10 Customer Experience Trends to Master by 2030 — How Many Are on Your Checklist?

Arvind Mehrotra
11 min readApr 5, 2024


In my years of guiding and working with top brands, one area of focus has held steady — customer experience. Navigating the evolving landscape of customer experience demands foresight and adaptability to emerging trends that will define their interactions with your brand in the years ahead.

I look forward to 2025–2030, as several critical customer experience trends are poised to reshape how businesses engage and connect with their audience. Here are the Ten trends on my radar:

1. Hyper-personalisation

In the digital age, consumers crave personalised experiences that speak directly to their preferences and needs. Hyper-personalisation goes beyond mere customisation; it’s about crafting tailored interactions that anticipate and fulfil customer expectations at every touchpoint.

Here’s how, for example, in the insurance industry:

- Policy Issuance: GenAI is streamlining the very foundation of insurance — policy issuance. With automated document verification and rapid risk assessment powered by Natural Language Processing and Machine Learning, GenAI delivers tailored policies within moments. For instance, Lemonade, a pioneering Insurtech, has leveraged this potential to offer real-time policy issuance. Artivatic.ai is an Indian insurtech platform that uses GenAI for advanced data analytics, self-learning, policy issuance, underwriting, claims processing, etc.

- Underwriting: GenAI infuses underwriting with a fresh perspective. It analyses diverse data sources, such as social media, and integrates inputs from IoT devices to create a comprehensive risk profile. Global reinsurance giant Gen Re exemplifies this approach.

- Marketing: GenAI’s sophisticated data analytics and sentiment analysis allow insurers to design campaigns that resonate with individual preferences. Progressive Insurance stands out in this domain, capturing customer attention with AI-driven personalised marketing tactics. Bajaj Allianz General Insurance, one of India’s leading private general insurers, is pioneering in enhancing customer experience and transparency by launching its innovative “Insurance Samjho” Gen AI-powered bot. This revolutionary next-generation AI technology bot is to simplify insurance complexities, empower customers with knowledge about their policies with easy-to-understand information, and simultaneously bridge the information gap in the insurance industry and increase insurance awareness in India.

By leveraging advanced data analytics, AI-driven insights, and predictive modelling, you can deliver personalised experiences that resonate deeply with your audience, fostering stronger connections and driving long-term loyalty.

2. Immersive technologies

The rise of immersive technologies, including VR, AR, and MR, presents unparalleled opportunities to create captivating brand experiences that transcend traditional boundaries. Imagine transporting your customers into virtual worlds where they can explore your products and services in unprecedented detail or offering interactive AR experiences that seamlessly blend the physical and digital realms.

- Immersive Learning: GenAI has the potential to revolutionise the learning landscape. With GenAI, we’ll be able to tap into rich data troves and drive on-the-fly, personalised learning experiences.

- Workforce Impact: GenAI and immersive experiences powered by avatars and machine learning tools are poised to help companies address workforce shortages by reinventing the employee experience. GenAI boosts employee performance and increases productivity and creative problem-solving by 50%.

- Personalised Interactions: GenAI can make every interaction count by creating products and services tailored to customers’ needs. For instance, Coca-Cola uses an image generator and language model tools to allow anyone who visits the company’s Create Real Magic site to add a personal flourish to Christmas greetings by creating their Coke-themed X-Mas cards.

- Enhanced Customer Experience: GenAI can engage in multi-turn question-and-answer dialogue with customers, understanding intent, sentiment, and context. It captures and summarises conversational insights to facilitate faster virtual-to-live agent handoffs in delivering bespoke experiences at scale.

According to a recent IDC report, 85% of A2000 retailers in the Asia Pacific (excluding Japan) will test/invest in GenAI to enhance product data, customer support, and customer experience initiatives through 2027. This indicates that AI and GenAI have nudged the retail sector to gear up for the coming years, where retailers will leverage technology to enhance operational efficiency, customer engagement, and data management. The Asia Pacific generative AI market size estimation is at USD 4.25 billion in 2023 and will grow at a compounded annual growth rate (CAGR) of 37.5% from 2024 to 2030. The increasing internet usage, technological advancement, and government initiatives drive market growth.

By embracing immersive technologies, you can captivate your audience’s imagination, differentiate your brand, and elevate the customer journey to new heights of engagement and excitement.

3. Voice-activated interfaces

Voice-activated interfaces represent the next frontier in customer engagement, offering intuitive and hands-free interactions that simplify and streamline the customer experience. With the proliferation of voice-enabled devices and platforms, consumers expect seamless voice-driven interactions that mirror natural conversation patterns. GenAI-powered voice bots can respond to open-ended questions more humanistically, improving the overall customer experience. Capgemini developed a virtual retail assistant named “Casey” to accept orders and drive the order-to-cash process for partner stores. Casey is voice-activated and GenAI-enabled.

