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3 Loyalty Retention Strategies for Your Subscription Service

Retaining loyal customers is pivotal to the success of any subscription-based service, as it’s important to keep customers subscribed and engaged with the service. While many businesses focus on acquiring new customers, it’s equally important to focus on retaining existing customers and increasing customer loyalty.

Subscription services provide customers the convenience of having products and services delivered to them regularly. In 2023, Subscription Cancellations are at an all-time high in the USA markets. With such a market sentiment, brands need to have a loyalty retention strategy in place. We have enlisted 3 Loyalty Retention Strategies for Your Subscription Service that can help you win your customers.

What is a Subscription Based Service Model?

A subscription-based service is a business model where customers pay a recurring fee to access a service or product. Subscriptions can be offered on monthly, yearly, or pay-as-you-go models. Subscription services can be offered as a one-time purchase or as an ongoing commitment. For example, YouTube Premium offers an ads-free experience on subscribing as a Premium user at their monthly or annual subscription rates. 

Why is Retaining Customers Important?

Keeping customers happy and engaged helps to maintain loyalty and increase the lifetime value of a customer. HubSpot Research found that, in cases of company error, 96% of survey respondents continue buying from a company they regularly purchased from if the company apologized and corrected the situation. Retaining customers helps to reduce the cost of acquiring new customers, as well as increasing revenue.

Apart from the recurring revenue that existing customers bring in, there are upsell and cross-sell benefits. As per a blog by Chargebee, the success rate of selling to current customers is 60-70%, while selling to a first-time customer is 5-20%.

Thus, in a market where customers are fairly risk-averse and want to minimize their spending, retaining existing customers is critical to the success of a service provider.

Types of Loyalty Retention Strategies

  • Rewards Programs

Rewards programs help companies retain customers by incentivizing them to continue using their services. According to Forbes Research, 79% of consumers say loyalty programs make them continue to engage with a brand. While 75% say that they are likely to make another purchase after receiving an incentive.

By taking a subscription, a customer takes up a premium loyalty program with the brand or company. If they receive reward points as a part of it, the same can be redeemed for future purchases.

Prominent brands such as Sephora, Amazon Prime & Starbucks leverage such programs to cultivate a loyal customer base.

For example, Mariott offers it loyalty program called Mariott Bonvoy Benefits which offers multiple benefits from the moment users sign up. Through its portal, users have a personalized journey designed to heighten their experience with Mariott, as well as avail the best of travel and hospitality offers.

  • Personalized Customer Experiences

According to Evergage, 99% of marketers say personalization helps advance customer relationships, with 78% claiming it has a “strong” or “extremely strong” impact. Personalization helps make a customer feel more valued, and at the same time, it enhances their productivity or experience by helping them cut across a vast superset of choices, narrowing it down to highlight relevant material or services.

Streaming giant Netflix provides its users with hyper-personalized content recommendations through a customized Home Page, a Shuffle feature, and Recommendation lists. This helps users to be more engaged with the content they watch, as they are provided options based on their watch history and persona.

As more users become cognizant of extended reality technologies, the usage of AR/VR to draw in more personalized customer experiences has also increased.

Mantra Labs helped a leading Luxury Home Decor brand design and develop their Augmented Reality experience to boost their in-app engagement.

  • Automated Retention Strategies

Digital technologies enable brands to stay closer to their users and provide contextual nudges which ensure that there is a high recall for the product or service provided.

As most brands will have relevant subscriber data, they can use this to share personalized emails, push notifications, and other automated messages that are tailored to the customer’s interests and preferences. These messages can be used to remind customers of upcoming subscription renewals, offer discounts or promotions, or provide helpful tips and advice.

Brands must also ensure that the renewal journey of their customers is seamless. Providing multiple payment options, and, options to save payment details for faster checkouts.

While auto-renewals are a convenient feature, brands should proactively notify users of pending renewals, and in case of a heavily underutilized subscription offer customized plans. Media giant Wall Street Journal makes it difficult for paid users to cancel their subscriptions, with a user having to call their Customer Care Center and manually record their request to cancel the subscription, as opposed to directly canceling it via a portal. While this might marginally reduce customer churn, customer satisfaction drops significantly.

Eventually, brands have to ensure there is a balance between revenue generation and customer experience for prolonged success.

Final Thoughts

Retaining customers is essential to the success of any business. And loyalty retention strategies can help to ensure customers remain engaged and continue to purchase products or services. As subscriptions cancellation hit an all-time high, brands need to make their offerings personalized to provide value for money to subscribers. As well as ensure there is a significant focus on creating a seamless customer journey to boost customer satisfaction across all segments.

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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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