- Enterprises should consider the digital-first customer experience as a central pillar of their transformation strategies building on the work of omnichannel.
- Artificial intelligence (AI) and machine learning (ML) tools can unlock greater value, reduce costs, and improve the customer journey.
The internet and smartphone have driven a phenomenal pace of change in the way that customers interact with businesses since 2008. Multichannel evolved to accommodate the new channels of contact such as instant messaging, SMS, social media, and mobile apps that have become available to customers alongside voice.
While multichannel enabled these media, it left them disconnected and isolated from one another. The rise of omnichannel sought to integrate all contact media and allow customers and contact center agents to switch seamlessly between them. However, the experience is often far from smooth.
Too often when a customer moves from a conversation with a chatbot to communicating with a live agent, they are forced to repeat themselves and essentially start the process all over again. This is both frustrating for the customer and inefficient. What is worse for both the customer and the agent is that the agent often does not have full sight of previous interactions the customer has had with the business – whether that is a previous conversation with a contact center agent or salesperson, or using the website or mobile help either for transactions or self-service customer support.
GlobalData’s conversations with businesses in 2022 have highlighted the importance, in uncertain economic times, for businesses to maximize the value of every customer and to reduce costs. Remedying inefficiencies in customer contact solutions is one of the best ways for enterprises to score highly on both fronts. To achieve this, enterprises should consider moving beyond omnichannel and toward a digital-first customer experience (DFCX) methodology.
Where omnichannel focused on means of communication, DFCX looks first at data – specifically about recording, collating, and processing data on all of a customer’s interactions with a business. Enterprises must expand their horizons when considering customer contact beyond the contact center and consider the whole panoply of possible customer engagement scenarios (i.e., every time the customer has used the mobile app, browsed the website, called the contact center, or spoken to sales).
If this task seems daunting or unachievable, enterprises should be aware that technology solutions are there to help. CRM tools already exist to help enterprises gather customer data in a centralized way, and enterprises should ensure that this happens across all customer-facing segments of the business. Where more help is emerging is in the field of AI and ML.
AI and ML will play a role in various ways in the most effective DFCX solutions. For example, by processing large volumes of customer data to understand patterns of customer behavior and to understand what conclusions can be drawn and what actions can be taken. Collating this data and using AI can improve automated self-service options by helping predict customer needs at the point of contact and facilitating more successful interactions between chatbots/interactive voice response solutions.
The AI also helps when a customer speaks to a human agent. There is a balance between giving the agent no information and too much. AI can help highlight the most important information to human agents and also make recommendations either for solutions to a problem or the most appropriate service or product.
DXCS does not discard the work done to achieve omnichannel, but it can add the next layer of intelligence to make the most of that investment.