AI-based chatbots in customer service and their effects on user compliance Electronic Markets
In 2016, Starbucks changed their rewards system from a visits-based program to a spend-based program. As part of the new offer system, Starbucks was able to move from pushing 30 variations of email offers every few weeks to over 400,000 highly personalized variants per week. These more personalized interactions increased customer engagement and drove up sales. It’s also allowed the company to have deeper research into the popularity of products, insight into how different locations are performing and labor optimization for anticipated customer flows. The increasing sophistication of AI like OpenAI’s ChatGPT has led many customer service leaders and online entrepreneurs to wonder how these tools can help their support teams, enhance their customers’ experiences, and boost their competitive advantage.
By minimizing the need for human intervention (up to 80% of basic client queries can be suitably addressed with AI chatbots), the use of AI-enhanced customer service can return a 30% reduction in the cost of customer service provision. Putting that into a dollar figure, a recent report conducted by Juniper Research has determined that the use of chatbots will save businesses $11 billion a year. Here are a few ways service teams are currently using this technology to enhance their customer experience. Cognitive technologies are redefining how businesses interact with customers and service teams are no longer a peripheral aspect but a vital touchpoint influencing customer perception and loyalty. Shep Hyken, customer service expert and author of The Cult of the Customer, believes collaboration between human and machine can provide an opportunity for more efficient customer service.
Transforming customer service: The impact of AI
Besides a few exceptions (e.g., Araujo 2018; Derrick et al. 2011), the implications of more advanced anthropomorphic design cues remain underexplored. They can answer questions while guiding users towards relevant content and enhancing customer engagement. For instance, Facebook Messenger’s AI chatbots boost the platform’s customer service by providing quick responses to user inquiries, fostering engagement, and enhancing user experiences, thereby keeping users active and increasing the time they spend on the platform. An AI-enabled service perceived by consumers as courteous, caring, and responsive has the potential to inspire confidence in the brand (Wang & Lin, 2017). Moreover, from a consumer perspective, the experience of a high quality service decreases their perception of sacrifice (in terms of loss of control, loss of privacy, loss of money, effort, time consumption, or negative feeling, such as annoyance or irritation). Some studies position perceived sacrifice as a distinct factor from perceived service value (de Medeiros, Ribeiro, & Cortimiglia, 2016).
AI enables support teams to be agile in meeting customer needs because it removes the need to manually make changes to your processes. AI continues to learn from your customers in order to help you better meet their needs and can provide actionable insights into where customers need more help. Customer support is full of repetitive tasks and redundancies that when positively influenced, allow agents to perform better and optimely. The life of an agent can include answering the same support ticket hundreds of times a day, labeling and triaging tickets manually, and seeing increased response times to more complex tickets. “The customer always comes first”—it’s a business mantra as old as time, but it’s more relevant now than ever before.
Crucial Benefits of AI in Customer Service
To achieve this, we propose a new model drawing on trust commitment theory (Morgan & Hunt, 1994) and the service quality model (Parasuraman et al., 1994). Our model integrates trust and perceived sacrifice as factors mediating the relationships between the AI-enabled service quality, convenience and the customer experience. In addition, the model integrates relationship commitment as a factor affecting the customer experience of AI-enabled shopping.
A customer-centric service ecosystem requires the balanced use of AI-driven value co-creation while mitigating value-co-destruction concerns. The chapter concludes with a strategic framework to overcome challenges with balancing strategies to yield superior AI-enabled customer service. It is important to acknowledge that perceived sacrifices remain important concerns for customer, even after several interactions with AI-enabled services. Trust-commitment theory highlights the roles of trust and commitment to a relationship play in the process of developing relationships between buyers and sellers (Morgan & Hunt, 1994). Each study highlights the significant role that trust and relationship commitment play in technology-mediated interactions between customers and retailers.
How are customer service teams using conversational AI?
To find the answers to these questions, companies should start now with some relatively simple but high-value use cases that will allow them to test the technology and learn what works and what doesn’t from technical, functional, and business perspectives. Exhibit 2 lays out the variety of use cases across the typical customer service journey—from initial customer contact to final response and resolution—that will likely be augmented by generative AI. The large language models (LLMs) upon which ChatGPT and other text-based generative AI applications are built give these apps the power to respond to prompts with human-like text and voice, answering complex questions with seeming ease. The general public has quickly begun testing generative AI’s capabilities, and the technology is rapidly gaining acceptance, lauded for the variety and nature of the responses it provides.
