AI for Customer Support: Case Studies and Results for SMEs
When it comes to resolving customer issues, what’s more important: speed or accuracy? In truth, both are equally crucial. Customer service directly impacts revenue, reputation, and customer loyalty. Yet many CS teams struggle with overwhelming inquiry volumes, fragmented systems, and limited staffing. These challenges slow down response times and reduce service quality.
The core issue is inefficient access to information. Agents spend valuable time switching between tools to find what they need. In high-turnover environments, the lack of experienced staff adds even more friction.
Why is AI essential for customer service teams, and how can it help? Enterprise AI Search gives agents instant access to accurate, cross-system data. It improves speed, enhances service quality, and enables teams to focus on solving meaningful problems. In this post, we explore how AI is reshaping customer service through real enterprise use cases.
Enterprise Case: How AI for Customer Support Boosted Performance
📌 Vodafone: Improving Support Efficiency with AI Search
Challenge:
Vodafone’s customer service center faced a major bottleneck due to fragmented data across multiple systems. By leveraging AI for customer service, Vodafone aimed to streamline data access and improve overall support efficiency. Customer contract information, pricing plans, and technical support data were all stored separately, making it difficult and time-consuming for agents to retrieve what they needed. This led to longer wait times and reduced operational efficiency.
AI Adoption:
Vodafone addressed this by implementing IBM Watson Assistant to develop and integrate the chatbot into its agent support system. AI analyzes customer queries in real time and delivers relevant information, such as contract details and pricing options. Directly to agents. By performing unified searches across multiple databases, AI presents the necessary data through a single interface, eliminating the need to switch between systems.
Key Result of AI adoption:
- Customer satisfaction increased by 50% with GenAI-enhanced AI interactions
- Net Promoter Score (NPS) improved by 20% compared to the previous AI system
- First-time resolution rate increased from 15% to 60%
- Shorter customer wait times and improved service quality
AI enabled agents to access information quickly and efficiently, reducing call durations and freeing them to focus on tasks that required human judgment and problem-solving. Rather than replacing agents, AI functioned as a real-time assistant that enhanced productivity and decision-making.(Vodafone to boost TOBi with GenAI, The Mobile Network 2024)
📌Lufthansa: Reducing Wait Times through AI Search
Challenge:
Lufthansa’s customer service center, Lufthansa InTouch, faced mounting operational pressure due to high volumes of inquiries related to booking changes, refund requests, and flight details. Agents had to manually retrieve data from various systems—including reservation records, account details, and flight schedules—leading to delays and inefficiencies.
AI Adoption:
Lufthansa adopted the AI platform to implement a conversational AI system, which was integrated into the agent support workflow. This AI solution analyzed customer queries in real time and retrieved relevant data, such as booking information, flight schedules, and refund policies, from multiple backend systems (e.g., CRM, reservation platforms). It also suggested optimal next steps, like proposing alternative flights or guiding refund procedures, to support faster decision-making.
Key Result of AI Adoption:
- Reduced customer wait times and improved service quality.
- AI agents support 16 million customer interactions per year, with peaks up to 375,000 per day.
The AI streamlined access to complex, distributed data, helping agents resolve inquiries faster and more accurately. By automating repetitive lookups and offering context-aware guidance, it allowed agents to focus on more nuanced customer interactions such as explaining refund policies or negotiating travel changes. The implementation also led to a significantly lower Average Handling Time (AHT), allowing agents to resolve inquiries more efficiently. It served as a reliable productivity partner rather than a replacement.(16+ Million AI Conversations Yearly With Self-Service AI Agent)
How AI Boosted CS Team Performance in SMEs
📌 Avetta: Shortening Call Handling Time with AI Search
Challenge:
Avetta’s customer service team faced operational inefficiencies caused by data silos across multiple systems. Information related to supply chain contractors, compliance documentation, and past customer inquiries was scattered, making it time-consuming for agents to locate and process the data. This led to longer customer wait times and prevented agents from focusing on complex support requests.
AI Adoption:
To address these issues, Avetta integrated a conversational AI solution to support its customer service team. The AI analyzed customer inquiries and retrieved relevant information—such as contractor certification status, compliance documents, and historical tickets—in real time, displaying it through a unified interface. AI-generated videos were also used to streamline agent onboarding and training processes, helping reduce data handling time. Additionally, the AI provided real-time guidance to agents, offering suggestions such as how to navigate compliance procedures.
Key Result of AI adoption:
- Reduced average call handling time by 16 seconds
- Increased onboarding efficiency by 20%
- Increased agent retention by 8%
AI eliminated the need for agents to manually navigate fragmented data systems, allowing them to access key information quickly and efficiently. This significantly shortened handling times and enabled agents to devote more attention to complex issues, such as contractor compliance resolution. AI-powered video training further enhanced agents’ ability to process data effectively. By automating repetitive tasks, the AI served as a productivity partner that elevated both decision-making and customer engagement quality. (Synthesia Case Study – How Avetta is using AI video to boost the productivity of 150 support agents 2024)
📌AI Is Vital for SMEs and CS Outsourcers Too
We’ve seen how companies of all sizes are using AI to transform their customer service operations. But in many ways, AI can make an even bigger impact for smaller teams, where every second counts and resources are limited. For SMEs and outsourcing providers, faster response times and higher accuracy are not just goals. They are essential to business success.
