Are patients or potential patients getting the experience they need from your website? Over the past decade, healthcare websites have grown increasingly important to the healthcare process. This shift has increased the burden of website developers to deliver an accessible and functional website that capitalizes on new technologies and meets customer needs.
A significant aspect of the customer experience revolves around search functionality. Both patient-facing websites and member portals should be aligned to ensure patients can find exactly what they’re looking for.
Healthcare websites are full of valuable and useful information, but patients often have a narrow focus while browsing. Whether they’re looking for educational information or trying to identify the proper provider, a more modern search experience is essential to improving the patient experience.
Consider What Patients Want
Speed and relevance are the two most important factors patients consider when searching a healthcare website. Imagine if search results could be personalized. Better search results could significantly reduce angry or confused inbound calls and solidify your website and organization as a preferred information source.
If patients can’t find what they want or need on a healthcare website, they almost always look elsewhere in frustration. How can new technologies benefit website development and functionality in this regard?
What Is Machine Learning?
Machine learning is a term that gets thrown around a lot, but most people still don’t understand this new technology. A subset of artificial intelligence, machine learning studies algorithms and data to recognize patterns and make predictions.
How, exactly, can healthcare websites make use of this technology? Machine learning uses data from website visits to make predictions and decisions that can be implemented without manual intervention. If a website visitor submits a support ticket, for example, it’s a clear indication that the page or pages they visited did not answer their question or solve their problem.
If visitors are leaving a webpage after just one minute when it should take 10 minutes to read, it likely means there’s an issue with the content. Perhaps it’s too technical or just not useful.
A machine learning system understands context. If certain users behaved similarly and found similar information to be relevant and important, it can then recommend the same information to users in the same boat.
Machine Learning and Intelligent Search
So, how exactly does machine learning make search intelligent? If a user searches for certain keywords and selects the fifth search result, it’s a sign that he finds that information to be most relevant. Each action performed by a user becomes data that is used to assess the relevance of a healthcare website’s content. Visiting pages, downloading content, engaging through online chats, submitting support tickets, and watching videos are all accounted for. These behaviors are captured and combined with search statistics to determine intent.
When a website’s search function is backed by machine learning, all of this data can be leveraged to automatically self-learn and improve search relevance over time. This automatic fine-tuning will yield better, more relevant search results and improve the average experience of patients and potential patients.
Without machine learning and intelligent search, it’s up to administrators to assess performance and update search rankings. While this can be done, it’s a lot more work and less accurate. If admins make an update based on last week or last month’s data, it’s already old and may no longer be useful or relevant. With machine learning, enterprise search doesn’t have to be manual or complex.
Though machine learning has been around for a while, the cloud has finally made it affordable. Cloud-based intelligent search can be hosted and managed by a vendor and scaled as a website grows.
Take advantage of machine learning and begin leveraging your company’s knowledge. Failing to do so can cause patients and potential patients to move to a competitor that can deliver the personalized and highly relevant information they want.