Client Case Study: How PrimeStreet Tripled Response Rates By Integrating Twilio Flex and AI

PrimeStreet Doubles Response Rates By Integrating Twilio Flex and AI

The Background

PrimeStreet, a high-growth real estate matching service, combines innovative technology and the human touch to help buyers and sellers connect with real estate professionals based on their price range and geographic area.

The Challenge

In 2023, the company identified an opportunity to leverage new AI capabilities to boost prospect response rates to its primarily email-based nurture and re-engagement sequences. In partnership with Terazo, the AI-driven campaign deployed sent more than 6,000 AI-generated SMS messages to nearly 5,000 inactive leads—resulting in a 2X higher re-engagement response rate compared to past campaigns. This pivot from email re-engagement to SMS text re-engagement was an exciting new chapter in PrimeStreet’s technology roadmap with Terazo. What’s more, the solution used few human resources since it ran on a Terazo-generated application leveraging Open AI’s GPT-4 model.

Our Approach

Identifying Appropriate AI Integrations with Twilio Flex

Terazo—a digital engineering consultancy specializing in Twilio implementations—had already migrated PrimeStreet to the Flex platform from a competitive call center solution to unlock new omnichannel marketing capabilities. In December 2023, Terazo conducted an AI workshop with PrimeStreet to identify specific pathways to integrate AI into the company’s re-engagement marketing campaigns.

During this work session, Terazo’s delivery team proposed multiple ideas on how AI could be incorporated into PrimeStreet’s campaigns. While the company was eager to leverage cutting-edge AI technologies, it was also committed to adopting them safely, securely, and respectfully to its customers and prospects.

Ultimately, PrimeStreet selected a hybrid model proposed by Terazo that would extract information from prospect conversations in Flex and other channels using traditional methods, mine them for potential causes of disengagement, and isolate customer segments based on these factors. Then, AI would be used to look at prospects’ message history and craft appropriate responses that could be pushed out via SMS. Any newly-engaged prospects that resulted from the AI-generated messages would go back into Flex for a direct response from a human agent.

Terazo implemented this new solution by the end of January 2024—just in time for the busy spring real estate season. Terazo and PrimeStreet deployed the revenue-generating solution in about 6 short weeks.

Technologies & Services Utilized

Twilio Flex

Twilio SMS

The Results

Increasing Prospect Engagement with AI and Flex

Before implementing Terazo’s AI-driven solution, PrimeStreet’s prospect re-engagement campaigns largely consisted of templated messages sent roughly once per month after prospects reached the end of their predefined nurture paths.

Through the thoughtful implementation of AI, PrimeStreet can now engage more prospects in an active, customized way without placing undue burden on their marketing team or call center team members. Their campaign results clearly prove the value of integrating AI into Twilio Flex and set the stage for future AI use case expansion.