Achieving an excellent customer experience and reputation is difficult enough in any business. Healthcare is a special challenge—and it’s even harder if your company runs multiple brands or sites. For marketing managers, reaching NPS benchmarks is a huge struggle with remote teams who have unique operations and cultures.

But there’s a way to overcome this challenge and unlock the growth that NPS evangelists claim will follow from a good score. In this post, we’ll explain how one key emerging technology has the ability to boost NPS for all locations simultaneously. It comes down to using AI to turn patient data into hyperlocal insights.

What is NPS?

NPS is a popular metric in a variety of fields. It’s used to gauge customer loyalty and satisfaction. NPS is calculated by asking one simple question: “On a scale of 0-10, how likely are you to recommend our services to friends and family?” For more details, download our NPS explainer.

What is NPS?

Net Promoter Score® is a proven loyalty and satisfaction metric that is calculated by asking one simple question: “On a scale of 0 – 10, how likely are you to recommend our services to friends or family?”

The tricky part comes when calculating NPS for service providers with multiple sites. An overall brand NPS—one that doesn’t differentiate between each brand location—offers limited value. It doesn’t tell you what’s happening on the ground, and it certainly doesn’t help you decide where to focus your efforts or what tactics to use. The real value comes from drilling down to the NPS for each location.

Implementing a truly personal touch at scale isn’t easy. But this drill-down approach to NPS empowers you to do just that.

Now, if you work in healthcare, take the challenges of a multi-unit business and multiply them by ten. Even with all the marketing technology we enjoy today (such as social media, e-mail marketing, and online patient portals), generating leads in healthcare can be a major hurdle. Tons of marketing dollars are wasted on promoting urgent care centers, dentistry offices, and other healthcare businesses.

That makes NPS all the more valuable. If you can leverage your existing clients to generate word-of-mouth marketing, then your marketing is more personal, more powerful, and more cost-effective.

What is AI?

Put simply, AI is technology that mimics the human brain’s capacity to make decisions, spot trends, and adapt to (or learn from) these experiences. This last capability is known as machine learning. It allows an AI system to change its own algorithm.

In short, with machine learning, AI systems can teach themselves. They get smarter over time—improving continuously without the need for human training.

AI is used to build systems that can handle all kinds of everyday tasks. These systems are especially good at taking over cognitive work that is repetitive in nature.

How is AI used in healthcare?

The role of AI in healthcare is on the rise, with the technology being very successful in imaging and diagnostics. AI has been able to support radiology, for example, by detecting cancer and help emergency departments triage cases more effectively. Overall, 54% of healthcare professionals are expecting widespread AI adoption by 2023.

AI also holds great potential value for healthcare marketing, patient experience, and NPS. It provides the ability to mine a continuous stream of patient feedback and make actionable insights accessible to a broader swathe of a care provider’s team. In fact, that’s Calibrater’s mission: we make it possible for 100% of your employees to learn from 100% of your patient feedback, every day.

That’s a huge step forward! That means patients’ perspectives are actually being heard, whoever they are and whatever their medical issue. This AI-aided listening also helps instill a greater sense of trust and community among patients and care providers.

Can anyone learn to use AI?

Some healthcare AI applications require training, while others are designed so that anyone can use them.

AI is currently being deployed as automated symptom checkers, for example, which would require a certain amount of training. That’s because knowing why the AI came to the conclusion it did can be a matter of life or death.

On the other hand, AIs are also being deployed to handle repetitive operational and administrative tasks (a chatbot, for example). This application would not require the administrative staff to have training in AI systems.

Calibrater Health is an example of a system developed to rely on AI without requiring any AI expertise on the part of the user. Calibrater’s survey suite was designed for growing healthcare businesses, and no customization or intensive training is needed. Businesses can expect actionable data to fuel marketing, physician engagement, and patient experience on Day 1.

Schedule a demo today to learn how to incorporate AI into your healthcare business!

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