Conversely AI

How to Reduce Medicare Sales Cost Per Acquisition with Lead Scoring AI Technology

Every year, millions of potential Medicare leads are sent to MAO call centers, but many are unqualified. Without intelligence behind the lead and lead sources, buyers are paying for fraudulent and/or low-quality leads, causing a high cost per acquisition. Whether they’re already enrolled in a Medicare program, or have low intent to buy, every day, unqualified leads take up valuable time on the phone that agents could be spending with high-intent customers. In sales, every call and every minute counts. So being able to identify high-quality leads as they come in can not only save time but also save on costs per lead and acquisition. That’s where machine learning and AI technology come in. You don’t have a crystal ball to predict whether a lead will convert. But luckily, you don’t actually need one. AI technology can lower the cost per acquisition through predictive lead scoring and real-time insights extracted from sales conversations.
  • Qualify Medicare leads in real-time, so you only focus on high-intent calls
  • Uncover customer opportunities in seconds
  • Match leads with the right salesperson for the job
  • Develop personalized sales scripts optimized for conversion
  • Improve customer experience by anticipating needs
  • Optimize bidding parameters for higher rates of return on sales calls

How AI can level up your Medicare lead scoring

AI technology leverages the data you already have to make better sales decisions and identify your best leads—and the ones better left off the call list. Here’s how AI-powered lead scoring technology can help you lower costs while boosting conversions.

1.   Understand customer intent in real-time

Through machine learning, AI technology can review historical and current conversational sales data to deliver real-time insights on lead quality and nurturing—within seconds of picking up the phone. Determine if a potential customer has the intent to shop for a new Medicare plan at the beginning of the call so you can move the lead through the sales funnel appropriately. Many lead providers charge a fee per lead if the call lasts longer than an agreed-upon threshold. Being able to identify a lead’s intent right away can not only save valuable time but also reduces the cost per acquisition.

2.   Analyze your lead source performance

AI technology combs through your lead source data to detect patterns in performance. Use these insights to find out how effective your lead sourcing is, identify opportunities to improve, and compare your lead source performance to other industry competitors. With comprehensive performance insights into your lead aggregators, you can make better decisions about which partners you work with and what sources deliver the best leads.

3.   Optimize lead bidding parameters

Every call has a cost associated with it, which is typically determined in a lead auction. When deciding on what to bid, buyers have to estimate the value of the leads coming from the seller. Too often, these bids are based on overly-broad data and assumptions. But AI technology empowers buyers to dig deeper into lead aggregator data and performance to calculate bids that are more accurate, resulting in higher returns on investment. AI technology helps you optimize your Medicare lead bidding parameters to include additional, unique data points such as:
  • Comprehensive historical performance
  • Personalized consumer data points
  • Real-time analysis of customer intent
Together, these data points paint a more complete picture of your lead performance and enable buyers to bid accordingly.

4.   Use data to route calls to the ideal agent

When you understand your leads and the strengths and weaknesses of your salespeople, you can match leads to agents for better outcomes. With AI technology’s advanced ability to append zero-party and third-party data, you can route calls automatically to the ideal agent. The AI layers prediction models with demographic, behavioral, and psychographic clustering mechanisms to profile lead needs so you can more effectively match them with agents that can address them. The result: More effective sales conversations and higher conversion rates.

5.   Scale the performance of your best salespeople

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 intention 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.

Lower cost to acquisition with Conversely AI’s lead optimization solution

Understanding customer intent is at the center of good sales strategy. By tapping into your customer, sales, and lead data, Conversely AI analyzes and identifies customer intent in real-time, generating actionable insights that lower the cost to acquire at scale. Get end-to-end visibility into your sales and lead generation processes for better performance, better leads, and lower costs. Contact us today to learn more about reducing the CPA of your Medicare leads.

READ MORE: Top 3 Medicare Compliance Challenges (+ How to Solve Them Before AEP)

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