Building an AI-powered chatbot that can make a sale

As we enter the second half of 2024, many retailers – from digital natives, to multi-channel retailers that have a digital presence – will be looking to gear up for various shopping festivals and dates. These include Singles’ day, Cyber Monday and End of Year festivities, just to name a few. These festivities present a critical opportunity for merchants to showcase their offerings online to a vast consumer audience. However, competition amongst retailers is fierce, particularly in Asia with many businesses leveraging dynamic marketing tactics such as interactive campaigns, live streaming, and social media promotion to entice and engage new customers.

In leveraging the scalability of digital and social channels, many retailers have turned to chatbots – but with the misconception that chatbots can only handle basic customer service functions. However, as AI continues its exponential evolution, especially in natural language processing (NLP), can AI-powered chatbots really drive sales? And if so, how should they be deployed in coordination with human agents?

The rise of AI-powered chatbots

AI-driven customer service chatbots have revolutionised customer experience at every stage of the sales funnel. These chatbots provide 24/7 support, personalised interactions, and efficient problem-solving abilities, such as answering queries, processing orders, customising offers, and managing returns. Chatbots can handle a large number of customer inquiries simultaneously without sacrificing service quality, which is particularly advantageous for small business owners.

A survey by MIT Technology Review revealed that nearly 90% of businesses reported measurable improvements in the speed of resolving complaints. These improvements in customer satisfaction subsequently enhance revenue performance and customer lifetime value. According to Verint’s 2023 State of Digital Customer Experience report, 31% of consumers have higher customer service expectations than the previous year, and 69% have ceased doing business with a company due to a single poor customer experience.

As e-commerce merchants increasingly implement AI-driven customer service technologies, maintaining a consistent and genuine brand voice across customer touchpoints has become more critical. Generative AI models, such as large language models (LLMs), have transformed how chatbots can be trained to mirror a brand's unique personality and voice. By incorporating brand-specific guidelines, tone, and language, brands can develop chatbots that seamlessly embody their identity, ensuring a cohesive and authentic customer experience across all digital channels. This approach also helps avoid inappropriate language or content, upholding a level of professionalism and trustworthiness.

For instance, H&M's generative AI chatbot on their website can reduce response times by up to 70% compared to human agents. Euromonitor International’s customer experience report found that 56.2% of Chinese consumers used voice assistants in 2023 whilst making purchases. The chatbot assists shoppers in searching for specific products, answers FAQs, and helps with orders, providing a more straightforward and satisfying experience for customers whilst significantly easing the burden on the customer service team.

Maximising efficiency with next-gen chatbots

Leveraging chatbots to enhance customer experience is crucial in today’s environment. Customer engagement has evolved dramatically in recent years, with interaction volumes increasing and customer expectations soaring. Meanwhile, brands are striving to do more with less to meet rising customer expectations and deliver exceptional experiences.

A key element in addressing the CX-cost equation is scaling interactions without significantly increasing budgets or reducing the quality of customer engagements. The Verint study indicates that 45% of highly confident respondents currently share work between human employees and bots, and 72% of highly confident respondents reported that using chatbots and messaging channels has been extremely effective over the past two years.

Steps to creating an effective AI chatbot for customer service

When developing an AI chatbot for customer service, several key steps ensure its effectiveness:

• Define the Objective: The primary goal should be to efficiently resolve customer inquiries whilst reducing workload. Brands should analyse common customer intents to identify areas where automation can have the most impact. Considering interactions from the perspective of pre- or post-sales customer service can also be valuable in designing the chatbot.
   
• Train with Quality Data: Collect valuable behavioral data from customer and agent interactions across various channels, as well as surveys and other feedback. For example, the Verint Intent Discovery Bot uses advanced AI to process customer data from multiple channels, enabling it to understand customer queries accurately and help intelligent virtual assistants (IVAs) provide better responses in the future.
   
• Utilise Data and Analytics: Once operational, use data and analytics, such as the number of conversations, average response time, user engagement, and conversation completion rates, for optimisation. Establish a systematic feedback process to measure performance, intent recognition, and advice effectiveness. This ongoing analysis and optimisation process ensures the chatbot gains deeper customer insights and continually improves to deliver optimal customer service.
   
• Understanding where human agents value-add: Whilst AI technology continues to become increasingly advanced, there will always be times where a human agent will be needed. This is especially so for high-value transactions, high-value customers or in managing complex requests. In this sense, AI chatbots can be used to manage high-volume, low-complexity tasks – freeing up human support agents to manage the lower-volume, but higher complexity requests. What will be essential is demarcating the triggers for human agents to come in.

Leveraging advanced chatbots in the e-commerce landscape

Whilst older chatbots were typically used for post-sales or general inquiries, advanced AI-powered chatbots now have the potential to transform the customer experience in e-commerce. They can shift chatbots from being cost centers to becoming revenue generators. In a competitive market, brands and e-commerce merchants leveraging advanced AI technologies can ensure round-the-clock availability, personalised interactions, and efficient query resolution, leading to higher customer satisfaction and loyalty. Embracing advanced chatbots offers a significant opportunity for e-commerce businesses to stay ahead in the rapidly evolving digital marketplace.