Challenge and selection:     I work in a company that provides financial solutions with a diversified portfolio of  customers. Our challenge was to reduce the percentage of calls of customers who did  not know about their transaction status or they are receiving a generic error and do not  know how to proceed or continue their operation.  Based on that, we decided to use the learning launch tool to test the idea of exchange all  the messages and transacción status for others more clear to the final user. We believe  that possibly improve the situation, by reducing the percentage of calls.      Application    With the idea of reducing the percentage of calls, we took one of the most used  transactions and we changed the messages that were received by the customers  (including the informative messages, status of transactions, warnings, and errors that  prevent continuing with the normal operation flow).  We set some parameters to find the flows we wanted to test more easily and we  contacted a group of clients with different needs (customers operating with corporative  and individual home banking with ages between 35 and 70).  We asked them to operate normally and naturally with the selected functionality (The  customer has to log in in the home banking, operated, and taking actions based on the  message they received on the screen.      Insight and approach    By applying the learning launch tool, the team realized that a percentage of customers  did not call the call center because they could be identified and understood the problem  and they have been able to solve by themselves.   The other percent had to call anyway because they needed some actions from the bank  to solve the problem. But here we could detect that the time of response of the call  center team decrease considerably because they already know the problem informed by  the customer and they knew how to fix it.   Besides, we realized based on the second group that there is a huge percent of messages  that requires some actions from the bank to continue the operation, and to decrease even  more the percentage of calls, we should take those problems, analyze them and take  some new actions.   We think that use the learning launch was the right tool to use to learn more about this  problem since we could implement an intermediate solution to solve the most important  inconvenience and, we could learn about other's “obstacles” to have even less percent of  calls.


Challenge and selection : I work in a company that provides financial solutions with a diversified portfolio of customers . Our challenge was to reduce the percentage of calls of customers who did not know about their transaction status or they are receiving a generic error and do not know how to proceed or continue their operation . Based on that , we decided to use the learning launch tool to test the idea of exchange all the messages and transacción status for others more clear to the final user . We believe that possibly improve the situation , by reducing the percentage of calls . Application With the idea of reducing the percentage of calls , we took one of the most used transactions and we changed the messages that were received by the customers ( including the informative messages , status of transactions , warnings , and errors that prevent continuing with the normal operation flow ) . We set some parameters to find the flows we wanted to test more easily and we contacted a group of clients with different needs ( customers operating with corporative and individual home banking with ages between 35 and 70 ) . We asked them to operate normally and naturally with the selected functionality ( The customer has to log in in the home banking , operated , and taking actions based on the message they received on the screen . Insight and approach By applying the learning launch tool , the team realized that a percentage of customers did not call the call center because they could be identified and understood the problem and they have been able to solve by themselves . The other percent had to call anyway because they needed some actions from the bank to solve the problem . But here we could detect that the time of response of the call center team decrease considerably because they already know the problem informed by the customer and they knew how to fix it . Besides , we realized based on the second group that there is a huge percent of messages that requires some actions from the bank to continue the operation , and to decrease even more the percentage of calls , we should take those problems , analyze them and take some new actions . We think that use the learning launch was the right tool to use to learn more about this problem since we could implement an intermediate solution to solve the most important inconvenience and , we could learn about other 's “ obstacles ” to have even less percent of calls .