Generative AI’s Transformative Impact on B2B Customer Service

10

October

2023

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Where self-service portals and chatbots dominated customer service for a long time, the next trend, to improve customer interaction and service quality, seems to be set by generative artifical intelligence (GenAI). The application of this emerging technology is increasingly seen in well-known platforms such as Zendesk and Salesforce Einstein, which use AI to enable personalised and more efficient service and improve current functionalities within systems.

The role of GenAI in B2B sales and Customer Service

GenAI is not simply a new technology, but rather can be seen as a collaborative partner. In B2B sales, GenAI strengthens the sales team on sales support tasks and marketing topics, freeing up team members’ hands, improving performance and ultimately generating more revenue (D’Angelo et al., 2023).

Looking at customer service, the application of GenAI will be able to increase productivity by 30-50% over the next three years (Bamberger et al., 2023). However, for now we are still in the third phase concerning the implementation of this technology, human-like self-service. After all, GenAI currently still contains relatively many sensitivities and inaccuracies, requiring human supervision to further train the model. Therefore, to make GenAI work for your organisation at this stage, a good balance and interaction between GenAI and team members is very important to ensure the reliability of the output.

Insights and Personalization

Another big advantage to GenAI will be enabling personalised customer experiences on a large scale. For instance, GenAI will not only make it possible to provide answers or suggestions to a customer or customer service agent, but also analyse data and come up with strategic insights (Kudyba, 2018). Based on these insights, the organisation can recruit strategic insights to understand their customers even better and recognise trends. One industry where GenAI is already deployed in this way is the financial sector; within the sector, personalised solutions and strategic choices measurably increase customer satisfaction. In this case, GenAI is not just a tool but the instigator when it comes to permanently changing customer contact through a far-reaching personalised experience.

Tools and applications

As described earlier, GenAI still needs to take some steps to provide complete support for every challenge. Nevertheless, organisations today can already benefit from the technology in applications such as Zendesk. The AI within Zendesk enables customer service agents to send AI suggested empathetic responses or offers (Mitchell, 2023). In doing so, Zendesk rests on the most fully trained AI currently available, namely ChatGPT, to further improve its own technology and get the most out of the Zendesk platform. The ultimate goal here is not to replace the agent’s work but rather to complement it and thereby improve the overall customer experience (Siggelkow, 2023).

Catching on to Zendesk’s vision, the integration of GenAI into B2B Customer Service seems inevitable, but also essential to provide improved, personalised and more efficient customer interaction.

References

Bamberger, S., Clark, N., Ramachandran, S., & Sokolova, V. (2023). How generative AI is already transforming customer service. BCG Global. https://www.bcg.com/publications/2023/how-generative-ai-transforms-customer-service

D’Angelo, S., Gauch, B., Hawks, A., & Ward, M. (2023). Get your B2B sales team ready for the power of generative AI. BCG Global. https://www.bcg.com/publications/2023/how-genai-can-transform-b2b-sales

Kudyba, S. (2018, July 24). Machine learning can help B2B firms learn more about their customers. Harvard Business Review. https://hbr.org/2018/01/machine-learning-can-help-b2b-firms-learn-more-about-their-customers

Mitchell, C. (2023). Zendesk expands its generative AI capabilities, announces new safeguards & controls. CX Today. https://www.cxtoday.com/crm/zendesk-expands-its-generative-ai-capabilities-announces-new-safeguards-controls/

Siggelkow, N. (2023, April 4). Create Winning Customer Experiences with Generative AI. Harvard Business Review. https://hbr.org/2023/04/create-winning-customer-experiences-with-generative-ai

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“This is your digital assistant; how can I help you?”

8

October

2021

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Over the last few years, the application of speech technology has become increasingly popular (Moore, 2017). Speech technology mainly consists of speech recognition, which transforms spoken words into text, and natural language processing, which aims to actually understand this text and convert it into understandable and analysable data (Chowdhury, 2003). Therefore, it can contribute to the gathering of knowledge about the needs and use of language by humans. A well-known example of speech technology, that nearly everyone has personal experience with, is Siri on Apple’s devices. It’s safe to say that customer experiences with these technologies are not completely seamless yet, as Siri usually starts speaking to you at the moment you don’t want her to, or decides to call one of your contacts instead of skipping a song on Spotify. However, if used in the right way, speech technology can assist firms in getting a better understanding of the needs of their customers, improving their customer service channel, and step-by-step creating a more seamless customer experience.

Digital customer service: benefits only?

