Today we can finally see the consumer version of what futurists, writers, and filmmakers have been conceptualizing for long: AI that can predict events and outcomes even before they happen. When Isaac Asimov foresaw cars with “robot brains,” he described a fictional technology that would fuel such an invention. Seven decades later, autonomous cars are a reality because of AI’s ability to analyze vast amounts of data from sensors, cameras, and other sources. And these proactive, predictive, and preventative capabilities of AI are equally applicable in almost any industry today, for example in healthcare with AI-powered wearables, retail with optimization of inventory for high-volume sales, or manufacturing with maintenance through anomaly detection.
When it comes to customer support, these capabilities are game-changing not only for current applications but also for future implications. The way businesses deliver support is improving every day, thanks to the rapidly evolving framework: technological breakthroughs, business innovations, and process agility. Here are six key methods that can transform the delivery of customer support.
1. Real-time monitoring
With AI-infused features in diagnostics, an electric car can detect potential malfunctions and schedule its own service appointment automatically, preventing issues like battery depletion or tire pressure drops before they become critical.
How does real-time monitoring play out in the world of business software? SAP Cloud ALM provides a feature-rich observability platform that can collect telemetry data, like metrics, logs, and traces, from applications and their supporting infrastructure, allowing support teams to review the health of these systems. By providing real-time analytics and a centralized dashboard, SAP Cloud ALM helps empower IT teams to quickly respond and fix issues, so the business remains operational with minimal interruptions. Additionally, the use of OpenTelemetry standardizes observability within a modern customer landscape.
“The SAP Cloud ALM solution has been instrumental for our IT operations. It offers real-time insights and seamless integration across all our enterprise applications, making everything run more smoothly. It’s like having a bird’s-eye view of our operations, ensuring efficiency and helping us stay proactive rather than reactive.”
Omprakash H, Senior Director, Blueprint Technologies Pvt. Ltd.
2. Proactive resolution
Customer feedback loops play an important role in improving products and services and refining customer relationships. Repeat requests, in customer and user feedback, help service providers identify critical needs and also prioritize features to be delivered.
For example, users within SAP Business Network and SAP Ariba solutions go to the help center for self-service or case assistance 10.8 times less than they did years ago. This drop in end-user support sessions is the result of features that have been built into the product, based on customer feedback.
AI-enabled outbreak detection is another significant process in proactive resolution that allows support teams to address unexpected increases in anomalies, customer complaints, or issues.
“We continuously identify the reasons for frequent customer demands and challenges from inquiries raised to SAP support. This allows SAP to proactively deliver the most impactful product changes before they become a challenge for more customers. This way, we improve our products while also focusing on key product capabilities used by our customers today.”
Alexey Ukrainsky, Solution Support Architect, SAP MCC
3. Predictive analytics
In the retail industry, predictive analytics is used effectively for proactive and preventative support. One prominent example is SAP’s holiday season readiness program, which helps position SAP as a front-runner in AI-driven, predictive, and proactive support solutions. With the goal of issue prevention at its core, the program can provide a comprehensive, 360-degree customer support profile, helping to accelerate issue detection and anticipate potential problems with AI-driven features like a virtual support assistant, resource prediction, web traffic prediction, a recommendation engine, case history analysis, issue correlation, and pattern recognition.
“During Cyber Week 2024, SAP’s holiday reason readiness program equipped our support and ops teams to achieve 100% uptime for our customers with the predictive, proactive, and bi-directional support model implemented by the program.”
Tarun Luthra, Head of Support, I&CX Solutions
4. Customer journey mapping
SAP Signavio solutions can help businesses visualize the end-to-end customer journey, tracking interactions across different touchpoints. This enables companies to identify areas of improvement in their customer support processes, leading to more personalized and effective interactions.
With the help of SAP Signavio Process Intelligence, SAP can successfully map support processes to help implement AI improvements for optimizing our services. The result: a 100% increase reported in customer value.
For example, a business that struggles with connecting customer experience data and operational data can take advantage of the SAP Signavio Journey-to-Process Analytics solution to help reduce time to insight and uncover anomalies and trends.
“The challenge in increasing our customer experience lies in the direct link between process and journey activities. I see SAP Signavio solutions as the perfect tools for consolidating these two perspectives to develop operational excellence in step with customer experience.”
Stefan Gammel, Business Process Consultant, Hilti Group
5. In-app support
Seamlessly integrating support features in a product, service, or system gives users easy access to directly request assistance within the interface, without needing to contact a support team or leave the platform. Built-In Support can include contextual, AI-assisted, self-service options like help application-specific documentation, troubleshooting tools, knowledge bases, and FAQs or real-time options like live chats with support engineers.
For example, WalkMe solutions and Built-In Support—layered over multiple applications in a business workflow—can provide real-time, proactive, in-app guidance to users, helping to significantly reduce the need for live assistance or support tickets.
“Context significantly enhances the quality of support. Built-In Support works like a pit stop at a racetrack. The repair crew is right where the action is. The interruption is brief and far less disruptive than taking your car to the workshop, ensuring a smoother return to your activities. In the context of your company, this helps you win your business race.”
Wilhelm Jütte, Chief Product Owner, Customer Support, SAP
6. Proactive mindset
None of the tools and processes that we deploy to implement a proactive and preventative support strategy are sustainable if our teams are not tuned to a proactive mindset. I believe high-performing support teams deliver the best results with a combination of human-machine collaboration, in a culture that promotes a forward-thinking, outcome-driven, service-oriented, and data-driven mindset.
At the end of the day, the best issue is the issue that we can prevent. Proactive and preventative support is not just about solving problems, but about creating peace of mind for end users, customers, partners, and support engineers so every customer receives custom care, even before they need help.
“Knowledge management within support is not just about enabling self-service through portals to deflect incoming tickets, but about eliminating the need to come to the support portal in the first place.”
Derek Matthews, Technical Support – Procurement Chief Innovation Officer, SAP
Stefan Steinle is executive vice president and head of Customer Support & Cloud Lifecycle Management at SAP.