Some other features can be :

- Enhanced Conversations: GenAI enables voice bots to engage in multi-turn conversations, referring to earlier parts of the dialogue and building context.

- Efficient Document Processing: GenAI can improve a wide range of document processing, making cognitive and semantic content searches more efficient and effect

Investing in voice-activated interfaces powered by sophisticated natural language processing and voice recognition technologies empowers customers to interact with your brand effortlessly, driving convenience, accessibility, and satisfaction.

4. Emotional intelligence

The human touch is essential in fostering meaningful customer connections in an increasingly digital world. Emotional intelligence lies at the heart of effective customer engagement, enabling your frontline staff to empathise, actively listen, and respond to customer needs with compassion and understanding.

By cultivating emotional intelligence within your organisation, you can forge deeper bonds with customers, instil trust and confidence, and differentiate your brand in a crowded marketplace.

5. Sustainability and social responsibility

Today’s consumers are increasingly conscious of their purchasing decisions’ social and environmental impact. As sustainability and social responsibility become integral to the brand identity, businesses must align their practices with meaningful causes and ethical standards.

By championing sustainability initiatives, supporting social causes, and transparently communicating your commitment to responsible business practices, you can build trust, foster goodwill, and inspire loyalty among socially conscious consumers.

6. Predictive customer service

Anticipating and addressing customer needs before they arise is the hallmark of predictive customer service. By harnessing the power of machine learning algorithms and predictive analytics, you can proactively identify patterns, trends, and potential pain points in the customer journey.

Generative AI (GenAI) has a transformative impact on predictive customer service, given are a few ideas:

- Strengthen Data Capabilities: To maximise GenAI’s impact on customer interactions, it’s recommended to invest in strategies, capabilities, and architecture to process structured and unstructured data. It includes deriving insights not just from every conversation but from every customer touchpoint. Exotel’s Voicebot, powered by GenAI, delivers exceptional customer support experiences. It uses cutting-edge AI technologies like Natural Language Understanding (NLU), Processing (NLP), Automatic Speech Recognition (ASR), Text-to-speech (TTS), and machine learning.

- Enterprise-wide Strategy: Adopting an enterprise-wide strategy can help in hyper-personalisation. Different departments of an organisation can reach out to customers with various products. ServiceNow’s digital technology (DT) team has benefited from applying GenAI use cases internally through their Now on Now program. They’re seeing tangible results from using their GenAI solution 120 days in. GenAI is saving valuable time for employees, customers, and agents. It accelerates resolution times and minimises direct human intervention. It enables users to find solutions swiftly using AI search, AI conversations, and AI interventions, leading to higher self-service rates.

- Predict Future Customer Behaviors: GenAI takes personalisation beyond reactive adjustments and actions, enabling businesses to predict and generate content tailored to anticipate future customer behaviours and preferences. B2B Technology Company: One B2B technology company uses GenAI as a predictive, proactive customer care agent. When an issue is detected, the system automatically triggers GenAI-enabled outreach to the customer, in many cases, before the individual even realises there is a problem.

From personalised product recommendations to proactive support interventions, predictive customer service enables you to exceed customer expectations, enhance satisfaction, and drive advocacy through proactive engagement and support.

7. Seamless omnichannel experiences

Customers expect seamless and consistent experiences across all channels and touchpoints in today’s interconnected world. A seamless omnichannel experience ensures that customers can transition effortlessly between physical and digital interactions, maintaining continuity and coherence throughout their journey.

SmartKarrot is leveraging AI to deliver omnichannel marketing analysis in several ways. It delivers Predictive Analytics by leveraging vast customer data, and AI algorithms can analyse patterns and trends to predict customer behaviour and potential issues. It allows Customer Success teams to proactively address customer needs rather than reacting to problems after they arise.

Another way SmartKarrot allows personalisation at scale across multiple channels is through its ability to analyse customer data, which extends to creating personalised experiences at scale. Customer Success teams can utilise AI to tailor customer interactions, providing customised recommendations, content, and solutions. SmartKarrot also provides automation and efficiency by automating routine and time-consuming tasks, enabling Customer Success teams to allocate their resources more strategically. The AI engine of SmartKarrot gives teams real-time insights by analysing data quickly and identifying patterns. It allows quick identification of emerging trends, potential issues, and areas for improvement.

Lastly, SmartKarrot’s augmented intelligence feature blends artificial intelligence and automation to enhance outcomes, improve decision-making, and improve predictive insights. The core benefits of SmartKarrot’s augmented intelligence are that it drives improved decisions through a unique collaboration of human interaction and technology, simplifies actions, enhances capabilities to suggest solutions, and reduces the time spent on activities that can be non-productive.