Most companies have installed an artificial intelligence-based chatbot on their website by now (Weerabahu et al., 2018). However, by implementing speech technology into their customer service channels, in the form of a digital assistant on the phone, firms can assist their customers in the old-fashioned way, but then the improved version of it. As an infinite number of digital assistants is constantly available, customers their waiting times will be drastically decreased. Additionally, they will be able to call the customer service centre at every time they would like, also after opening hours of the firm. These benefits would definitely create a more seamless customer experience. The firm that implements a digital assistant on its phone line will receive benefits as well. By having the digital assistant ask the simple question “What can I help you with?”, firms will gather more information about the needs of their customers, and know where they can improve the information that they provide on their products and services. Additionally, firms will learn about the language that their customers use. This will allow the digital assistant to, eventually, take over repetitive tasks from human customer service employees, and leave providing specialised advice to human customer service employees.

I’m wondering: How do you feel about digital assistants replacing human customer service employees? And do you think that, eventually, all human customer service employees will be replaced?

References

Chowdhury, G.G., 2003. Natural language processing. Annual review of information science and technology, 37(1), pp.51-89.

Moore, R.K., 2017. Is spoken language all-or-nothing? Implications for future speech-based human-machine interaction. In Dialogues with Social Robots (pp. 281-291). Springer, Singapore.

Weerabahu, D., Gamage, A., Dulakshi, C., Ganegoda, G.U. and Sandanayake, T., 2018, December. Digital Assistant for Supporting Bank Customer Service. In International Conference of the Sri Lanka Association for Artificial Intelligence (pp. 177-186). Springer, Singapore.

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Chatbot Explosion

18

September

2021

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Chatbots are popping up more and more at companies. As primarily it was used in customer service, but the shift has also taken place in improving customer experience (CX), business efficiencies, and these are just a few to name it. Chatbots are often termed as virtual agents, digital assistants, virtual customer assistants, and conversational AI bots.

Unforgettable COVID-19

COVID-19 is working as a catalyst for 76 percent of enterprises to invest in long-term IT reforms [1]. Due to the COVID-19 situation, businesses are digitizing to safeguard staff and service consumers who are experiencing mobility issues. Artificial intelligence-powered (AI-powered) chatbot spending will reach $78 billion in 2022, a massive increase from the $24 billion forecast in 2018 [1]. Software is the fastest-growing technology category, with AI/cognitive systems accounting for 40% of the market, with a five-year compound annual growth rate (CAGR) of 43% [1]. Deep learning and machine learning applications (wide applications across all sectors) and conversational AI are the two verticals where investments are concentrated (chatbots, personal assistants, virtual agents, etc.). The United States has the greatest market in conversational AI in terms of size and growth, while Southeast Asia has the fastest CAGR [1]. With increased private equity investment in AI/machine learning, the United States will dominate the incorporation of conversational AI. Furthermore, rising government spending on AI-powered technology will hasten industry expansion. The demand for increased functionality and value is driving an explosion of investment and interest as more consumers and businesses employ chatbots.

Explosion? Why?

When it comes to quick answers, 74% of customers end up choosing AI chatbots [1]. Companies who use AI chatbots in retail have witnessed a 47 percent increase in efficiency, a 40 percent increase in inventiveness, and a 36 percent increase in helpfulness [1]. Increased need for lower AI chatbot development costs, greater customer service, and omni-channel development are all driving growth.

Roadblock?

Although the chatbot market is still in its early stages, Europe lags behind other countries because to data privacy, ethical concerns, fear of failure, and market uncertainty [1]. The language barrier is now the most significant obstacle in the way of chatbots in underdeveloped countries. It would be straightforward if all interactions were conducted in English. Other languages, on the other hand, can be far more sophisticated in terms of syntax and organization. To feel natural to customers and so improve the customer experience, chatbots must be schooled in the complexities of the language [1].

Each organization that commits to a chatbot in its business operations decides for itself the regulations regarding the development of the chatbot. Among other factors, a chatbot can handle sensitive data. So here and there may vary the extent to which the chatbot is transparent.

I personally believe that it should be clearly stated in advance what will be done with the data and in whose hands it ends up. If I would like to use a chatbot myself, the questions will refer to more informative answers that you can get within a split second via the chat. No more and no less.

Now, I am curious to what extent will you trust a chatbot with sharing data (for example, personal data) and why?

