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Reduce warranty exposure using customer complaints data
Artificial Intelligence, Machine Learning

Reduce warranty exposure using customer complaints data

Technological evolution has brought in with it many troughs and tresses. The awareness about rights that customers enjoy is at its zenith, alongside access to information makes them spoilt for choices.

Customer satisfaction becomes the centrifugal force behind the success of an organization. Once bitten twice shy, true to this, if there has been a challenge in a particular aspect, and a warranty ticket has been raised, it becomes imperative for the companies to rectify it in the current machine/model and ensure that the same defect is eliminated from the ‘to be made’ machine/model.

When a customer arrives at the service center, his or her description about the issue is rather vague with mostly the sounds or experience which do not directly indicate the actual problem. The Service Agent needs to then arrive at the possible solution and the part where the crisis lies.

Such situations arise at every point where the problems are explained in vague words and the experts are to decipher these and come up with specific solutions to ensure that these problems do no repeat.

There are deeper issues as these external elements that are seen are superficial and technicalities involved in resolving the actual problem may be multiple.

One Automotive manufacturer wanted to focus on these two aspects- giving high quality – next vehicle, and understanding the challenges faced by the existing user to minimize warranty issues.

Challenge on hand:
  1. Picking on intricate details of a warranty issue that a client has raised so as to find the root cause of it.
  2. Implementing those changes in the next production to eliminate more warranty issues.
  3. How does one identify those LCDs- Little chunks of details so time and money is saved?
  4. Who would help them?
Solution:

Intuceo used its expertise to adapt processes in order to resolve these issues. The comments that were given by the customers were deciphered and coded appropriately so the system could help the Engineers to rectify the same in the no time so the customers were satisfied and the warranty issues came down too.

Process:

Natural Language Programming is a process that was used to decode the warranty issues raised by the customers to boil it down to the minimum.

Business Impact:
  1. Improvised designs and quality.
  2. The above factors lead to saving time from days to minutes.
  3. Enormous wastage was saved helping the company save costs.