These days, robust search tools are essential to improving customer satisfaction. However, it can be challenging for healthcare providers to find the ideal solution for a digital search strategy due to the variety and intricacy of search solutions available.
The key to finding the optimal search solution is to focus on the preferences and behaviors of consumers as they interact with your digital offerings.
But monitoring the actions and interactions of patients and potential patients leads to a mountain of data for healthcare providers to review. These providers are learning that the better option is to find a search solution that responds to user data in real time. Through the use of artificial intelligence (AI), search tools can learn user behaviors and display more current or relevant information each and every time.
Relevance Is the Key
The first step to designing an effective and robust enterprise search solution is to focus on user-interface and general best practices like ease of use, attention to content clarity, and intuitive UI presentation.
Most healthcare providers already adhere to these standards, but this is just the starting line for developing a digital search experience. More needs to be done to ensure your enterprise search solution improves patient satisfaction, increases patient adoption and retention, and even improves outcomes.
To take a search solution to the next level, healthcare providers must focus on relevance. This can be done in several ways:
- Query suggestions powered by machine learning. This technology offers users suggestions as they type, speeding up the search process and helping them find relevant material.
- Automatic relevance tuning ensures the top search results are always as relevant as possible to patient queries.
- Content recommendations should also be used to display necessary or useful content to patients without them having to ask for it.
Non-verbal cues are a significant portion of communication for humans, but keyword-focused searches can’t pick up these cues. However, AI-powered enterprise search can bridge that gap and return more useful and relevant content by discerning intent from a combination of keywords and gathered information about user intent.
How can intent be determined? A user’s behavior, what they type as search queries, and other context can be compared to other users with similar behavior. Results are likely to be the same for similar users, so machine learning is capable of delivering more relevant information when patients perform searches.
The Benefits of Enterprise Search
When patients or prospective patients get the answers they need more quickly, everyone benefits. This is especially true if individuals are given personalized search results.
If potential patients aren’t able to find what they’re looking for on your website, they’ll find the information elsewhere. Enterprise search powered by AI will keep potential patients on your website and solidify your company’s position as a great source of information.
On the business side of things, robust enterprise search will reduce inbound call inquiries, freeing up employees to handle more important matters. Additionally, customer service can be improved by reviewing collected search information. When a provider understands how individuals interact with their digital platform, customer service representatives can assist patients better.