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CX 2021: How will 5G impact the customer experience future

8 minutes read

5G, the most anticipated wireless network technology, is touted to alter the way people go about their daily lives at home and work. Its USP lies in being a lot faster with a capability to handle more connected devices than the existing 4G LTE network. The fastest 5G networks might be at least 10 times faster than 4G LTE, according to wireless industry trade group GSMA. 

5G signals run over new radio frequencies, needing radios and other equipment on cell towers to be updated. A 5G network can be built using three methods depending on the type of assets of the wireless carrier: low-band network that covers a wide area but is only about 20% faster than 4G; high-band network that boasts of superfast speeds but they don’t travel well, especially through hard surfaces; and mid-band network which balances both speed and coverage. 

Industry trade group GSMA estimates that by the year 2025, the number of 5G connections will reach 1.4 billion – 15 percent of the global total. Additionally, global IoT connections will triple to 25 billion by 2025, while global IoT revenue will quadruple to $1.1 trillion, according to this report published by GSMA. 

Image Source: www.speedtest.net 

How will 5G impact customer experience

Image Source: tmforum.org

The increased reliability, performance, and efficiency of the new spectrum will come as a boon while, at the same time, raise the bar for customer expectations. The intertwining of technology with our daily lives could also mean the proliferation of other technologies, including the Internet of Things (IoT), Augmented and Virtual Reality, Big Data, and Cloud Computing. 

Consumers have regularly cited reliability as their biggest gripe with 4G networks. Over 4 out of 10 (43%) consumers say the internet on their mobile device “cuts in and out sometimes/is not always strong,” according to a PwC survey titled, The Promise of 5G: Consumers Are Intrigued, But Will They Pay? 

According to Deloitte, India’s digital economy will exceed USD 1 trillion by 2025 as a result of increased smartphone usage, rapid internet penetration, and the advancement of mobile broadband and data connectivity. 5G, on the other hand, is likely to be the key catalyst of this expansion.

Video options, however, go beyond content consumption unto live support, too. For consumer-facing companies, live video support will open doors to better customer service, a crucial aspect of a good customer experience. A 5,000-person survey done by Oracle found that 75% of its respondents recognize the value and efficiency of voice and video chat. They also look forward to first-call resolutions.

Even for agents providing email support, a quick video explaining steps looks like a more efficient way to give a resolution instead of emails with a step-by-step guide, an aspect that companies can consider for seamless processes. 

The GSM Association, an industry organization representing mobile network operators around the world, says the number of IoT connections worldwide will grow manifold between 2019 and 2025, to over 25 billion.

AR/VR capabilities and 5G

5G’s advent is a likely measure to “revolutionize” tech, especially through AR and VR. The high speed and low latency of 5G might imply that processing power could be moved to the cloud thereby allowing for more widespread use of VR/AR technology.

AR/VR technologies powered by high-speed 5G could help boost interest in newer concepts like virtual stores and the use of AR to experience products in their homes, or makeup on one’s face, and more. The combination of high speed and minimal lag is perfect for both VR and AR, which has a lot in store for the gaming community too. According to Nielsen’s study Augmented Retail: The New Consumer Reality released in 2019, many people are willing to use VR/AR to check out products.

That said, true VR/AR growth from 5G is difficult to predict since it also depends on the pace of customer and brand adoption. Nevertheless, its use in customer experiences will be interesting to watch in the coming years.

Big data processing power and 5G 

AI and big data analytics are currently in use to identify customer patterns in order to personalize CX. 5G’s capabilities are likely to raise the bar on the volume of data companies collect and increase the pace at which AI can process it. 

Faster speeds and lower latency lend themselves to an influx as they prepare for the next wave of automation and AI-backed technologies. Businesses will begin relying on mobile networks more frequently than before while streamlining core operations.

5G latency is expected to be faster than human visual processing, thus making it possible to control devices remotely effectively, in (almost) real-time. 

Insurance and 5G

Image Source: www.capgemini.com 

Insurance agencies rely on network carriers to share data for selling policies. With larger mounds of data widely available through 5G, agencies will be at an advantage to leverage more data without having to host or own it themselves. This means greater efficiency to navigate through data in a simpler manner.

The Internet of Things (IoT) has seemingly benefitted the auto insurance industry the most. The data is easier to generate, which includes the policyholder’s car details, mileage, speed, and overall usage of the car depending on each drive. 

https://www.youtube.com/watch?v=n5wkY3gQYiU

With IoT, a policyholder’s car isn’t the only thing that could help generate data. In case of a home fire, an oven could be used to collect data for requisite claim information. Likewise, a drone could share accurate location data. 

Overall, agriculture, manufacturing, logistics, financial services will all benefit from lower latency, high speeds, thus ensuring an immersive experience for all. 

Dogan Kaleli, CEO at Stere.io, Founder at Nion, wrote in ‘Why 5G is a Major Game-changer for the #Insurance Industry?‘ that 5G along with revolutionary technologies will mark the beginning of the 4th industrial revolution or the flywheel effect.

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Conversational UI in Healthcare: Enhancing Patient Interaction with Chatbots

As healthcare becomes more patient-centric, the demand for efficient and personalized care continues to grow. One of the key technologies that have gained traction in this domain is Conversational UI (CUI) — a user interface where interactions occur through natural language, often with the help of chatbots. For developers, building a robust CUI in healthcare requires a balance of technical proficiency, understanding of the healthcare landscape, and empathy toward patient needs. Let’s explore how CUI can improve patient interactions through chatbots and what developers should consider during implementation.

