Businesses these days receive hundreds and even thousands of customer queries daily. For any customer service representative, it becomes tremendously difficult to keep track of these issues, specifically because of the three Vs


Volume

Velocity and

Variety


With inconsistent similarities between large amounts of incoming data along with the frequency of product updates, it adds exponential complexity to the process of unearthing trends in the data. This data can be created from various data sources including customer-created tickets, service requests, bots, customer reviews, case objects from different CRMs, help articles, or even FAQs. While these datasets share the same ground of belonging to customer interactions, they all can have extreme differences in terms of unearthing actual actions to be derived from them.


At Ascendo, we call these “Interactions”. What is common across these interactions is that they deal with symptoms/problems/ that a customer needs. Each of them needs an understanding of what the “root cause” of the request is. Then the root cause should be mapped to the relevant solution/knowledge to surface it back to the customer.