Five Trends Shaping the Digital Health Customer Experience

4 minutes, 38 seconds read

Published on Sep 30, 2020

The fast growth of the digital health industry in India due to COVID-19 has led to the reshaping of customer health experiences. Innovations like mobile healthcare apps, telehealth services, e-pharma services are witnessing higher adoption rates and transforming the digital health customer experience.

Lack of awareness regarding the use of mhealth apps, uncertainty about apps’ working efficiency, security issues, etc. were the root cause of its wavering development, prior to the pandemic. During lockdowns, nearly 67% of Indians felt comfortable receiving medical advice over calls and video sessions, according to a Royal Philips survey.

The healthcare industry has shifted towards a patient-centric model to deliver convenient and meaningful experiences from the patient’s home. Below are the top five trends that are shaping digital health customer experiences:

Customers are relying on mHealth apps

Mobile health apps in India have witnessed an increase in downloads due to changes in lifestyle, increased interest in fitness & wellness programs and to track & monitor a variety of health data — sleep patterns, calorie intake, physical activity, etc. Followed by the telehealth segment, the mHealth segment is expected to dominate the Indian market by reaching approximately USD 1.87 Bn by 2024.

Mobile health apps in India such as Practo, PharmEasy, 1mg, Medlife, cure.fit etc. allow customers to order healthy food, buy medicines with discounts, receive health tips and attend virtual doctor consultations by staying at home. Even though mHealth apps are general wellness related, the number of condition management apps are likely to increase with customer engagement. Moreover, the growth of the mHealth segment will ensure cost effective healthcare services that will prompt the consumers to use health apps. With the rise of mobile health apps, more benefits are likely to be incorporated such as in the case of health emergencies where an app can send the location of the needy to the hospital, thus saving ambulance drivers’ time in following directions.

Increase in Demand for Personalized Care

Customers have begun to feel empowered and valued through wearable devices and other digital health tools as it is enabling them to take control of their health. With electronic health records in hand, healthcare organizations are leveraging patients’ health records that are helping in optimizing the digital health customer experience. Predicting problems and providing solutions before they bother the patients has become the new model. This has paved the way for hyper personalization. By analyzing an individual’s DNA, it allows HCPs to monitor patients’ medication, provide health tips and helps them to diagnose diseases early. For instance, DNAfit offers genome-personalized health advice, workout plans, etc. that help customers in framing a daily routine. Apple Healthkit also functions in a similar fashion to personalize healthcare services as patient data is collected, compared and mined to result in a customized health experience.

Younger generation has more trust in tech companies

Around 32% of gen X and 43% of millennial are open to receive virtual healthcare, according to an Accenture survey. As the younger generation provides active feedback to the healthcare organizations, examining their behaviour can provide significant insights that might help mending the existing gaps between HCOs and customers. According to a recent Deloitte survey, empathy and reliability are the two factors that customers expect from healthcare providers. This shows that when customers are given the option to own their personal data related to health, healthcare organizations are more likely to attract customers. Considering how consumers are sensitive about their data, data interoperability is likely to help organizations in meeting consumer needs. In addition to this, increase in digital touchpoints are likely to multiply to meet diverse consumer needs.

Increased Demand for Value-added services

According to an Accenture survey, around 57% of customers are open to remote virtual care. This shows the increasing appreciation of real-time assistance and contactless healthcare. Healthcare providers are likely to produce more value-added services by enhancing patient engagement, data collection, digital health channels. Traditional ways of treatment will change when HCOs leverage patient data from technologies and smart devices. Expert advice of HCPs in developing value-added services will further assist in producing accurate solutions for patients. Consumer demand for value-added services shows the increasing expectations from the digital health industry that will transform the customer experiences, as the leading health organizations are likely to produce more digitally enabled health solutions. Post COVID-19 when people begin to socialize, the contactless health services will be useful in cases of health emergencies, or for old people who find it hard to travel.

Consumers are open to omnichannel virtual care

Be it buying of medicines, or keeping a regular check on health, the digital health tools such as mHealth apps, fitness trackers, etc have been adopted by consumers to satiate their healthcare needs. Openness to various digital health channels shows the strengthening of consumer trust. Recently Apple launched Apple Watch series 6 that allows users to take on-demand readings of blood oxygen level anytime. Its potential to give readings anytime and anywhere reflects customers’ increase in usage of digital health tools. Apart from tracking steps, fitness trackers also have advanced health features like, heart-rate monitors, SpO2 monitors, sleep tracking, etc. Web apps and chatbots are being used by healthcare organizations to assist people with health-related problems. Digital healthtech company Your.MD uses chatbot and web app to help customers get personalized health information. The future of the digital health industry is likely to witness an enhancement and increase in the number of access points. Increased acceptance of omnichannel will lead to optimization of customer engagement as HCOs will have more resources from where they can leverage patient data.

