The foundation of self-service automation is its knowledge
base. Each entry in a knowledge base should answer a question and solve a
single problem clearly and precisely from start to finish. In order to function
optimally for self-service, it has to be robust, organized and, above all,
accessible. This means that articles in an online content library are highly
searchable. Self services can be made available to customers in login-protected
areas or as a chatbot that can answer questions about products, services,
orders, etc. directly.
Chatbots
and NLP support self-service automation
As part of self-service automation, chatbot technology
enables the right content to be displayed to the right people using, for
example, keywords and machine intelligence. More and more people prefer chatbot
interactions in customer service, as chatbots can solve problems quickly and
answer questions precisely without the customer having to wait and thus
contribute significantly to a positive customer experience. A recent study has
shown that 80 percent of customer inquiries are resolved by chatbots without
the intervention of a customer service representative.
Using Natural Language Processing (NLP) and Machine Learning
(ML) helps the bot understand the quirks and variations in the way people type
or speak. It helps the bot understand the customer's intent in order to keep
track of relevant item recommendations. ML allows the bot to get smarter over
time, so its accuracy will continuously improve. With the right self-service
automation, customer inquiries can even be processed completely automatically
by using the appropriate knowledge based on the recognized category and
context.
"Robotic Process Automation" factsheet
Download the RPA factsheet as PDF now
Self
service evaluation
Self-service automation delivered through workload automation
or an enterprise scheduling platform can typically be connected to any
application or system in the organization. This leads to a potentially endless
list of use cases for self service automation.
Given these prospects and the undisputed benefits, many
companies are tempted to automate all services as self-service. But not all
service cases are suitable for delivering a good self-service experience,
especially when the automation of the service workflow is limited.
In order to identify the services suitable for meaningful
and successful self-service automation, each use case should be checked for
• which self-service benefits can be expected for the
company and the customers and
• how complex the implementation of self service is, which
is determined by the sequence of activities required to complete a service
request, e.g. For example, creating records, obtaining approvals, or running
scripts.
Giving in to the "first come, first served" urge
is certainly not a good decision. The added value of an automated self-service
depends crucially on the degree of coverage of the self-service results with
the findings from the customer journey analysis. The number and type of
activities necessary to provide the service, the requirements for user input,
and the security and data risk, including regulatory and compliance risks,
determine the complexity of the solution.
globalmarketingguide bloomersweb techbizcenter marketing2business
upticktechnology
