Improving PayPal's NPS with Conversational analytics.

We’ve been partnering with PayPal for 16 years now. Their ambition is to provide the best customer service and the safest interactions. We’ve been able to overachieve and reach their dream NPS target of 60+.

PayPal trusts us to take care of their most important relationships - the ones they have with their customers. We do that by providing customer care in digital and voice channels in French, Italian, Arabic, and English, in the French, Italian, Middle East & Africa, and Canadian markets.

By investing in operational improvements and digital solutions we managed to achieve 62.88 NPS and reduce RCR by 8.52%.

The solution. 

One of the key drivers of these improvements was the Center of excellence we built for them. This way we were able to discover areas for improvement and suggest multiple solutions, one of which was implementing a conversational analytics tool in order to improve NPS.

By using conversational analytics, we’re able to monitor 100% of recorded calls and written conversations to analyze the customer and agent sentiment. What is Sentiment? As it applies to customer service and contact centers, sentiment is generally referred to as a method of measuring emotion in customer and agent interactions. The reason behind this measurement is to analyze interactions to uncover areas of improvement.

Using sentiment to score agent interactions removes the need for random sampling because the interactions are already scored. It also empowers quality programs to analyze 100% of interactions to get a true sense of trends and the reasons behind them. The sentiment model takes into consideration: 

• Language used by customers and agents can indicate a positive or negative sentiment
• Laughter detection can indicate a positive change in an otherwise negative conversation 
• Cross-talk (where the agent and customer talk over each other) might indicate confusion or frustration
• Changes in pitch and tone or speaking rate can signal changing satisfaction during the interaction

Conversations with negative sentiments most often result in lower NPS. So we decided to do callbacks to each customer that exhibited negative sentiments in conversations with our agents. High-performing and senior agents would call these customers within 24h after the initial interaction and talk to them about the issue they had, in an attempt to increase their satisfaction with the support we provide. 

The results.

In the span of just six months, we were able to increase NPS by 6.85 pts thanks to 11.586 callbacks made by the sentiment task force (composed of 4 extra mentors fully dedicated to this task) with a 70% success rate, and we indirectly helped in reducing almost 1% in Recontact rate.

Being the client’s Center of excellence for this tool worldwide, we’re able to create queries that can be validated and improved to ensure the accuracy of data. Additionally, the team grew by 4 more people after the original results and started work on 300 more queries.