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  • 47% increase in sales conversion

    One of the largest telecommunications companies in the country
    challenge

    The customer’s need was to attract new customers for the postpaid mobile product in the most efficient way possible and to focus on prospects with the greatest lifetime value

    "As part of our business analytics solution, we created a custom predictive algorithm analyzing socioeconomic, demographic, and behavioral data."
    solution

    As part of our business analytics solution, we created a custom predictive algorithm analyzing socioeconomic, demographic, and behavioral data. We defined 30 groups based on their purchase propensity and lifetime value. The customer submitted new data every two weeks which was used to update the groups.

    We combined human with virtual agents: the robots began the contact with groups of medium and low propensity to purchase while human agents focused on the groups with the highest purchase propensity as well as on the successful contacts initiated by virtual agents.

    results

    We managed to increase sales productivity by 47%. We also identified important insights into the socioeconomic, demographic, and behavioral profile of the prospects that were contacted which resulted in the creation of further successful offers by the customer.

    We also managed to increase the performance of the operation on the following terms:

    • We improved customer contact index by 21%
    • We increased the credit approval rates index by 45%
    • We reduced the First Pay Default index by 30%
    • We kept the quality indicators at levels of 95%