Can you tell when someone is honest? Interested? Committed?
This number affects:
What we know:
Having analyzed tens of thousands of calls associated with specific outcomes, (e.g., customer promised and in fact made payment), we apply our award-winning technology to pick up on subtle voice patterns in real-time from the audio signal of a call. Using a state-of-the-art deep learning approach, we have built powerful predictive models linking the rich set of behavioral properties tracked during each interaction, with the customer’s underlying propensity to pay and an agent’s overall performance.
We read subconscious vocal signals (voice tells) to reveal agent incitement and customer satisfaction, factors that help us identify the behavioral patterns of both the Customer and Agent. For example, when a call contains a promise to pay or to buy, by analyzing agent and customer voices for acoustic cues (such as intonation, and interaction patterns like speaker’s dominance), our platform measures if this promise will translate into a payment with 90% precision. Accurate predictions of payments (kept promises) leads to better revenue estimates, improved call scheduling, and improved RoI.
CUSTOMER SUCCESS STORY
We analyzed 2M calls from First Call’s contact center. 15% of those calls were marked by the agent as promise-to-pay calls. We automatically analyzed the recordings to determine the credibility of these promises. Our deep learning engine was able to detect with 90% precision the calls that actually led to payments, as promised.
We improved targeted follow-up calling that lead to 5% revenue increase with 2% cost savings.
Behavioral Signals algorithms process human emotions and behaviors, deciphering data to give you credible actionable information. We help you add real numbers and measurable value to your company.