Published March 28, 2023
Building and retaining successful client relationships is a key element for any business to succeed in today's competitive world. With constant advancements in technology, artificial intelligence (AI) has become a mainstream tool for businesses. One of the most exciting applications of AI is generative AI, which can help businesses in building and nurturing successful client relationships. In this article, we will discuss how generative AI can be leveraged in client service.
Generative AI is an AI-based technology that creates a model from a specific data set and produces new output. It's an exciting technology that can be used for a variety of applications, including personalised communication, predictive analysis, and to support customer service. In recent years, businesses have started to realise the importance of generative AI for building successful client relationships. By using generative AI to analyse client data, companies can gain a better understanding of their clients' needs and preferences.
One specific type of generative AI is Large Language Models, or LLMs. Large Language Models (LLMs) are a type of machine learning model that is trained to understand and generate natural language. They are capable of processing large volumes of textual data, learning from it and then producing responses that can be indistinguishable from those generated by humans. LLMs like GPT-4, BERT and T5 have gained a lot of popularity in recent years due to their ability to perform a range of language-related tasks, such as text classification, question answering, summarisation and even language translation.
Artificial intelligence (AI) can bring numerous efficiencies when working with clients, let’s explore some of these in more detail:
One of the most significant benefits of AI is that it can process vast amounts of data quickly and accurately. This means that AI can help client service teams make better decisions by analysing data more comprehensively than humans. AI can analyse data from multiple sources and identify patterns and trends that may not be immediately apparent to humans. By processing data faster and more accurately, AI can help businesses make more informed decisions that are based on data-driven insights.
By analysing client feedback, reviews or client engagement, AI can identify the sentiment behind the text, whether it is positive, negative or neutral. This information can then be used by businesses to understand client sentiment and improve their products or services.
AI can learn from previous interactions with clients and apply that knowledge to future interactions. This can help clients receive personalised service and customised solutions, which can contribute to increased client satisfaction and loyalty. For example, if a client has a history of purchasing certain products or asking certain questions, AI can use that information to provide personalised recommendations or solutions. This can help to improve the client experience and increase their likelihood of remaining a loyal client.
Another efficiency that AI brings is the ability to automate routine tasks. For example, AI can handle basic customer service inquiries, freeing up client service managers to handle more complex tasks. This can help increase the efficiency of client service teams and reduce response times for clients. AI can also automate data entry and processing, reducing the time and effort required to complete these tasks. This allows clients to receive faster and more efficient service, which can lead to increased productivity and profitability.
AI can also help businesses identify patterns and trends that they may have otherwise missed. For example, AI can analyse customer purchase history and identify products or services that are frequently purchased together. This can help client service teams identify cross-sell and up-sell opportunities, which can increase client revenue. By identifying patterns and trends, AI can also help client service teams make more informed decisions about their business.
Kaizan is an AI designed for client service teams to help expand revenue. Communication data gathered from client calls and via email communication is passed through LLMs to train the AI on client sentiment. The AI can be trained to spot key phrases mentioned by a client or a lack of engagement in real-time, which will provide risk flags to the client service team. They can use these warning signs to understand which clients are at risk of churning and create an appropriate strategic plan to remedy. Equally, the AI can be trained to surface the most immediate cross-sell and up-sell opportunities based on client sentiment and language used during interactions with the client service team.
Generative AI can also be used to improve customer service. By analysing customer data, generative AI can identify common issues and provide solutions before the customer even reaches out for help. This can help in reducing response times and increase customer satisfaction. Additionally, generative AI can be used to create virtual assistants or chatbots that can answer common questions and provide support 24/7. This can help businesses to provide a seamless customer experience and build a strong relationship.
Whilst generative AI can be a valuable tool for building successful client relationships, it is not a replacement for human interaction. Clients still want to feel like they are working with real people who care about their needs and concerns. To strike the right balance between automation and personalisation, it is important for companies to take a multifaceted approach to client interactions. This might involve using generative AI to personalise content, but also incorporating more traditional tactics like personalised follow-up emails, in-person meetings or events, and actively seeking feedback from clients.
While generative AI offers many benefits for businesses, there are also challenges that need to be addressed. One of the main challenges is ensuring the accuracy of the data used to train the model. Another challenge is the potential for bias in the data, which can lead to inaccurate or unfair predictions. To overcome these challenges, businesses need to invest in high-quality data and ensure that it is representative of their client base. Additionally, businesses should regularly audit their AI systems to detect and correct any biases.
Overall, generative AI has the potential to revolutionise the way that companies build and maintain successful client relationships. By using this technology thoughtfully, companies can create more personalised, efficient, and effective interactions with their clients, leading to better business outcomes and increased success. As AI continues to evolve, it is important for businesses to stay up-to-date with the latest technologies and use them to their advantage.