10 Companies Using AI for Customer Service: Real-World Case Studies
We've already seen how customer service is being revolutionized by artificial intelligence (AI), with companies helping customers more quickly, more accurately, and around the clock.
By automating responses, personalizing interactions, and enhancing overall efficiency, AI is transforming how businesses care for their customers, improving customer satisfaction and reducing operational costs.
AI in customer service is not limited to a single industry. It's a versatile tool that can be used in retail, finance, hospitality, and beyond, enhancing customer experiences and optimizing efficiency across the board.
Let's delve into ten inspiring examples of AI used in customer service applications, each a success story in its own right.
1. BNP Paribas: Streamlining Inquiries with AI
The French multinational bank BNP Paribas had the challenge of repetitive inquiries from marketing teams slowing down how they could tackle unique, high-impact tasks.
They solved this by partnering with YeldaAI, creating a virtual assistant that automated responses to common questions. The AI-powered assistant was integrated into the bank's internal information system to access branding documents and information.
The AI assistant can retrieve specific files, guidelines, and promotional assets from the Information System. This is important because the AI reflects the latest guidelines essential for teams working across multiple regions.
The result was that 80% of requests were automated, allowing the brand to focus on more strategic and high-value initiatives. By reducing the manual workload, response times improved, and productivity increased.
2. Fnac: Voice-Activated E-Commerce on Google Home
The retail chain Fnac sought a way to make shopping more convenient. It didn't want to invest in custom app development, but it still wanted customers to use voice commands to order through Google Home.
The solution was to deploy e-commerce and customer service modules integrated with Fnac's APIs so that Fnac could quickly launch a voice application to assist customers with product inquiries and purchases through Google Assistant and Google Home.
The voice assistant generated millions of interactions. Fnac improved customer engagement, driving online sales. The voice technology helped keep Fnac at the forefront of AI-driven customer service in Europe.
Fnac made shopping more convenient and enhanced the user experience with product recommendations, searches, and customer service through voice commands. Voice-led search and buy options opened up new customer service channels.
3. Steel Shopping Mall: Interactive Voice Assistant for Customer Inquiries
When it opened, the Steel Shopping Mall in France expected a high volume of visitor questions and was looking for a voice assistant who could handle real-time inquiries.
With the help of YeldaAI, Steel implemented "Ponpon", a conversational assistant available on the mall's website and at kiosks within the mall. Ponpon can provide immediate answers to frequently asked questions.
Combining physical shopping with digital convenience means Ponpon's physical placement in physical kiosks allows them to enjoy the benefits more tangibly.
Ponpon handled over 4,500 conversations in its first month with a 90% comprehension rate, reducing the burden on mall staff while improving overall customer satisfaction.
4. Prixtel: Voice Support for a Digital-Only Customer Service Model
Prixtel is a fully digital telecoms company that needed to offer high-quality customer support on its mobile site without live agents.
By using YeldaAI's "FAQ" and "Customer Service" modules, Prixtel could automatically handle 80% of written and spoken customer inquiries.
It can use voice recognition to provide details on mobile plan pricing, usage, and account management, maintaining a customer-first approach.
As a digital-only company, Prixtel would otherwise struggle to offer a personalized touch that provided the efficiency of AI-driven automation.
Prixtel's voice assistant managed an 85% issue resolution rate, offering effective support for Prixtel without needing agents. The results were increased customer satisfaction and a stronger brand reputation while innovating digital support.
This AI solution could evolve to further reduce dependency on human agents by offering more detailed account management or AI-based solutions like mobile data usage predictions.
5. FrieslandCampina: Voice and Text Assistant for Customer Engagement on WhatsApp
FrieslandCampina is a dairy cooperative that wanted to improve its CRM in Asia through customer support and brand engagement on WhatsApp.
It deployed a multilingual (Chinese and English) assistant with YeldaAI. The assistant provides answers to product inquiries and general customer support.
As part of a broader CRM strategy, the AI system can deliver nutrition information, answer product queries, and directly guide customers on product use in WhatsApp.
The assistant helped improve FrieslandCampina's CRM capabilities in Asia and establish a more personal connection with customers through a widely used messaging platform.
