National Real Estate Company Uses Stream Chat to Allow Agents to Communicate with Clients

About the “Real Estate Company”

This market-leading real estate company has agents and facilities all across the United States. As one of the largest real estate franchises in terms of sales volume, the number of agents, and units sold they also have one of the largest risks in terms of communication between agents and clients.

Challenge

Agents communicate with their clients in a number of ways: phone, in person, email and text. Whenever there’s a need to ensure communication is accurate, you should always “put it in writing”. That works great for email, but these days most agents text with their clients. When that happens the real estate company loses all visibility into what’s being said, what might be promised, and in the case of a dispute or even legal action, the content can’t be subpoenaed.

This real estate company needed a way to ensure they could gain access to every text between agents and clients, and also have the ability to head off potential issues before they grow out of hand.

Solution

Stream Chat was chosen to be the internal “glue” to tie texting conversations together between agents and clients. By connecting Stream Chat through a third party API driven SMS solution, the real estate company’s back end is able to monitor all communications happening from all of their agents.

The system is set up such that one party initiates a text, that text gets pulled into Stream Chat, which then is converted back into a text to the second party. This solution also allows the real estate company to tie in advanced AI to do sentiment analysis and alert internal staff when harmful, deceitful or otherwise damaging conversations to occur.

Also, because all of the messaging is stored within Stream Chat (unlimited retention), it can always be queried and brought forward as evidence of agreements, promised or other statements during the process.

Moving Forward

By using Stream Chat this leading real estate company was able to reduce risk, increase customer service and predict issues before they happen. Future iterations of the implementation will add the ability to do big data analysis across multiple conversations that will allow the AI to become even smarter, and by tying in bot services they will be able to automate some suggestions to their agents, automate setting up showing times and other common needs.

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