[1] Hoang, T. (2021, 17 mei). The AI Chatbot Explosion in Various Regions around the World. Discover.Bot. https://discover.bot/bot-talk/ai-chatbot-in-various-regions/

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Implementing AI chatbots for automating call centers for better online customer services

9

September

2019

No ratings yet. The developments in the world of Artificial Intelligence (AI) gave rise to chatbots and set foot as a new way for organizations to communicate with their customers. Adopting these AI-based chatbots to respond to customer services requests should be an essential consideration in every organization.

What is a chatbot? And Why?

A chatbot is a computer software system with which you can interact with natural conversational language through messaging apps, chats, windows with text-based messages or increasingly by voice [1][2]. But, how do these chatbots engage with people? Well, there are two types of chatbots: simple and AI-powered chatbots.

Simple chatbots respond to predetermined answers to customer’s questions. These are very practical for providing quick solutions to routine questions. However, there is an increasing excitement revolve around AI chatbots, which are enabled via machine learning and natural language processing (NLP). In NLP, the bot learns the language of the customer, based on the experience and data from previous conversations given by people in the past. The bot learns to recognize what the intentions of the customers are, and which data is included in the customer’s message. Then, based on the business ruling, the bot examines what his next question should be. The bot interacts with the customer to request any missing data or opt for calling an employee for further help when necessary. These AI-driven chatbots can perform very sophisticated tasks, creating a real back-and-forth conversation between the human user and machine [3].

We have seen the abilities of these AI-powered chat agents in one of the Google’s I/O 2018 conferences revealing the Google Duplex [4], which could carry out realistic specific verbal tasks, such as making a reservation or appointment, over the phone [5].

This is huge, as organizations can program to use these AI chatbots for automating their call centers and improve upon their customer services, both online and physically on the phone.

The main reasons why organizations with call centers should adopt AI chatbots are because chatbots are available 24/7 and can give an immediate response on customer’s requests alleviating the frustrations in having to wait for the busy employees of call centers to pick up. They give very consistent answers to customer queries, even able in multiple languages and are very good at working with high volumes of requests. Automating the responses can free up human agents to deal with more complex issues with specific customer queries and requests. [6]

This increases employee satisfaction because the work of a customer service employee becomes more challenging.  Yes! They make the work in customer service more satisfying and on top of that will not replace the employees working there. They help with providing a better customer experience, preventing any irritation and frustration, making sure the chatbot does not get in the way of the customer and gives up the conversation to the employee when needed, which the employee benefit from not having to answer to routine everyday questions. Chatbots also significantly reduce the lead times of conversations and increases customer satisfaction. Customers with simple questions get an immediate response, without having to wait. AI Chatbots can listen and detect the emotional content based on the language and can bring up appropriate response information by passing it to the call center’s worker screen who can give a more attentive response for customers in difficult situations. [7]

However, chatbots are still at their infancy and don’t always work right and seamlessly as hoped for, which can create even more frustration for customers. Many organizations have opted for implementing this innovative technology of chatbots without thinking, simply doing it for the sake of doing it, as chatbots were making a widespread presence due to the nature of its hype.  Organizations should, however, be developing these chatbots with primary emphasis on helping the employee in the call center first, to build up their capabilities and confidence, such as increasing their satisfaction at work, before implementing one for the customers. If done with the right approach, organizations should definitely consider implementing AI chatbots in their online customer services as it brings benefits of much better and seamless customer service.

 

References:

[1] Shawar, B. A., & Atwell, E. S. (2005). Using corpora in machine-learning chatbot systems. International Journal of Corpus Linguistics, 10(4), 489–516. doi: 10.1075/ijcl.10.4.06sha

[2] Guzman, I., & Pathania, A. (2016). Chatbots in Customer Service. Accenture Interactive.

[3] Rouse, M. (n.d.). What is IM bot? – Definition from WhatIs.com. Retrieved from https://searchdomino.techtarget.com/definition/IM-bot

[4] Rouse, M. (n.d.).  What is Google Duplex? – Definition from WhatIs.com. Retrieved from https://whatis.techtarget.com/definition/Google-Duplex

[5] You can find this in the following Youtube video https://www.youtube.com/watch?v=D5VN56jQMWM).

[6] Jepma, L. (2019). Chatbots: Beyond the Hype, Now What? Retrieved from https://www.business2community.com/tech-gadgets/chatbots-beyond-the-hype-now-what-02237191

[7] Baraniuk, C. (2018). How talking machines are taking call centre jobs. Retrieved from https://www.bbc.com/news/business-45272835

 

 

 

 

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