By integrating channels, aligning messaging, and optimising touchpoints, you can deliver a unified brand experience that resonates with customers, fosters engagement and drives loyalty across the entire customer lifecycle.

8. Blockchain-powered trust

Blockchain technology offers unprecedented transparency, security, and trust in customer relationships. You can secure transactions, verify authenticity, and confidently protect sensitive data by leveraging blockchain’s immutable ledger and decentralised architecture.

From supply chain transparency to secure payments and identity verification, blockchain-powered solutions inspire trust, instil confidence, and reinforce the integrity of your brand in the eyes of customers and stakeholders alike.

9. AI-driven emotional analytics

Understanding and responding to customer emotions is vital to delivering exceptional experiences that resonate more deeply. AI-driven emotional analytics empowers you to decode and interpret emotional cues, sentiment signals, and behavioural patterns in customer interactions.

For example, in enhanced sentiment analysis, GenAI can interpret the text to identify hidden emotions and perceptions, which is known as sentiment analysis. This is beneficial for companies because it gives them insights into customer behaviour and improves customer experience. GenAI models can be trained on specific and vast datasets to improve accuracy, allowing them to pick up subtle linguistic concepts like irony, sarcasm, slang, etc. As a result, GenAI models can provide higher accuracy with sentiment analysis.

Higher Efficiency and Scalability: GenAI models analyse large volumes of text data in real-time, enabling quicker identification of trends and shifts in sentiment. They can be quickly scaled according to requirements and customised to fit the needs of any industry and sector. Bloomberg generates world-class performance by building generative AI tools that leverage internal data.

By leveraging emotional insights, you can personalise experiences, tailor communications, and anticipate needs with empathy and understanding, fostering stronger emotional connections and driving customer loyalty and advocacy.

10. Data privacy and ethical AI

Upholding the highest data privacy standards and ethical AI practices is paramount in building and maintaining customer trust. Customer Experience Management (CEM) will undergo significant changes in the next five years, particularly in integrating ethical or responsible AI.

Ethical AI consideration becomes real as more AI integrates into CEM; a growing focus will be on moral concerns, such as fairness, transparency, and privacy. Zendesk has developed ethical AI guidelines for customer experience, focusing on transparency, explainability, and informing customers when interacting with an AI chatbot.

Businesses must ensure that their use of AI is transparent and explainable, building customer trust. Salesforce considers it its responsibility to develop ethical AI and guide organisations on building a trusted AI capability that enhances customer experience and enables customer success.

Regulatory compliance concerning AI and data privacy regulations will evolve, and businesses must ensure that they adopt and comply. Pivony emphasises the ethical use of AI in customer experience, focusing on fairness, accountability, and privacy protection.

You can safeguard customer privacy and ensure the responsible use of data and AI technologies by prioritising transparency, consent, and data protection principles in your data handling practices. Demonstrating integrity, accountability, and respect for customer rights can strengthen trust, foster loyalty, and differentiate your brand in an increasingly data-driven world.

In Conclusion

As you embrace these transformative customer experience trends, remember that success lies in technological innovation, human connection, and ethical leadership. By prioritising customer-centricity, empathy, and integrity, you’ll meet your customers’ evolving needs and inspire loyalty, advocacy, and enduring relationships in the years ahead.

Customer experience is critical, and overreliance on machines can pose challenges. Striking a balance between machine learning and human oversight is essential. Here are some considerations:

Continuous Monitoring and Review:

- Machines: They can quickly process vast amounts of data but need more context and intuition.

- Humans: Monitoring machine performance, identifying anomalies, and adjusting models are crucial.

- Hybrid Approach: Combine automated monitoring with human intuition to catch issues early.

Deployment Approval:

- Machines: Deploy models automatically based on predefined criteria.

- Humans: Approve deployments after thorough evaluation, considering ethical, legal, and business implications.

- Collaboration: Involve domain experts, data scientists, and stakeholders in decision-making.

Verification through Audits:

- Machines: Generate predictions, but audits are necessary to ensure fairness, bias mitigation, and compliance.

- Humans: Conduct regular audits to assess model behaviour, identify biases, and validate outcomes.

- Transparency: Document model decisions and share insights with auditors.

Ethical Considerations:

- Machines: May unintentionally perpetuate biases or make harmful decisions.

- Humans: Responsible for ensuring fairness, transparency, and ethical use of AI.

- Education: Train teams on ethical AI practices and encourage responsible behaviour.

In summary, a collaborative approach that combines the strengths of machine learning and human judgment is essential for robust, customer-centric AI systems.

Are you eager to embrace the future of customer experience with strategic vision, purpose, and a relentless pursuit of excellence? Speak with me at Arvind@am-pmassociates.com.



Arvind Mehrotra

Board Advisor, Strategy, Culture Alignment and Technology Advisor