Chatbots are penetrating more and more industries dealing with a high volume of repeating customer inquiries such as telecommunication, banking and insurance.
But are there valid use cases to deploy bots in industries like wholesale distribution with B2B processes and a B2B customer basis?
We from SAP think “yes”. Let’s go and learn from the experience that SAP has made with chatbots in the Digital Commerce Environment of the
Digital Store where customers can buy directly products and solutions from SAP web pages, very similar to other online shopping catalogs. We want to share our experience with you and try to apply it to Wholesale Distribution industry requirements.
What do we do?
SAP deploys bots behind the “Contact Us” button on certain product pages. The chatbot understands the context the customer is in and provides appropriate information with the highest speed, consistency and scalability, and it escalates to a human agent those queries that are too complex or specific to be handled by a bot.
To improve the user’s confidence on this tool, we give the total number of further steps the customer must go through before getting a final answer. This increased the adoption significantly.
We store each chat as ticket in our CRM ticketing system and extract anonymous business intelligence from the conversation to be analyzed through our SAP Analytics Cloud solution. The chat environment is treated as parallel customer inbound channel.
In general, we distinguish
4 main use cases.
- Direct Answer (with options)
The customer has a direct question that requires a direct answer: for example, “I want to download product X”. The chatbot guides the customer with simple questions though the required steps. As the product remains in memory, the user can move through related topics, e.g. from “download” to “install” to “license key” and continue to receive answers related to the same product. At the end the chatbot always asks if the query was answered, and we have markers for further analysis.
- Issues & workarounds
The customer encounters an issue that may be solved through some workarounds: for example the customer adds a product to a shopping cart, but encounters an issue and opens a chat: the chatbot understands the checkout context, and proposes a few effective workarounds; if none of them is effective, the bot will ask the customer to type the issue they are encountering, and will pass it to the agent in a structured format.
- Technical support
The customer has a product technical error: in this case the bot asks the customer to type the error they encounter, then it generates a dynamic link to search the customer input words in the technical knowledge repositories. We never lose the context of the support question and guide the customer through his search.
- Order update
A very common question every customer might have is for example “where is my order?”. The chatbot authenticates the user through Cloud SID and apply Single Sign On when deployed. Once authenticated, the chatbot queries the order database and provides customer specific information.
We think that all 4 use cases apply to Wholesale Distribution Industries, but especially the last use case regarding order-related queries should be of very high interest in Wholesale Distribution. The most recent improvement of SAP Conversational AI will soon be that it is able to identify customers through integrated Single Sign On. The features are expected to be available in Q3 of 2019. To provide customer-specific information by connecting to backend-systems, pulling and providing information in a secured and safe manner, should be a great step forward to apply chatbots also in a B2B environment like we have in Wholesale Distribution.
Further information, please explore our
sap.com page about
SAP Conversational AI.