This solution only uses WhatsApp, but FrieslandCampina could expand its AI solutions to other messaging platforms and support channels, leveraging AI in an omnichannel customer service solution for the best results.
6. H&M: AI-Powered Chatbot to Assist with Customer Service
The multinational clothing giant H&M looked to AI to manage high volumes of customer service inquiries, especially during peak shopping seasons.
The solution was an AI chatbot that could handle inquiries about orders, product information, and product availability. Using machine learning, this chatbot could offer personalized responses based on a customer's history and preferences.
These recommendations can include outfit combinations or similar items to what other customers browse online. It can also notify customers when items are back in stock or when new products arrive that they might like.
H&M reduced response times by 70%. The chatbot resolved common questions and even offered fashion tips.
7. Delta Airlines: Automated Customer Support for Flight Assistance
Delta Airlines needed to streamline support for frequent customer inquiries, particularly those relating to flight bookings, baggage tracking, and other travel services.
The solution was a chatbot that could help passengers with booking, travel updates, and flight check-ins. Powered by AI, this bot retrieves relevant data, offers tailored assistance, and improves service for travelers.
In addition to flight information, it can assist with frequent flyer account inquiries and travel restrictions, providing a comprehensive customer service solution.
By integrating voice commands, Delta customers can enjoy hands-free customer support, which is particularly useful for passengers on their way to the airport or busy business travelers.
The result was a faster service, particularly during peak travel periods, reduced wait times, and higher customer satisfaction. Delta could handle many inquiries, far more than human agents could have handled without the solution.
Ultimately, the most significant results are seen at in-airport service desks, where lines are shorter, and customer feedback metrics are more positive.
8. KLM Royal Dutch Airlines: Social Media Integration for Real-Time Customer Support
Another airline, KLM, was looking for a way to improve customer support, but this time, the focus was on social media, where many of KLM's customers expect real-time responses.
KLM used a specialized AI tool integrated into social media platforms like Twitter/X and Facebook. Customers can manage common inquiries, such as booking changes, flight schedules, and baggage policies.
A fine example of using AI to deliver personalized social media support, KLM's chatbot answered questions with real-time flight tracking, boarding processes, and even passport requirements. The chatbot is multilingual and can accommodate international travelers across social media platforms.
KLM's chatbot handles thousands of messages weekly, reducing response times and enhancing customer satisfaction through social media engagement.
9. Uber: Proactive Support with AI for Better Customer Satisfaction
Uber, a ridesharing platform, needed a way to handle a large volume of customer service inquiries, from ride cancellations to billing disputes.
Uber used AI-powered solutions to identify potential issues and proactively solve them automatically. The system detected patterns in ride data and suggested solutions before customers even filed complaints.
It can contact users who may face delayed pick-ups, offering them solutions like refunds where necessary. It predicts common pain points through past ride data and ultimately makes riders feel more valued and supported.
Complaint handling times were significantly reduced, and the customer experience improved. After all, solving a problem before it's even a problem means that customers won't have to follow up.
10. Octopus Energy: AI-Assisted Email Responses and Query Management
Octopus Energy was looking for a way to improve customer satisfaction by improving their email support, particularly regarding response times and accuracy.
The AI assistant generates detailed responses to customer inquiries while automatically categorizing and prioritizing emails so that human agents can handle more complex issues.
Beyond categorizing inquiries into urgent, medium, and low-priority tiers, it retrieves past interactions and allows for personalized responses so customers don't need to repeat details.
Overall, the solution improved customer happiness by 18% as inquiries were handled more quickly and accurately, resulting in more satisfied customers.
As you can see, AI is becoming a force for change in customer service rather than as a replacement for human customer service agents.
Instead, it takes care of repetitive tasks, provides personalized assistance, and proactively addresses customer issues, leaving customer service agents free to focus on areas where they provide the most value.
As these tools continue to evolve, there's much scope for further integration into other existing systems, beyond customer data and CRM, further raising the bar for unparalleled customer service.
The human element is still crucial, though, as you can see how AI is used alongside human customer service agents as a tool that empowers them to do their best work.
Organizations already use AI for customer service in powerful ways, but who knows what the future will bring?