A ‘No-Touch’ Customer Service

Author – Siva Ulaganathan, SAP CX Expert, NTT DATA Business Solutions UK

While customer experience is the sum of all interactions that the customer has through various touchpoints, often it is the interaction with the customer service or support that leaves a strong emotional impact with the customer. Customer experience is a quotient of the customer’s emotional connect with the brand!

While it is important that customer service, as a process area, gets maximum attention to improve customer experience, it is equally important that the related costs are also kept under control to not affect the bottom-line. Historically companies have adopted a low touch customer service model to this effect, but with SAP Conversation AI it is now possible to implement a ‘No-Touch’ model to improve customer experience and at the same time keep the costs down.

Conversational AI Concepts

SAP Conversational AI is a cloud based platform to develop and deploy ChatBots that can integrate seamlessly with enterprise applications including S4 or C/4HANA. Development is intuitive with no coding requirement and both front end and back end integration is seamless using industry standard protocols. With built-in natural language processing & sentiment analysis, SAP Conversational AI is able to provide a positive ‘human interaction’ experience to the customer.

Business Use Case

Let’s consider a business use case. A customer has placed a high value order through the company’s eCommerce platform and chose next day delivery. While the eCommerce platform provided a positive experience for the customer by providing a very intuitive and easy to use sales channel, the customer has experienced a delay in the delivery and is required to get in touch with customer service to get this resolved.

SAP Conversation AI ChatBot has been integrated with S4 to retrieve the delivery status of the order and when the customer is frustrated with the delay in delivery, it is able to quickly understand the sentiment and creates a high priority ticket with the customer details in SAP Service Cloud, and updates the customer accordingly. The ticket will be routed in SAP Service Cloud based on priority with the delivery prioritised and the customer updated as per the SLA to close the loop.

SAP Conversational AI – Implementation Components

Intents: Intents are expressions that the BOT understands and is able to relate to a topic. Some of the intents for the above use case would be ‘greetings’, ‘delivery-status’ etc. There is a library of intents for common use cases which can be ‘Forked’ into without creating one every time.

Entities: Entities are ‘information’ captured during the conversation. For example, order number in the above scenario is a custom entity. Apart from the custom entities, there is a list of standard entities called Gold Entities which are automatically captured by the system and can be used in the conversational flow.

Skills – A skill defines the action which is performed in response to a customer interaction. This can simply be answering a basic question or can be complex as performing an API call to a backend system to retrieve or update information. In the above scenario, get-status or create-ticket are examples of skills which perform the API call to backend systems.

Once the components are created, the BOT can be trained and deployed onto the runtime environment.

Integration with backend (C4 and S/4HANA)

SAP Conversational AI integrates with backend systems using WebHooks. WebHooks are defined in the actions inside a skill which means these are triggered during the conversational flow as required.

The OData services in C4 or S4 can be exposed as WebHooks either though a node.js application built on SAP Cloud Platform or as a HTTP endpoint in Cloud platform Integration (CPI). CPI integration would be better suited in an enterprise scenario although this depends on the business use case.

Integration with front-end

SAP Conversational AI provides out of the box integration with a number of social media & AI channels including Amazon Alexa, Skype/Cortana, SAP JAM/Co-Pilot, Twitter etc. Apart from these the most common use case would be integration with the company website or the eCommerce platform for which a code snippet is provide which can be copied into the relevant web pages to quickly enable the ChatBot.

Conclusion

SAP Conversational AI provides an easy to use platform for a faster implementation of ChatBots that can be integrated with enterprise applications. As businesses are increasingly transforming to the digital world, it is imperative to provide a tailored and personalised experience to the customers in all interactions. SAP Conversational AI is the right step in that direction and is an important component in implementation of customer experience journey in the digital world!!

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