The customer is a healthcare and insurance market leader, ranked in the top five (5) on Fortune Magazine’s list of the World’s Most Admired Companies in Health Care: Insurance and Managed Care. Currently providing coverage for upwards of 20MM Americans, they are the third largest health insurance provider in the United States, with a portfolio that includes primary and specialty healthcare plans.
The contact center is the lynchpin in the direct line of revenue for this insurance provider. The company was attempting to adequately address the market opportunity for in-home health and wellbeing assessments, but was facing service failures stemming from inconsistencies in agent performance rooted in an inability to overcome objections within the initial scheduling call. In the initial days of the COVID-19 pandemic, agents were unable to consistently or confidently address patients’ fears about care providers entering their homes, the differences between in-home visits and primary care visits, how primary care physicians would access patient data, and what COVID precautions would be in place for each visit.
Relying on outdated agent software – and using static scripts that couldn’t react or adapt to each patient’s personal concerns – agents were not able to overcome obstacles in each conversation with appropriate rebuttals.
The insurance company knew their static agent scripts failed to generate consistent results. No matter how much time and training they invested into their call centers, agents could not achieve the same conversion results, consistently. The performance gap was a symptom of the platform. In a desperate attempt to improve their numbers, low-performing agents would experiment with ad-hoc messaging and techniques. While their intentions were good, the results were not – creating inconsistent customer experiences from one agent to the next.
Additionally, the static scripts in place for objection handling were not speciﬁc to the unique situations encountered by each customer. The scripts failed to account for situational nuances, intricacies, or details, even when those details were provided by the customer. What the insurer needed was a more intelligent agent support tool that could produce customized engagements and better results.
Patients are the most important customers. Making each human interaction more effective, while personalizing care delivery and customer experience at scale, is critical to preserving the insurance provider’s legacy. Deploying XSELL made it possible for them to humanize their healthcare experience delivery for millions of Americans, while providing the support their agents needed.
After unsuccessful attempts to deploy other AI tools, and with so much at stake, the Fortune 50 insurer worked with XSELL to improve its call center situation. The XSELL solution’s ability to analyze and prescribe the necessary rebuttals to drive conversion was identified as the most critical component in the insurance provider’s success.
XSELL integrated its real-time agent coaching solution into the company’s Five9 telephony system to support each call. The XSELL solution combines machine learning, artiﬁcial intelligence, and human authenticity to support natural and effective interactions – giving the insurer a cutting-edge competitive advantage by drawing on their own best practices to map a path to success.
The XSELL real-time solution also provided each agent with proven:
The suggested strategies are those used by the insurer’s top-performing agents. The XSELL solution empowers each agent to perform like the best agent in every moment of opportunity. It ensures that conversations feel unique and tailored to the customer, by responding to their speciﬁc words and needs.
Agents using XSELL real-time coaching increased in-home appointments by 52% and delivered a 9x ROI in Year One with a 26% reduction in the number of calls it took to book an appointment. More signiﬁcantly, the XSELL solution continues to learn, continually improving the rate at which conversations lead to appointments. The XSELL agents also reduced objections, completing more actions, more quickly, than non-users.
What if every patient had dealt with your single best health advocate? What would that mean for your top line – and your bottom line?
The XSELL human-in-the-loop advantage uses actual agents for every interaction. It’s not that bots aren’t intelligent. They’re great at running algorithms. But they still can’t understand satire, exaggeration, and other human subtleties. XSELL works differently. They start with your archived messages and use AI to identify successful strategies. Then, they apply a human touch. Once perfected, their “royal roads” serve up the best responses to agents — in real-time — and always during significant moments of opportunity. XSELL provides optimal responses during every moment of interaction, not via a verbatim script.
Companies can’t outperform the competition with contact center bots only — bots are a future-state technology that fails to deliver today. XSELL communicates with nuance and empathy. Patients, and agents, deserve the kind of natural interactions that bots can’t understand. Real people are the XSELL Technologies difference and your contact centers’ best opportunity.
XSELL Technologies – Know Us By Our Results
XSELL integrated real-time agent coaching into the company’s Five9 telephony system to support each call. The solution combines machine learning, artiﬁcial intelligence, and human authenticity to support natural and effective interactions – giving the insurer a cutting-edge competitive advantage.
"There's such a difference in getting a member to agree to an appointment with the right language. This is what XSELL is to us. It's putting the best language that top converters have used in the past to persuade a member to book an appointment in front of every agent. As XSELL learns from Top Performers' language that's most successful and then adds it to the new script, it impacts the call center and the agents significantly. We are seeing a large gap between call center agents and (XSELL) call center agents. The end result is higher conversion."