expertise at the center of growth
After 14 years at EasyBroker, Vicky has a clear sense of what makes customer success valuable: people who know the product, understand real estate, and have the time to bring both kinds of expertise to their customers.
AI Answers helps preserve that as EasyBroker grows. Vicky can continue building the team with a long-term view, while the people already there spend more of their time helping customers become better at what they do.
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