AI in the healthcare sector has proven to be a sparkling success for businesses and patients alike. It has bridged the gap between service providers and consumers and opened new avenues for revenue generation and customer behavior analysis.
Today, businesses are accumulating more data than ever before. Thanks to the rise of social media culture and businesses opening new channels for their customers to give feedback, companies have an almost unending amount of data to learn from. To this end, they are employing various AI and ML technologies like chatbots, Natural Language Processing (NLPs), etc. These AI technologies help businesses take the astonishing amount of unstructured customer data they have captured and harness valuable, actionable insights that can help them improve their services and internal business processes. Every sector today employs some form of AI, from healthcare to manufacturing, to help them deal with customer data.
Customer feedback is the cornerstone of any business’s success. Given the cut-throat nature of the business world, it is vital for businesses to know what their customers like and dislike about their offerings and mold them in a way that pleases their customers without becoming an additional burden on their business.
AIs have been incredibly successful in helping businesses become well-oiled machines so far. AI has allowed companies to become more productive, efficient, and environment-friendly. But one area where there is still some work to be done is on the customer support side of things. While chatbots and NLP engines are welcome additions, traditional AI tools have proven ineffective in figuring out customers’ sentiments and opinions toward products and services. And this is where AI-based sentiment analysis comes in.
Using sentiment analysis, businesses can perform Opinion Mining, which can help them figure out the general sentiment of different customer profiles towards their services. And perhaps nowhere is this technology more needed than in the healthcare sector.
In this blog post, we will learn more about sentiment analysis and how it helps the healthcare sector, its benefits, and the roadblocks.
- AI-based sentiment analysis allows healthcare providers to understand the subtleties behind customer feedback rather than simply looking for negative or positive keywords.
- Sentiment analysis tools have a staggering accuracy rate of 90%!
- On top of text-based feedback analysis, many companies are developing tools that analyze live customer support and service calls. They have shown a 30% hike in customer satisfaction and a 15% dip in customer-handle calls.
- Healthcare businesses can use sentiment analysis to provide better services to their patients by identifying the key areas in their services that need improvement and then coming up with evidence-based solutions.
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What is Sentiment Analysis?
Sentiment analysis is a much more complex method of analyzing customer opinions and sentiments towards a certain product or set of services using not just trigger words but long sentence fragments. AI-based sentiment analysis modules can grasp the tone of a sentence and deduce whether the overall feedback is negative, positive, or neutral.
Companies use various ways to get customer feedback, from online surveys to the comments sections of different social media platforms. But it is not always clear whether the criticism is objective or genuine, which makes it harder for companies to understand customer sentiment toward their products and services. But sentiment analysis makes that a problem of the past.
These modules can analyze a big chunk of unstructured data in-depth and deduce the overall customer opinions (this process is called Opinion Mining.) Using sentiment analysis, companies can understand their customers better, evaluate their needs, and improve to build a stronger brand image and customer relations.
Sentiment analysis studies not only studies text-based reviews from social media platforms and comment sections on various sites, but some companies are now developing tools that analyze customer service and support calls to improve their understanding of customer opinions towards their services. These tools have shown a 30% spike in customer satisfaction and a 15% decrease in call handle time.
How Can AI Sentiment Analysis Help Healthcare Businesses?
Most healthcare providers, such as hospitals and clinics, are always trying to improve their services. It is essential for them to fine-tune their offerings so that their patients can have the best experience possible. In the healthcare sector, a customer’s experience counts for a lot. If a hospital fails to provide adequate services to a patient who’s trusted them with his well-being, things can get dire and inflict irreparable damage to its reputation. So, learning what customers like and don’t like about their services is not only a way for healthcare providers to enhance their business but a way to survive.
AI sentiment analysis, therefore, is the need of the hour for healthcare businesses.
Sentiment analysis, at its core, is a way for businesses to find out the opinions of different groups of people buying a product or subscribing to a service. Therefore, the sentiment of a group of people towards a certain, whether good or bad, can truly help companies improve. AI-based sentiment analysis tools have an average accuracy rate of 90%, which makes them an essential tool in any business toolkit.
AI healthcare solutions are a big market nowadays; most hospitals employ at least one solution to help them run their business smoothly. That is why it is exceptionally convenient that AI sentiment analysis can be integrated with most healthcare software solutions like chatbots, Customer Data Platforms like Salesforce, Open Data Initiatives (ODIs), and Cloud Information Model (CIM).
How does AI-based Sentiment Analysis in Healthcare Work?