Want practical insights into how SME support teams use AI?
Key Considerations for AI Adoption in SMEs
AI has proven to be a powerful enabler for SMEs and customer service outsourcing teams, driving both efficiency and quality in customer service operations. As demonstrated in multiple cases, successful implementation requires more than technology—it demands clear goals, strategic planning, and a realistic understanding of AI’s limitations.
Unlike large enterprises, SMEs must make every investment count. That means evaluating AI solutions based on cost-effectiveness, scalability, real business impact, security, and the agent experience. When implemented correctly, AI enables support agents to offload repetitive work and focus on high-value, complex customer needs—boosting both satisfaction and productivity. Here are the key considerations SMEs should address before adopting AI in customer service.
1. Set Clear Objectives and Define AI's Role
Gartner (2024) highlights that clear use cases are key to successful AI adoption. SMEs should begin by identifying the specific bottlenecks in their CS operations—such as delays in accessing customer data or lack of training for new agents.
Once the pain points are clear, define measurable goals: reducing response time, improving First Contact Resolution (FCR), accelerating onboarding, or increasing customer satisfaction. AI can support these objectives by:
- Automating repetitive inquiries: Chatbots and virtual assistants can handle FAQs and simple requests, reducing agent workload.
- Centralizing data access: AI can retrieve data scattered across multiple systems (CRM, ERP, ticketing) and present it through a single interface.
- Offering real-time agent guidance: AI can recommend next-best actions (e.g., refund options, policy explanations) to increase accuracy and consistency.
2. Ensure Ease of Deployment
Many SMEs lack dedicated IT teams, making ease of adoption a top priority. Developer-free solutions that don’t require complex setup allow businesses to implement AI quickly and start seeing results without significant technical investment.
- Choose no-code/low-code platforms: Tools like Refinder or Zendesk AI are designed for non-technical users to set up and operate with minimal support.
- Run a pilot (POC): Before full deployment, test whether the AI tool aligns with your workflow. Free trials or demo periods reduce risk and help increase internal buy-in.
3. Prioritize Fast Setup
Even cloud-based SaaS AI solutions can take 4–6 weeks or more to fully integrate, depending on the scale and complexity of the systems involved. For SMEs, plug-and-play solutions that are ready out of the box help preserve limited resources and deliver value faster.
A solution that enables quick testing and immediate results allows teams to make data-driven decisions about full adoption, without lengthy delays or costly customization.
4. Assess Total Cost and ROI
The subscription fee alone doesn’t reflect the true cost of AI. SMEs need to consider the total cost of ownership (TCO), which includes direct, indirect, and hidden expenses.
- Direct costs: SaaS fees, licensing, or server costs for on-prem deployments.
- Indirect costs: Agent training, system integration, ongoing support and maintenance.
- Hidden costs: Security and compliance preparation, risk of implementation failure, or future upgrade needs.
To maximize ROI, SMEs should look for options that allow them to start small—minimizing upfront investment and scaling as needed.
5. Confirm Security and Compliance
SME support teams and outsourcing providers handle sensitive customer data. Any AI solution must comply with data security standards and local regulations like GDPR or CCPA.
Before deployment, confirm the solution:
- Encrypts data at rest and in transit
- Supports role-based access controls
- Is designed with regulatory compliance in mind
Refinder: AI Search Solution for SME Customer Service
Fast Setup and No-Code Integration
Refinder is a lightweight AI-powered search solution designed for SMEs, startups, and support teams that need fast deployment and simple configuration. It connects to tools like Google Drive, Gmail, Notion, Figma, Jira, and Confluence — all without needing a developer.
With no-code integration and a low learning curve, Refinder helps teams get started quickly without IT bottlenecks.
Secure and Compliant AI for Customer Data Handling
Refinder is designed with security and compliance at its core, making it a reliable choice for teams handling sensitive customer information. It includes robust access controls and compliance features tailored to regulated industries.
AI Search to Improve Response Time and Accuracy
By unifying scattered data from multiple tools, Refinder enables customer support agents to instantly retrieve the information they need. This directly reduces average response time and increases resolution accuracy.
Its RAG-based AI engine understands complex queries and returns relevant answers, even across fragmented or unstructured data sources.
Easy Onboarding and Trial for SME Support Teams
Refinder is ready to use in just a few hours, not weeks. Teams benefit from a smooth onboarding process. Expert guidance is available if needed, and a free trial lets you explore the solution with confidence.
Experience Refinder AI Search — Contact Us or Join the Webinar
If your support team is overwhelmed by scattered information and repetitive queries, Refinder can help. It simplifies knowledge access and boosts customer service performance without adding extra tools or complexity. To see it in action, Contact us today or join our upcoming webinar!
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