Tigo Guatemala - Case Study

Tigo Guatemala has trusted ACF Technologies because our company has provided the required control tools that Tigo needed. ACF Technologies has a user-friendly platform that allows a 360- degree view of the events that happen daily.

When the customer enters the shop, Tigo can use the information and tools for offering excellent service. The client joins the queue with their phone number through a kiosk, therefore the customer feels that the service is organized and customized. The system is capable of measuring the wait time, the number of clients that arrive at the agency, the reason for the visit, and the customer service time. The users can see the productivity of the employees and they can also see the reasons for inquiries.

ACF Technologies also included the recordings management service (Sense Ear) in each desk so that is possible to monitor and record each conversation. This function allows Tigo to find opportunities for improving each detail of the user experience.

The Results:

When implementing Q-Flow, an NPS (Net promoter score) higher than 65% is projected, thus providing a satisfactory experience throughout the visit to Tigo Guatemala clients. Q-Flow is the basis for any report or study that is required on the business operation.

Tigo has had significant progress on the administration and control of the following areas:

• The visit records are organized by the user
• The system shows the agents’ productivity records and the most suitable agents for each agency
• The system has improved the customer B2B and B2C classification in order to increase the quality of customer service and it offers the most attractive proposals for customer segments
• The customers should not wait for more than 15 minutes in each transaction. The maximum time is 50 minutes on a busy day. This led to a 45% reduction in waiting, which reduced dropouts
• In relation to waiting time, previously it was averaged at 25:00 minutes, currently, it has been reduced to an average no greater than 18:00 minutes, thus supporting that the longest waiting time of a client does not exceed 21:00 minutes in line
• By having this adjustment in the attention times, it was possible to obtain a productivity per store and assistant of 85% and the occupation of the shop staff did not fall below 95%
   

The data generated by Q-Flow is complete and concise since it details each case or ticket generated, in waiting time, service time and the tabulation entered by the assistant and this allows us to know; when, why and who served our client.