I believe that innovation paired with the fundamentals of a personalized customer service relationship will be what divides the exceptional from the also-rans as we adapt to this shift. Ultimately, AI is only as good as the data it is given, so it is just as important that we continue developing the sources that give us the best data and ensure any tools we adopt go towards creating excellent customer service experiences and more effective CS agents. This way, implementing AI-enabled customer experience solutions will not only improve customer satisfaction and cut costs by reducing the time spent on dealing with customer enquiries, but also positively impact the overall health of your business.
Concerns and Challenges with AI in Customer Service
This capability, along with the ability to interact with customers just like a human agent in both tone of voice and responsiveness, will continue to improve the customer experience. AI can help every one of these aspects of support by automating repetitive queries, automating the ticket triaging process, and allowing agents an assistant when responding to the more complex support questions. Self-service platforms and chatbots can improve the customer experience, but they can also frustrate users.
- You might also exclude elderly individuals who don’t feel comfortable using this technology.
- As mentioned above, chatbots are the most effective AI/automation tool used in customer service, and 84% believe it improves the customer experience.
- Singh has implemented AI into their customer service processes and recommends that complex or emotionally charged issues “may require human intervention.”
- While AI itself isn’t exactly new, the sheer level of availability of this tech to humans is.
AI powered customer service solutions enable 24/7 customer support that helps offer customers the support they need no matter the time of day or their location. With 24/7 customer support, support agents aren’t required to be online around the clock and can still help customers even when they aren’t live. To achieve the promise of AI-enabled customer service, companies can match the reimagined vision for engagement across all customer touchpoints to the appropriate AI-powered tools, core technology, and data. Exhibit 1 captures the new model for customer service—from communicating with customers before they even reach out with a specific need, through to providing AI-supported solutions and evaluating performance after the fact. The most mature companies tend to operate in digital-native sectors like ecommerce, taxi aggregation, and over-the-top (OTT) media services. In more traditional B2C sectors, such as banking, telecommunications, and insurance, some organizations have reached levels three and four of the maturity scale, with the most advanced players beginning to push towards level five.
Regulatory Compliance
They introduced the tool to save customers from searching “for an FAQ or date selector to answer their questions” and provide a better experience. This makes it the second most popular use for AI/automation in customer service, according to the State of AI Report. Appinventiv is a leading AI development company that can be your strategic partner in harnessing the power of AI to transform your social media app. AI for social media apps helps identify the ideal influencer for a specific ad campaign.
Maya Gupta, Owner of Hoefnagel Wooden Jigsaw Puzzles Club, spoke about their experience using AI in customer service. According to Head of Customer Support at Koinly Hannah Nordlund, using AI to automate manual tasks can make everyday work life in customer support more interesting. “It’s a customer-first approach to creating a personalized and seamless experience between our social channels and ecommerce websites.” From 24/7 customer to multilingual support, we highlight seven key advantages of using AI in customer service.
Data-Driven Content Creation
This has implications for a wide variety of sectors, such as beauty brands to effectively generate personalised styles and product recommendations based on their demands and preferences (Maras, 2020). Expected benefits are increased levels of automation, cost reduction, increased flexibility and streamlined customer interactions. For these benefits to be fully realised, it is necessary to analyse and understand this complex phenomenon more deeply. For example, the dependence on AI technology and the need for increasing amounts of customer data may raise trust issues among customers (Dwivedi et al., 2019). Furthermore, the absence of human interaction or additional efforts potentially required from customers may constitute sacrifices affecting their overall experience.
Moving ahead into a more automated future can create the impression that the human touch — whether in everyday life or customer service — won’t be as valuable as it has been in the past. Enter machine learning, which currently accounts for 44 percent of venture funding in AI, and arguably represents the future of artificial intelligence-driven customer support. That may be effective for basic inquiries (i.e. “Do you have this printer in stock?”), but customer behavior is rarely predictable.
We cover what it is, how it works, and how it can be used as part of a successful support strategy. In most cases, reaping the benefits of AI is highly dependent on how thoughtfully you integrate AI into your customer what is AI customer service service tools and processes. But we also recognize that AI isn’t a one-size-fits-all solution for customer service teams. One that has customers not just returning but referring your product/service to their network.