A few years ago, mobile phones did not have functions that nowadays we consider part of our routines such as video chat and music streaming. Today’s smartphones, moreover, have evolved to include integration of functions like camera, mobile payment and various apps. Similarly, customer care approaches have developed along with cellphones. Historically, the inability of businesses to afford real-time analysis meant that customer care was mostly reactive, dealing with issues as they arose.
In an era of real-time data, this backward-looking strategy presents a challenge companies need to overcome to understand customer behavior and boost business performance. Organizations now aim to retrieve information from past, present and future to gain a comprehensive view of their processes to forecast events and identify anomalies. Consequently, the outcomes expected will be the result of anticipated preparation and planning.
At SAP, the vast repository of historical issues, combined with extensive product knowledge and expertise, forms a rich foundation for preventive support. Some of the best practices to implement successful preventative customer care involve:
- Using robust automation systems and AI models to process issue signals quickly.
- Providing self-service opportunities through knowledge bases and chatbots.
- Offering proactive support through notifications and updates.
AI and Machine Learning, alongside various data points and automation, enable us to identify patterns and issues, and to implement automated mitigation actions to prevent customers' business impact at early stages.
Furthermore, the potential of insights from critical event data as a strategic asset has expanded its use beyond traditional areas like marketing and sales. Now, departments such as customer service, finance, and operations management are also adopting this strategy. To assess the effectiveness of our customer care efforts, SAP employs several key metrics, including:
- Customer Satisfaction Score (CSAT) and Net Promoter Score (NPS).
- Customer Effort Score (CES) to rate how effortlessly customers were able to receive support.
- Reduction in support calls or inquiries.
- Production uptime and availability.
In this way, we monitor our progress while refining algorithms based on real-world feedback and performance metrics. For our customers, preventive support means an increase in reliability of their system that will lead to customer satisfaction. Additionally, they adapt to changing scenarios, therefore decision-making process will be based on real-time information.
Having successfully exercised this approach to support SAP Commerce Cloud customers during 2024 Black Friday and Cyber Monday sales events, we are at the moment expanding this model across other SAP products.
Just as smartphones have become essential through the integration of diverse functionalities, our preventive support approach seeks to be crucial in proactive customer care. As we continue to refine our AI models and expand our prognostic capabilities, we're committed to staying at the forefront of innovative solutions that keep businesses running smoothly.
At SAP Sapphire 2025, which will take place in Orlando and Madrid, we’ll hold sessions with experts to show how we support customers to better predict issues.
Check out this SAP News Center article to learn how proactive customer care can drive success during peak e-commerce sales periods.
A special thanks to SAP experts Bharath Ramamurthy, Vice President of Strategic Initiatives, Customer Support, and Martina Kiely, Business Lead of Technology & Transformation Office, Customer Support Experience, for their contributions to this article.
