How Beneficiary-First Medicare Strategies Drive Agent Revenue & Agency Growth

Putting Beneficiaries First Dramatically Improves Outcomes for Everyone

Using 1.756 million real-world scenarios, a 3% national sample of all 59.3 million Medicare Part C and D enrollees, this study shows that the current Medicare market is significantly misaligned. The model powering this study is continuously refined by real-world market data and evolving plan landscapes, making it more predictive and valuable with every cycle of analysis.

The Problem Today

• 90.6% of Medicare beneficiaries are currently on the wrong plan
• The average beneficiary is overpaying $3,193 per year out-of-pocket: 77.8% overpay by $1,000+, nearly half by $3,000+
• National annual overpayments exceed $189 billion
• Only 9.4% of beneficiaries are currently in their optimal plan

With AISmartBids Optimization + Automatic Annual Reshopping

• Year 1: 90.6% of beneficiaries are moved to their optimal plan
• Year 2+: 79.9% stay on their optimal plan with no action needed; the remaining 20.1% are automatically switched, keeping 100% alignment every year
• Average out-of-pocket overpayment drops 83.6% to just $525
• Zero-premium plan usage increases from 59% to 94%
• Market concentration (top 4 carriers) falls from 86.6% to 70.1% while still rewarding the best plans (Humana's share actually rises from 32% to 42.6%)
• Agent/agency revenue per client rises nearly 80% ($233 → $417), even with 5x more zero-commission placements
• Client retention improves from 84% to 95%
• Revenue per agent nearly triples and agency valuation increases ~2.7x

Why This Study Was Conducted

Picking a Medicare plan is too difficult. Industry reports consistently show that many beneficiaries are on plans that don't fit their needs and cost more than necessary. This study was designed to validate the extent of plan misalignment and measure how a data-driven decisioning tool like AISmartBids would change outcomes for beneficiaries, agents, and agencies.

The study examined five areas:

• Plan Mismatch — How many beneficiaries are on the wrong plan based on benefits and cost? Are they switching, and are they switching to the best option?
• Market Concentration Bias — Is the current concentration of carriers influencing plan selection in ways that don't serve beneficiaries?
• Cost Savings — Are beneficiaries paying too much out of pocket? How much could they save by switching?
• Agent/Agency Impact — How would optimized plan decisioning affect agent income and agency value?
• Plan Reshopping — How would automatic annual reshopping affect beneficiaries and agents over time?

We generated 3,513 synthetic users and modeled 500 data-supported, real-world scenarios for each, producing 1,756,500 total scenarios representing approximately 3% of the 59.3 million current Medicare Part C and D enrollees. Current plans were assigned using actual CMS enrollment distributions by carrier, contract, and geography. Recommended plans were generated using the AISmartBids engine with identical inputs, enabling a fair, side-by-side comparison between how plans are selected today and what a data-driven approach would suggest.

The analytical model underlying this study is a living system, continuously refined by real-world market data, shifting plan landscapes, regulatory changes, and the compounding record of beneficiary and agent choices over time. Each analysis cycle introduces new plan entries and exits, regional shifts, and observed enrollment outcomes that sharpen predictive accuracy and surface emerging patterns earlier.

What the Data Shows

The current Medicare Advantage market is highly concentrated among a few carriers and shows significant underutilization of zero-premium and zero-commission plans. When the AISmartBids optimization engine is applied, enrollment spreads across carriers, zero-premium utilization increases from 59% to 94%, and zero-commission placements increase nearly 5x. Even with that shift, long-term per-beneficiary revenue increases by nearly 80%. This reveals that the current market is driven more by habit and marketing than by economics.

The beneficiary impact is substantial. While 11.34% of beneficiaries typically switch plans in any given year, this study found that 90.6% are currently on a misaligned plan and should switch. That misalignment results in an average out-of-pocket overpayment of $3,193 annually, amounting to over $5.6 billion within this case study sample, scaling to more than $189 billion nationally. With the AISmartBids annual reshopping feature, average overpayment drops to $525 per beneficiary and plan alignment rises from 9.4% to 100%.

Most Beneficiaries Are on the Wrong Plan, and Paying Thousands More Than Necessary

While only 11.34% of beneficiaries switched plans during recent enrollment seasons, 90.6% were actually on a plan that didn't match their needs, costs, and preferences. An objective, data-driven approach to plan selection dramatically reduces unnecessary out-of-pocket spending, minimizes disruptive switching, and keeps coverage aligned with changing needs.

The Impact of Automatic Annual Reshopping

Proactive, automated plan monitoring is one of the most significant benefits for beneficiaries. With automatic reshopping, plan alignment moves from 9.4% to 100% and average out-of-pocket overpayments decrease 83.6% — from $3,193 to $525. That directly increases beneficiary satisfaction and loyalty, which reduces attrition for agents and agencies.

Data-Driven Decisions Reduce Concentration Bias and Reward the Best Plans

The top 4 carriers provide just 15.5% of all available Medicare plans. Yet CMS enrollment data shows they hold 86.6% of enrolled plans, a striking concentration driven by marketing, agent familiarity, and inertia rather than plan quality or fit.

This study's recommendations were based entirely on plan match, cost, and ratings, without regard to carrier marketing or broker preferences. Under those conditions, the top 4 carriers' combined enrollment share dropped from 86.6% to 70.1%, with enrollment shifting toward underrepresented carriers that offer better value.

Importantly, the best-performing carriers still benefit. Humana, one of the top 4 carriers, saw enrollment share actually increase from 32% to 42.6%, demonstrating their plans offer superior match, cost, and ratings compared to competitors. A merit-based system doesn't punish strong plans, it simply stops propping up weaker ones.

Doing What's Best for the Client Pays More

When the focus is on what's best for the client, zero-premium and zero-commission plan placements increase significantly, yet overall compensation increases as well. Matching clients to the right plans raises average revenue per client from $233 to $417.

Beyond revenue, agents can close in half the time. This reduced reshopping workload comes through automation, and agents can handle up to twice as many clients without burnout. The high-effort tasks that consume agent time, annual reshopping, plan comparison, client follow-up, are handled automatically.

Client-First Optimization Drives Higher Revenue, Stronger Retention, and Scalable Growth

Today, only 6.7% of placements are zero-compensation, but this study recommends nearly 30%. Even with that shift, long-term revenue per client increases from $233 to $417. Focusing on client-first strategies actually increases income and lifetime value, not the reverse.

The study shows retention rises from 84% to 95%, client lifetime value triples, revenue per agent nearly triples, and agency valuation increases by over 3.5x. Instead of requiring additional headcount to grow, AISmartBids enables existing teams to serve significantly more clients through technology leverage.

A Real-World Agency Profile

To illustrate the financial impact of AISmartBids, consider a typical owner-operated agency with a local focus.

Revenue Comparison

Efficiency and Value Gains (Year 2)