As another year of digital disruption comes to an end, what would be the key pillars of customer experience in 2024?
The end of another pivotal year of digital disruption has profoundly transformed customer expectations. Amidst rising costs and technological shifts, brands are urged to not just keep up, but to anticipate and redefine. It is no longer enough to offer a product or service; it’s the complete experience that counts.
Customers want deeper engagement that goes beyond passive transactions. Personalized experiences that match evolving priorities, and higher levels of transparency have become fundamental, yet critical, business differentiators. To navigate these changes, businesses need to step up and ground their technology in trust and personalization.
Personalization at the heart of customer engagement
Personalization is a tenet of modern customer engagement. Research shows that 85% of consumers value the experience a company provides as much as its products and services. When done well, personalization can unlock long-lasting customer relationships and loyalty. And yet, two-thirds still feel that companies are treating them as a mere number, rather than a unique individual. In the search for better experiences, customers are not afraid to switch brands if needed.
Most businesses have what they need to step up – the data. But how can they maximize the potential of this data to come out on top in this race of customer engagement?
This is where the magic of innovation shines. Over the year, we have seen the evolution of generative AI capabilities. Today, companies use generative AI to scale customer service and personalization, and identify patterns in customer behavior and preferences. Compliment this with breakthrough innovations like conversational AI, and we are in a position to deliver truly personalized experiences.
Conversational AI is fundamentally reshaping business workflows, enabling employees to focus on what’s most important – the customer experience. With conversational AI assistant tools such as Einstein Copilot, employees can create and receive content by simply asking questions in natural language, while ensuring that results are grounded in trusted data.
Its customizable nature also proves to be a game-changer, allowing it to be built and used for the unique specifications of any business. For example, marketers can create personalized landing pages based on a customer’s browsing and buying preferences. In financial services, an advisor can analyze a client’s spending and savings history to offer personalized coaching and tailored plans.
The trust imperative
These innovations have become crucial pieces of the puzzle in providing personalization at scale, while improving productivity and the overall customer experience for businesses and employees.
However, as these tools are increasingly adopted for day-to-day operations, businesses must ensure ethical and safety standards. After all, to treat customers as individuals rather than numbers, we cannot forget a core tenet of any relationship – trust.
To put this into perspective, Salesforce research reveals that 66% of Singapore customers feel advances in AI make it more important that companies are trustworthy. 79% are concerned about companies using AI unethically.
Even as trust is quickly becoming the fabric of our growing digital economy, 63% of respondents in our research have not received training from employers on how to use generative AI ethically or safely.
How can businesses combat this to employ AI strategies grounded in trust?
This starts with using trusted and secure platforms and applications, and complimenting them with training for workers to ethically and safely use the technology.
To establish a trusted AI infrastructure, businesses must ensure the technology is developed responsibly and ethically, and grounded in a foundation of secure customer data. This provides accurate and validated content that employees, business leaders, and customers can trust. Coupled with innovations like Salesforce Einstein Trust Layer, we can assure customers of their data security and ownership.
AI is only as good as the data it’s trained on. Making sure that AI models are grounded in trusted data also lays the foundation to securely train these models over time, and develop new AI use cases.
Even with secure infrastructure, employees will still require the oversight and skillsets to use them effectively. Structured and targeted training systems and tools need to be made available for all employees to use AI safely and ethically. Such investments go beyond safeguarding AI usage, and will instill confidence and trust within employees. This trust will invariably cascade down to customers, regulators and other stakeholders.
As the tides of customer expectations continue to shift, we can no longer afford to go with the flow when it comes to customer engagement. Technologies such as AI hold immense potential for businesses to keep up with changing needs and preferences. Success will favor companies who can demonstrate a thoughtful approach to technology, grounded in trust and improved customer experience.
