How Capable is AI in Medical Billing Marketing when it comes to Strategy?
Artificial intelligence, especially large language models and generative AI, is making waves in many fields, especially in marketing which depends heavily on language and generating content. But can medical billing marketing AI truly excel in the specialized and complex realm of strategy? Here, we explore how AI performs in crafting marketing positioning and differentiation strategies for medical billing companies by running a test and comparing it to humans. In this article we’ll share the results which will surprise you.
Testing AI in Medical Billing Marketing – Positioning and Differentiation
In a test for a client in the medical billing industry, we used generative AI platforms like OpenAI and Gemini to generate a marketing positioning statement. We fed the AI multiple pages of detailed information—essentially the same data we use internally to craft positioning statements. Surprisingly, the AI generated a lengthy, 196-word essay.
This output was puzzling, as marketing positioning statements should be concise and impactful, not essay-length. We tried refining the prompts, hoping the AI would improve, but the results remained far from what an effective positioning statement should look like.
Evaluating AI in Medical Billing Marketing – Generated Strategy Statements
Let’s examine the AI-generated positioning statement piece by piece. Here’s the best it created after several iterations: “[Client name] delivers exceptional revenue growth for [specialty] practices by optimizing collections through precise billing, proactive communication, and tailored financial strategies that maximize reimbursement.”
On the surface that sounds like a good marketing positioning and differentiation statement, but breaking down each element reveals significant issues:
- “Exceptional Revenue Growth” – This phrase implies that the billing company is bringing in new patient referrals, which isn’t the primary role of a medical billing company. It’s misleading at best.
- “Optimizing Collections” – This term is overused in medical billing and lacks specificity. “Optimized” is vague and could mean anything, making it ineffective in marketing.
- “Precise Billing” – Decades ago, billing companies focused on “accuracy” and “precision” in their branding, but clients today are not prioritizing these qualities as top marketing differentiators.
- “Proactive Communication” – While beneficial, “proactive communication” is unlikely to be a core selling point in billing services. It’s not among the top attributes clients seek.
- “Tailored Financial Strategies” – Medical billing companies are not wealth managers. Financial strategy is far outside the core function of revenue cycle management, making this phrase misleading at best or worse outright false.
- “Maximize Reimbursement” – This phrase is at best redundant, as it echoes “revenue growth” and “optimizing collections.” Overused language like this lacks originality and impact. Worse, it is terribly overused in medical billing marketing and lacks any impact because it is again vague.
In summary, nearly every part of the AI’s output was either confusing, misleading, or ineffective. Aside from potentially using the company name and “maximize reimbursement” (albeit overused), there was no value in the AI-generated content.
Why AI in Medical Billing Marketing Struggles
The disappointing output wasn’t due to inadequate inputs; we provided the same data that human strategists use to create strong positioning statements. The client even praised the human-generated positioning statement, highlighting its value in differentiating their brand.
The core issue lies in how large language models work. These models use word associations and probabilities to predict and generate responses. However, AI often pulls from a pool of commonly used (and often poor-quality) marketing language. In medical billing, where much of the existing marketing content is uninspired and not differentiated, AI models lack the ability to discern effective phrasing from generic, ineffective language.
The Role of AI in Improving Human-Generated Content
While AI couldn’t independently create a compelling positioning statement, it frequently proves useful in refining and iterating on a marketing copy. It can be great (with well-crafted prompts) at generating ideas and iterations on taglines and other types of copy. However, when we input our draft into an AI model, it was essentially useless and did not provide any value. It essentially tried to regress to the mean, which as noted before is not high quality or differentiated.
For now, AI can support but not replace human insight in this domain. As generative models improve, there may come a time when AI can play a larger role in the marketing strategy for medical billing. But for now, human expertise remains essential.
Conclusion: Current Limitations for AI in Medical Billing Marketing
In conclusion, AI alone cannot yet create effective marketing strategy like positioning or differentiation statements for medical billing companies. However, AI can enhance human-generated content, often making it a valuable tool in the refinement stage. While the future may bring more advanced AI tools that can perform more complex marketing tasks, for now, human creativity and strategic thinking are irreplaceable in crafting impactful medical billing marketing strategies.
