Are your web analytics telling you what you need to know?

Posted by Brad Veach Tuesday, October 24, 2017

Optimize patient self-scheduling with web analytics

Metrics are important. And when it comes to providing a service, conversions are one of the most crucial metrics to understand. Analyzing your data, understanding your results and comparing them against a benchmark for success is a critical process to growth. Analytics provide you with essential information needed to understand the funnel of activity by your consumer, what’s working and what isn’t. With new tools becoming available for healthcare like digital care coordination, the need to track consumers’ web traffic is even more important. With online scheduling in place, healthcare websites can actively track conversions and see how many visits turn into booked appointments. To look at this the right way, healthcare organizations need to take a page out of the retailers’ web analytics book.

In the world of ecommerce, it’s commonplace to know conversion rates like how many customers are adding products to their carts (which by the way is on average 8%) and how many are actually completing a sale (1-2% on average). Healthcare companies that are embracing the new wave of consumerism and enabling digital care coordination need to take a similar approach to observing web traffic patterns.

Do you know what your conversion rate is?

Akin to any kind of online purchase, one of the most crucial metrics we have available to monitor are conversions. MyHealthDirect focuses on providing solutions that improve patient experience, clinical outcomes and financial results. Part of doing this is providing our clients with not just a tailored patient self-scheduling solution, but one with built-in web analytics, customized to their needs.

Picking up where standard analytics drop-off, ours provide the ability to do A/B testing, see the precise funnel of booking activity (and when, specifically, patients drop off during the process), understand conversion rates, and tie together data sets with information such as lead times or wait times.

Web Analytics Funnel

*Delivered by region, department, location, and provider

Looking at the data science example above we can observe several things.

  • Decision Support: For starters, we can see how many people engaged in the “decision support” process of being guided to the right provider (asked a series of qualifying questions to bring up only the appropriate appointment inventory based on their answers). This is the initiation of the booking process (i.e. where a consumer would be brought after clicking a “Schedule Now” button on your website or something similar).
  • Filled Out Contact Form: To the right, we can see how many folks opted to have the provider contact them to book the appointment, instead of continuing the online booking process.
  • Search and Calendar: Here we are able to see how many people completed the decision support sequence and actually viewed search and calendar results.
  • Patient Information: Next, we see how many visitors are entering their patient info (essentially, they’ve selected the slot they want and are locking it in).
  • Booked: Finally, we see how many visitors fully completed the booking process.

In this specific instance of 343 visitors that began the booking process, 18.5% went all the way and scheduled an appointment. That’s a solid conversion rate. But it gets even better. By analyzing the steps in the process, we’ve helped customers increase this conversion rate to 30% - now that is astounding, especially when compared to retailers who average 1-2%. Simple things like adjusting what questions you ask or changing what inventory your providers make available can dramatically increase the success of your online scheduling program.

The results of better analytics? An average 30% conversion rate.

The results speak for themselves. Our clients are regularly achieving a 30 percent conversion rate when it comes to patient self-scheduling. The real difference maker is that our customers are using a digital care coordination platform with an analytics platform customized specifically for tracking online appointment scheduling traffic. This platform gives them the unique ability to carefully create processes that meet the needs of their consumers in searching for care, receiving decision support and ultimately finding the right appointment. Combine this with the ability to compare metrics with other data sets, like lead times and wait times, and you have truly unmatched value at your fingertips. When it comes to opportunities to optimize your programs, the sky’s the limit.

Interested in learning how customer-centered, data-driven patient self-scheduling solutions can improve both clinical and financial results for you? Download our free guide on Redefining Patient Access.

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Topics: Self-Scheduling, Data Analytics, Decision Support, Online Scheduling, Digital Care Coordination

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