To know about how healthcare industry is bringing hospitals to a customer’s doorstep, watch our webinar on Digital Health Beyond COVID-19.

Know about our work in Digital Health and how we have helped clients such as Suraksha Diagnostics, Abbvie, Religare Health Insurance, and SBI Health Insurance build mobile and web applications improving their operational efficiency and customer experience.

Further Readings:

When we hear million-dollar AI mistakes, the first thought is: What could it be? Was it a massive investment in the wrong technology? Did a critical AI application go up in flames? Or was it an overhyped solution that failed to deliver on its promises? Spoiler alert: it’s often all of these—and more. From overlooked data science issues to misaligned business goals and poorly defined AI projects, failures are a mix of preventable errors.

Remember Blockbuster? They had multiple chances to embrace advanced technology like streaming but stuck to their old model, ignoring the shifting landscape. The result? Netflix became a giant while Blockbuster faded into history. AI failures follow a similar pattern—when businesses fail to adapt their processes, even the most innovative AI tools turn into liabilities. Gartner reports nearly 80% of AI projects fail, costing millions. How do companies, with all their resources and brainpower manage to bungle something as transformative as AI?

1. Investing Without a Clear Goal

Enterprises often treat artificial intelligence as a must-have accessory rather than a strategic tool. “If our competitors have it, we need it too!” they exclaim, rushing into adoption without asking why. The result? Expensive systems that yield no measurable business outcomes. Without aligning AI’s capabilities—like natural language processing or generative AI solutions—with goals such as boosting customer experience or driving operational efficiency, AI becomes just another line item in the budget.

2. Data Woes

AI is only as smart as the data it’s fed. Yet, many enterprises underestimate the importance of clean, structured, and unbiased data. They plug in inconsistent or incomplete data and expect groundbreaking insights. The result? AI models that churn out unreliable or even harmful outcomes.

Case in Point: A faulty ATS filtered for outdated AngularJS skills, rejecting all applicants, including a manager’s fake CV. The error, unnoticed due to blind reliance on AI, cost the HR team their jobs—a stark reminder that human oversight is critical in AI systems.

3. Underestimating the Human Element

AI might be powerful, but it does not replace human judgment. Whether it’s an AI assistant like Claude AI or OpenAI’s ChatGPT API, Enterprises often overlook the need for human oversight and fail to train employees on how to interact with AI systems. What you get is either blind trust in algorithms or complete resistance from employees, both of which spell trouble.

4. Stuck in Experiment Mode

AI adoption often stagnates when businesses fixate on piloting instead of scaling. Tools like DALL-E or MidJourney may excel in proofs of concept but lack enterprise-wide integration. This leaves companies in an endless cycle of testing AI applications, wasting resources without realizing full-scale business value.

5. Ignoring Change Management

Transitioning to AI technology is as much about organizational culture as it is about deploying AI models. Mismanagement, such as overlooking ethical AI considerations or failing to explain AI’s impact on roles, leads to resistance. Whether it’s a small chatbot AI tool or full-scale AI automation, fostering employee buy-in is critical.

How to Avoid These Pitfalls

Start with Strategy: Define clear objectives for adopting artificial intelligence programs.
Invest in Data: Build a robust data infrastructure. Clean, unbiased, and relevant data is the foundation of any successful AI initiative.
Prioritize Education and Oversight: Train teams to work with AI and establish clear guidelines for human-AI collaboration.
Think Big, but Scale Smart: Start with pilots but plan to expand AI in finance, healthcare, operations or other areas from day one.
Focus on Change Management: Communicate the value of tools like AI robots or AI-driven insights to teams at all levels.

Graph of AI adoption across different countries

Mantra Labs is Your AI Partner for Success

At Mantra Labs, we don’t just offer AI solutions—we provide a comprehensive, end-to-end strategy to help businesses adopt the complex process of AI implementation. While implementing AI can lead to transformative outcomes, it’s not a one-size-fits-all solution. True success lies in aligning the right technology with your unique business needs, and that’s where we excel. Whether you’re leveraging AI in healthcare with tools like poly AI or exploring AI trading platforms, we craft custom solutions tailored to your needs.

By addressing challenges like biased AI algorithms or misaligned AI strategies, we ensure you sidestep costly pitfalls. Our approach not only simplifies AI adoption but transforms it into a competitive advantage. Ready to avoid the million-dollar mistake and unlock AI’s full potential? Let’s make it happen—together.