Leading Telecom Operator Understands Customer Pain Points in Greater Detail With Text Analytics

500%

ROI

Of the customer rescue program in the 1st year after implementation

34%

reduction

Of the customer rescue program in the 1st year after implementation

92%

of superdetractors

Are precisely identified due to the high accuracy of the model

The business problem

Our client, a leading telecom provider has had a working Voice of the Customer program for a long time and the Medallia platform has been instrumental in the continuous transformation of the company. In 2020 executives felt that the current text analytics framework was no longer the best fit to the changing nature of business, because of the onset of global COVID-19 pandemic, internal restructuring and other factors.

In pursuit of delivering a greater customer experience, they wanted to have a greater understanding and quicker identification of unaddressed customer pains and follow up closely how customer feedback evolves while the company introduces different changes.

Our Solution

In 2020, our client engaged GemSeek to create a customised text analytics code frame and apply it to open-ended feedback in the platform. GemSeek made structural and content changes to more than 10% of the topic tree to reflect the changing business requirements and emerging needs in a more comprehensive way. The new code frame covers 230 touchpoints across 5 business segments and allows real-time analysis of millions of customer comments as they come into the system.

Achievements

As a result, the volume of tagged customer comments expanded by more than 35%, leading to a general increase in the quantity and quality of meaningful insights.

323 users from various functions and departments now have a real-time access to these insights and use them to initiate short- or long-term improvements to different business aspects.

NPS improvements in particular areas, due to actionable insights derived from TA
New offers (e.g. new TV package, new mobile subscription plan) developed, based on customer needs identified by TA