Shilo has introduced Signals, an AI-driven personality assessment tool designed to create DISC behavioral profiles for real estate agents using their call recordings, as announced by the company.
Based in Phoenix, this AI conversation analysis platform highlights a new feature that assesses weeks or even months of agent conversations. The objective is to uncover each agent’s fundamental motivators, apprehensions, conflict resolution styles, and social behaviors. By doing so, Signals offers personalized coaching recommendations that reflect how agents communicate, rather than relying on self-descriptive survey results.
Eliminating Bias and Adapting to Behavioral Shifts
Traditional DISC personality assessment tools often depend on self-reported questionnaires, which can introduce bias or become outdated as an agent’s behavior evolves. Shilo positions Signals as a means for teams to consistently evaluate communication styles in the background of daily operations, linking this analysis to coaching practices, script revisions, and lead follow-up techniques.
Each insight provided by Signals corresponds to specific calls and includes confidence scores. This offers team leaders a transparent audit trail that explains why the platform has categorized an agent in a certain DISC type or recommended a particular coaching strategy, according to the announcement.
Brokerages and teams invest significantly in coaching and training but often provide the same resources to all agents. Shilo references data from the National Association of Realtors (NAR), indicating that 87% of agents exit the industry within five years. Additionally, internal estimates suggest teams lose 40% to 60% of their lead investments due to inconsistent call execution.
Signals aims to enhance coaching accuracy by customizing recommendations based on how each agent processes information and acts. For real estate leaders, the potential impact of personality-aware coaching is an increase in conversion rates for existing leads, along with a decrease in turnover among agents who find generic training unhelpful.
A Comprehensive Analysis of Over 3 Million Calls
Operating on Shilo’s proprietary models, Signals is backed by what the company claims is over 21 years of accumulated conversation data, gathered from more than 7,000 real estate agents. To date, the platform has analyzed over 3 million calls, making it the largest collection of analyzed real estate dialogues in the industry.
“We prioritize data transparency at Shilo because it fundamentally establishes trust,” stated Justin Benson, CEO and co-founder of Shilo. “We don’t advocate for blind trust in AI, much like we wouldn’t recommend unrestricted trust in a person without historical context that ensures reliability. Each signal is assigned a confidence score and is supported by verifiable evidence drawn from prior conversations.”
The system effortlessly generates personality insights from calls that agents are already conducting through their existing phone systems and CRM integrations. This streamlining eliminates the need for separate assessments and reduces barriers to adoption among larger teams.
A Signals profile incorporates: DISC personality insights with spectrum bars for Dominance, Influence, Steadiness, and Conscientiousness; a comprehensive “About Me” narrative; a concise, easily understandable summary based on call patterns, core motivations and fears; as well as insights into conflict styles and social interactions that describe how an agent manages disagreements and fosters relationships. It also includes tailored coaching recommendations aligned with the agent’s DISC profile.
These recommendations are crafted to be specific and contextual rather than generic. For instance, Shilo provides an example where the platform advises an SC-profiled agent to adapt their communication with high-D or high-I clients by prioritizing a direct approach to listings, postponing process details until later in the conversation.
Dynamic Updates as Agents Make More Calls
As agents continue to make calls, Signals refreshes profiles and confidence levels, presenting new suggestions as behavioral patterns evolve. This creates a dynamic personality and coaching layer for managers, complementing existing call metrics, such as talk time, contact rates, and appointment-setting rates.
For teams in real estate and mortgage, the quality of coaching frequently determines success in converting online leads. While many conversation analytics platforms have been focused on script adherence and keyword tracking, Shilo’s venture into personality insights reflects a broader trend of utilizing AI to not only analyze the content of calls but also the individual delivering them and their manner of communication.
By linking personality insights to verifiable call data, Signals endeavors to provide team leaders with a framework for making decisions about which agents should be on calls, who should prioritize in-person consultations, and how to modify scripts for different communication styles. In an environment characterized by tighter lead budgets and increased scrutiny on agent performance, tools that align coaching with behavior are poised to influence hiring, allocation, and training strategies.
Shilo’s extensive platform evaluates calls on a 1-to-5-star scale, offers per-call coaching with script suggestions, generates insights at both the individual and organizational levels, automates CRM updates, and crafts AI role-playing scenarios based on actual conversations. Current integrations include Follow Up Boss, Sierra Interactive, BoldTrail, Lofty, CINC, SureSend, and Bonzo, along with an API-only option for enterprises seeking custom models.
Editor’s note: This article was generated using HousingWire Automation and reviewed by a HousingWire editor before publication. The system facilitates the conversion of company announcements and industry data into news articles that align with HousingWire’s style.
