Conversely AI

How Conversational AI is Radically Changing Insurance Sales in 2023

By now you have heard a lot about conversational AI and large language models like ChatGPT, but do you know just how these AI models are radically changing the Medicare Advantage sales model going into 2023?

MAOs and third-party marketers can now use AI to understand human language, enhancing their ability to score calls for compliance and extract relevant data for meaningful follow-up in healthcare.

There are four ways that conversational AI can radically help MAOs and third-party marketers thrive in the months and years to come.

1) Reduce Insurance Compliance Risk

As an insurance agency or broker, it can be difficult to know if all the mandated compliances and confirmations needed from a customer have been. With so many calls or leads exchanging hands, how do you monitor and review agent compliance elements at scale to protect your brand?

Conversational AI is now making it possible to scan 100% of insurance sales conversations, tagging key insights, phrases, and required statements for compliance standpoint and then applying a compliance confidence level to each conversation automatically. Sophisticated systems monitor compliance elements using natural language processing, allowing the engine to find compliance intents through personable conversation instead of only through robotic keyword-based scripting.

Even more, some quality monitoring systems like Conversely AI, can further reduce compliance risk and turn your insights into action by processing aggregated data and instilling a closed-loop management process that acts on your risks and opportunities assigning tasks, tracking progress, and monitoring outcomes.

2) Automate Hyper Personalized Follow-up Campaigns

In 2023, personalization will change the game for customer experiences. In a study compiled by Salesforce, 58% of consumers say they’d switch to a provider that excels at personalizing experiences without compromising trust. But brands can no longer skate by with basic personalization attributes like name, address, and other relatively fixed attributes to move the needle. To maximize Medicare enrollments, companies need to shift their level of personalization to relate to the evolving content in which customers make their purchase decisions. This takes a deep understanding of customer needs, preferences, and past interactions. With the help of conversational AI, this next-level personalization or hyper-personalization can be achieved.

Hyper-Personalization is the most advanced way brands can tailor their marketing to individual customers. And now, thanks to predictive analytics, artificial intelligence (AI), and machine learning manifested through conversational data, businesses can make the shift and evolve new touchpoints that respond to a customer’s changing circumstances.

Hyper Personalized Marketing Can Help:

  • Maximize revenue: Empower your conversational data to create automated, relevant, and custom onboarding, nurturing, and retention campaigns so leads are always nurtured and cross-sell/retention opportunities are always activated.
  • Reduce cost per sale: Optimize your outreach strategies to maximize conversion outcomes.
  • Elevate the customer experience: Improve the customer experience throughout the customer journey, facilitating personalized virtual concierge services.

3) Optimize Your Sales Process

What sets your top performers apart from their peers? What words move the sales process forward? Which messages resonate with your buyers?

With AI technology, you don’t have to rely on trial and error to improve sales. Using real-time analysis and predictive lead scoring, AI technology can prompt agents on what action to take next.

AI-powered lead scoring technology compiles comprehensive data from multiple sources to uncover the best path to sale, including:

  • Channel permissions
  • Conversational data that validates the quality and intent level to buy of the lead
  • The price paid for the lead transfer
  • The campaign type that originated the lead
  • Intent scores based on conversation elements

Once you have these insights, you can treat segments of lead sources differently (e.g., different scripts for high-intent vs low-intent leads, etc.). Together, historical data can build prediction models for what to do next, enabling better sales practices and improving performance across the board.

4) Consistent Scalability Even During High Turnover

Today, employee attrition at call centers that focus on sales is extremely high. Since the start of COVID-19, the attrition rate for sales-based contact centers was just below 80%. With 11.4 million job openings and roughly 56 workers for every 100 job openings, finding and retaining skilled quality assurance and sales agents is a challenge. And even when you can find qualified candidates, the cost of replacing an employee is as much as 2x their annual salary.

With an AI solution, you can analyze each conversation for sales and compliance adherence to uncover insights into performance and identify exceptions so you can take immediate corrective action. This efficiency enables organizations to act more quickly to resolve red flags and mitigate risk during enrollment. In addition, a byproduct of these tools helps build employee confidence, mitigating attrition.

After a conversation is complete, scale your nurturing and retention strategies to reduce cost per sale and increase lifetime value with automated hyper-personalization campaigns that utilize your conversational data to personalize an ongoing engagement strategy. In what ways are you using AI in your business operations? To learn more about how Conversely AI is implementing conversational AI to improve business outcomes visit us at or email [email protected]

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