Why Conversational UI is Gaining Popularity in Healthcare

From scheduling appointments to answering medical queries, healthcare chatbots have become vital tools for enhancing patient engagement and streamlining healthcare workflows. Conversational UIs enable these chatbots to interact with patients naturally, making them accessible even to non-tech-savvy users. By incorporating AI and NLP (Natural Language Processing), chatbots can now simulate human-like conversations, ensuring patients receive timely, relevant responses. 

Image credit: https://www.analytixlabs.co.in/blog/ai-chatbots-in-healthcare/ 

Key Areas Where Chatbots Are Revolutionizing Healthcare

  1. Appointment Scheduling and Reminders – Chatbots can automatically schedule appointments based on patient availability and send reminders before the visit, reducing no-show rates. For developers, this feature requires integration with hospital management systems (HMS) and calendar APIs. The challenge lies in ensuring secure and real-time data transfer while adhering to healthcare compliance standards like HIPAA.
  1. Medical Query Resolution– Chatbots equipped with NLP can answer common patient questions related to symptoms, medications, and treatment plans. This reduces the burden on healthcare providers, allowing them to focus on more critical tasks. Developers working on this feature need to consider integrating medical databases, such as SNOMED CT or ICD-10, for accurate and up-to-date information.
  1. Patient Monitoring and Follow-ups – Post-discharge, chatbots can monitor a patient’s condition by regularly asking for health updates (e.g., vital signs or medication adherence). Developers can integrate IoT devices, such as wearable health monitors, with chatbot platforms to collect real-time data, providing healthcare professionals with actionable insights.
  1. Mental Health Support – Chatbots have shown promise in offering mental health support by providing patients with an outlet to discuss their feelings and receive advice. Building these chatbots involves training them on therapeutic conversational frameworks like Cognitive Behavioral Therapy (CBT), ensuring they offer relevant advice while recognizing when a human intervention is required.

Key Considerations for Developers

1. Natural Language Processing (NLP) and AI Training

NLP plays a pivotal role in enabling chatbots to understand and process patient queries effectively. Developers must focus on the following:

Training Data: Start by gathering extensive datasets that include real-life medical queries and patient conversations. This ensures that the chatbot can recognize various intents and respond appropriately.

Multi-language Support: Healthcare is global, so building multi-lingual capabilities is critical. Using tools like Google’s BERT or Microsoft’s Turing-NLG models can help chatbots understand context in different languages.

Contextual Understanding: The chatbot must not just respond to individual queries but also maintain the context across the conversation. Developers can use contextual models that preserve the state of the conversation, ensuring personalized patient interactions.

2. Security and Compliance

Healthcare chatbots handle sensitive patient information, making security a top priority. Developers must ensure compliance with regulations such as HIPAA (Health Insurance Portability and Accountability Act) in the U.S. and GDPR (General Data Protection Regulation) in Europe. Key practices include:

  • Data Encryption: All communication between the chatbot and the server must be encrypted using protocols like TLS (Transport Layer Security).
  • Authentication Mechanisms: Implement two-factor authentication (2FA) to verify patient identity, especially for sensitive tasks like accessing medical records.
  • Anonymization: To avoid accidental data breaches, ensure that the chatbot anonymizes data where possible.

3. Seamless Integration with EHR Systems

For chatbots to be truly effective in healthcare, they must integrate seamlessly with Electronic Health Record (EHR) systems. This requires a deep understanding of healthcare APIs like FHIR (Fast Healthcare Interoperability Resources) or HL7. Developers should aim to:

  • Enable Real-time Updates: Ensure that chatbot interactions (e.g., new appointment schedules, and symptom checks) are instantly reflected in the patient’s EHR.
  • Avoid Data Silos: Ensure that all systems (EHR, chatbot, scheduling system) can communicate with each other, eliminating data silos that can lead to fragmented patient information.

4. Scalability and Performance Optimization

In healthcare, downtime can be critical. Developers need to ensure that chatbots are scalable and capable of handling thousands of patient interactions simultaneously. Using cloud-based platforms (AWS, Google Cloud) that offer auto-scaling capabilities can help. Additionally, performance optimization can be achieved by:

  • Caching Responses: Store frequently used responses (such as FAQs) in memory to speed up interaction times.
  • Load Balancing: Implement load balancers to distribute incoming queries across servers, ensuring no single server is overwhelmed.

Tools and Platforms for Building Healthcare Chatbots

Several tools and platforms can aid developers in building healthcare chatbots with conversational UIs:

  1. Dialogflow (Google): Offers pre-built healthcare intents and integrates with Google Cloud’s healthcare APIs.
  2. Microsoft Bot Framework: A scalable platform that integrates with Azure services and offers AI-driven insights.
  3. Rasa: An open-source NLP tool that provides flexibility in creating highly customized healthcare bots.

Conclusion

Conversational UI in healthcare is transforming patient care by offering real-time, scalable, and personalized interactions through chatbots. However, for developers, building these systems goes beyond programming chatbots — it involves understanding the unique challenges of healthcare, from regulatory compliance to seamless integration with hospital systems. By focusing on NLP capabilities, ensuring security and privacy, and integrating with existing healthcare infrastructure, developers can create chatbots that not only enhance patient interaction but also alleviate the burden on healthcare providers.

References

  1. NLP in Healthcare: Opportunities and Challenges
  2. HIPAA Compliance for Chatbots

About the Author:

Shristi is a creative professional with a passion for visual storytelling. She recently transitioned from the world of video and motion graphics to the exciting field of product design at Mantra Labs. When she’s not designing, she enjoys watching movies, traveling, and sharing her experiences through vlogs.

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