TLDR: An AI-Powered Customer Service Revolution – AI is transforming customer service by offering personalised solutions, and UX plays a crucial role in creating intuitive and engaging customer experiences.
Revolutionising Customer Service
AI-Powered Solutions for Financial Institutions
Imagine a world where customer service is not just efficient but truly personalised.
The Challenge: In today’s fast-paced digital age, financial institutions face the challenge of providing exceptional customer support while maintaining operational efficiency. Traditional customer service UX often falls short in meeting the diverse needs and expectations of modern customers.
The Solution: This case study explores how AI can revolutionise customer service by creating seamless support and behind-the-scenes tools that put people and businesses in control of their money.
By leveraging AI-powered tools, financial institutions can transform the way customers interact with their services and UX designers can connect the dots with engineers, product managers, analysts, and researchers, to tell stories that position AI-powered tools as a business friend, not a foe.
User research and UX Design
What the product needs to accomplish.
Evidence informs designers that Customer Service Representative (CSR) typically operate in multiple panes of glass. Extracting snippets of information to help customers within the guardrails of their abilities, their access and a timeframe (a phone call). How can this be combined, for the CSR and potentially for self-serving customers?
Three persona-types, three outputs;
- Mr ‘Self-service’; They need a tool highlighting quick-and-easy answers to their questions, without having to contact a CSR. CSR can also provide support and is able to troubleshoot issues and resolve customer problems to deeper issues.
- Mrs ‘To-the-point’; Some customers want only the facts, escalating issues to a human CSR when necessary.
- Mr ‘Analytical’; CSRs need to have a complete understanding of a customer’s history in order to provide effective support.
Developing a user centred mode
Personalised recommendations, automating routine tasks, (like FAQs) and predictive analytics based on customer needs and behaviours, are just some of the benefits Machine Learning has in the field of UX Customer Service.
It was clear for this project there was no one silver bullet. Providing a suite of support from self-service to employing Natural Language Processing (NLP) can all contribute to improving the overall customer experience. Understanding the wealth of possibilities Artificial Intelligence can provide, there was a focussed on three key areas:
1. Personalised Knowledge Base
An AI-powered knowledge base that proactively suggests relevant articles or FAQs based on the customer’s specific query.
More about ‘Proactive Suggestion’ Later
2. Integrated Chatbots with Human Handoff
Allowing the AI to analyse customer sentiment enables the bot and the CSR to tailor their responses to better meet customer needs and improve satisfaction.
3. Unified Customer History
A centralised platform that provides agents with a complete view of a customer’s interactions, including past inquiries, support cases, proactively alerts, and account history.
Interlude
Proactive Suggestions
AI can anticipate customer needs and offer solutions before the customer even asks through machine learning algorithms of a customer’s history, product information and industry trends that identify patterns and predict potential customer needs proactively. For example, recommending accessories to recently purchased items, offering troubleshooting tips if a customer has contacted support multiple times, etc.
Here the AI recognises this customer has recently been the victim of fraud (see Account Overview note). The right sidebar offers a platform for the UI to proactively generate helpful links to the CSR to aid the customer, before they have even asked.
My UX Process and Impact
Refined wireframes, optimise self-service and focus on the benefits of a conversational AI
Starting with several wireframed directions, then through osmosis filtered down concepts to self-service, a conversational UI and omnichannel integration within the form of a centralised platform. Based on experience and number of assumptions, wireframes were generated to bolster clarification. Variants evolved in parallel that merged into a winning model for all three proposals;
1. Self Service and Hyper-Personalisation
Proactively suggestion, relevant articles and FAQs
A Personalised Knowledge Base empowers customers to self-serve, with dual-function to help CSR agents to provide targeted support. Aligned to business objectives, these external and internal tools thrive on individual customer data, preferences and behaviour.
The Customer
Customers are presented with a user-friendly interface, to reduce wait times and empowered customers can self-serve by searching for documents, tutorials (or anything really), related to their query. They have prompted categories to help with Discovery and personalised topics that are trending this week.
On login, the user is greeted with an app-like interface. This contemporary approach guides them through top-level categories, i.e. Personal and Business finance, then using a navigation as a signpost they are able to drill-down on an Account Overview and User Guide. Tailored topics are surfaced (based on search and account history) within the sidebar quick links.
The interface has push-points throughout all sections both introduce AI recommendations and provide personalised AI financial insight.
The CSR
Using the same B2C interface, CSR agents can access and add-to content, generate most frequently asked self-service tutorials and use the Knowledge Base to improve their own skills.
2. Conversational Interface with Human Handoff
Human-AI Hybrid
A smooth transition from AI chatbot, with ‘sentiment analysis’ baked-in, to a human agent
An AI chatbot that can handle simple inquiries but seamlessly transitions to a human agent when the conversation becomes complex or requires personalised assistance. This hand-over reduces agent workload for routine queries which improves customer satisfaction with faster responses, but also ensures a smooth transition to human support when needed.
NLP
Natural Language Processing (NLP)
Gauge customer emotions from an AI-Chatbot that uses sentiment analysis baked-in.
Properly trained, the AI can recognise the underlying intent behind customer queries, even if expressed differently and provide the right hand-off to the right CSR.
3. Unified Customer History
360˚ View
A centralised platform | An assistant that proactively spot patterns to anticipate customer needs
A centralised platform that provides agents with a complete view of a customer’s interactions, including past inquiries, support cases, account history and proactively alerts. For example, if a customer is nearing their contract expiration and has a high purchase frequency, the platform could proactively offer renewal terms or upsell opportunities.
A single platform to access all customer interaction data:
- Reduces the need for customers to repeat information
- Enables agents to provide personalised and informed assistance
- Spot patterns and insights that might inform business decisions
- Anticipate customer needs and provide timely solutions with proactive support
Outcomes, split by discipline
It is clear that AI enhances personalisation, efficiency, and problem-solving. But how can UX leverage these to create a more human experience.
Business Outcomes:
- Operational Efficiency: AI streamlines processes and reduces agent workload.
- Data-Driven Insights: AI provides valuable customer data for informed decisions.
- Cost Reduction: AI automates tasks and reduces operational costs.
UX Outcomes:
- Personalisation: AI can tailor the Self-Service experience, and brings Hyper-Personalisation to individual needs.
- Seamlessness: AI integrates chatbots and provides a unified customer view.
- Proactive Support: AI anticipates customer needs to find answers fast and can provide that 360 view at-a-glance.
UX & AI | Future-proof partners
Overall, UX and AI empowers businesses to deliver exceptional customer experiences, improve efficiency, and gain that competitive edge.
Empowering users with the financial tools they deserve
- Mastering Design Theory and Lean Agile
- Solve big problems, fast.
- How delight and speed are rewriting our UX playbooks