Sentiment analysis is a three-step process: Identify, extract, and analyze. Using various channels customer feedback data is collected in private or shared data repositories. Once the unstructured data is collected, the incredibly competent sentiment analysis gets to work and conducts opinion mining. It extracts the required data based on certain parameters and then analyzes it to draw conclusions.
Two key tools are often employed to automate the opinion mining process: Conversational AIs and Aspect-based Patient Sentiment Analysis.
A conversational AI combines chatbot technology with ML and NLP engines to enhance the patient support experience. These AIs can have human-sounding conversations with users with astonishing accuracy. When combined with conversational AIs, sentiment analysis can provide real-time deductions and problem resolutions, elevating the customer experience. Furthermore, sentiment analysis can help healthcare providers find out what services their patients have the most issues with, which services they like the most, and their overall opinion about their services. Using this data, healthcare providers can improve their services to a great degree.
When combined with AI applications in healthcare, aspect-based sentiment analysis can help businesses hone in on patient sentiments and opinions about a particular aspect of their services or products. This helps businesses get feedback about particular components or areas of their services and products. And by improving upon those aspects of their offerings, companies can improve customer sentiment towards the brand as a whole.
Top Benefits of Sentiment Analysis using AI in the Healthcare Sector
Sentiment analysis has many benefits for the healthcare sector. As we have seen in the above few sections, sentiment analysis is an incredibly complex process that can help businesses from various sectors improve their products by not simply targeting specific keywords with negative connotations in customer feedback but by actually studying longer sentences to understand the emotions behind that feedback. And healthcare sector is no different in that regard. Given below are some of the top benefits of using sentiment analysis in healthcare:
- AI in healthcare has been a great success. It has helped healthcare providers improve almost every aspect of their business model, customer-facing and internal. But by enhancing their AI and integrating sentiment analysis in their workflow, they can provide more patient-oriented healthcare services.
- Sentiment analysis also allows hospitals and clinics to analyze patient behavior and get actionable insights that they can use to improve their services.
- Sentiment analysis goes beyond simply finding what customers don’t like about your services. It allows you to change things, sure. But sentiment analysis is a continuous process; you can use it to see how patients and customers are reacting to the new changes. This way, sentiment analysis allows you to come up with solutions and gauge their effectiveness and course correct if the changes are not resonating with the patients.
- Based on customer preferences and history, sentiment analysis modules can recommend the right services to the patients.
- These modules provide efficient data scouring and filtering abilities and promote accurate evaluation of business strengths and weaknesses.
- Healthcare providers can use these insights to build better future strategies and plans. Furthermore, sentiment analysis offers enhanced patient satisfaction and improved patient customer retention.
Major Roadblocks for AI-based Sentiment Analysis in the Healthcare Sector
AI in healthcare has been a big success over the past few years. But AI adoption is not as easy as some would have you believe. And while things are getting easier every year, there are still some major roadblocks that healthcare businesses must be aware of going in.
- Most businesses find it very tough to deal with large volumes of unstructured data. Since customer feedback data is accumulated from various channels, it becomes very difficult for them to manage and keep it secure.
- Usually, there is a big communication gap between healthcare service providers and their customers, leading to misunderstandings. It is very common for businesses to read customer requirements wrongly and come up with a counterproductive service that ends up hurting the brand.
- Opinion mining requires a lot of top-shelf infrastructures to be effective. Furthermore, they need healthcare software development firms as a technology partner to build custom AIs and train them with their data. All of it can be a lot of overhead for a business that is already struggling.
- Modern technology implementations and adoptions go hand-in-hand with current processes and workflows. A lot of times, healthcare businesses suffer from outdated methods of doing things that contradict all the good AI applications in healthcare are doing.
- The lack of the necessary internal workforce or a technology partner is a big roadblock. Every ambitious and modern healthcare provider needs an AI development company to back them up technology-wise and help their sentiment analysis modules reach their full potential.
How Can Matellio Help Healthcare Businesses Implement AI-based Sentiment Analysis?
Equipped with infallible instincts that come with years of industry experience, Matellio helps healthcare businesses modernize their internal and customer-facing processes. As experienced healthcare software development companies, we excel at identifying business pain points and using the latest AI/ML technologies for problem resolution. We employ the Agile development methodology to keep our clients at the heart of our process.
AI experts at Matellio have proven skills in healthcare solution development that help businesses not only retain customers but also bring in new patients. We build impeccable customer service workflows by integrating AI-based chatbots fused with conversational AI that elevate customer experiences and improve revenues.
If you want to know more about our healthcare development services, please get in touch with us.
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