Challenge
One of the leading telephone, broadband and pay television companies in Brazil, with almost 100 million subscribers in its service portfolio. Our challenge with the “New Client Acquisition” project was to increase the capture of new clients for the Postpaid mobile product, with a strategic focus on the prospect’s quality and lifetime value.
We developed a totally personalized solution for this objective: we created a predictive algorithm from socioeconomic, demographic and behavioral data with the most advanced machine learning techniques on the market.
Strategy
We developed a totally personalized solution for this objective: we created a predictive algorithm from socioeconomic, demographic and behavioral data with the most advanced machine learning techniques on the market.
This intelligence model was the basis for defining 30 behavioral groups, separated by the level of sales likelihood and lifetime value. The focus of the sales operation was directed at 10 clusters of greater likelihood (30% of the base), who used voice contact. Every 15 days, our algorithm handled the new information sent by the customer, which resulted in a continuous learning strategy with the tool and the work teams.
As a result of the algorithm’s intelligence, we streamlined our service, managing to combine human and robotized service through the use of virtual agents. We used the robots to start contact with the middle- and low-likelihood groups, and transferred service operators with a greater success rate, increasing thus the capture of prospects.
This intelligence model was the basis for defining 30 behavioral groups, separated by the level of sales likelihood and lifetime value. The focus of the sales operation was directed at 10 clusters of greater likelihood (30% of the base), who used voice contact. Every 15 days, our algorithm handled the new information sent by the customer, which resulted in a continuous learning strategy with the tool and the work teams.
As a result of the algorithm’s intelligence, we streamlined our service, managing to combine human and robotized service through the use of virtual agents. We used the robots to start contact with the middle- and low-likelihood groups, and transferred service operators with a greater success rate, increasing thus the capture of prospects.
Results
+47%
sales conversion
+45%
credit approval rates
+21%
customer contact rates
This project is an example of the application of our methodology of business analytics with operational management and technological innovation in a strategic client for the ecosystem.
Sales productivity increased 47% through the change from a random system of contacts to a system centered on intelligence, performance optimization and technological innovation, in which we combined strategy and customer goals with our operational work.
Major insights were identified in the socio-economic, demographic and behavioral profile of the public in question, which allowed us to intensify the growing trend in results and, at the same time, the creation of different, more assertive offers by the customer.
