How dataPlor's Datasets Helped American Express Expand In Mexico

After using a competitor's dataset which was only 10% qualified, American Express used dataPlor's dataset - 90% qualified - to successfully expand in Mexico

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The Challenge

American Express (Amex) among the top five largest providers of credit cards in the world, needed to expand its footprint in Mexico. The company sought to acquire more customers in the coveted, high-end restaurant and retail segment. The sales and marketing team wanted to target high-end small businesses with patrons that were commonly American Express cardholders.

First Approach: Bad Data

Unfortunately, Amex's initial approach did not go as expected. After utilizing a competitor’s dataset, their sales and marketing team realized the 90% of the records were bad. This resulted in significant operational inefficiencies, unqualified leads, and wasted time and money.

dataPlor Solution

Next, American Express sought dataPlor's help to obtain qualified data sets uniquely suited to their needs.

dataPlor's deployed its on-the-ground field team to visit high-end small businesses. They asked decision makers qualifying questions and used proprietary mobile technology to capture complete comprehensive business information.

The hand-collected, human-verified database was turned over to American Express. Its sales and marketing teams were able to leverage dataPlor's datasets on their calls, dramatically increasing their rate of customer acquisition. The lead on the project, Amex's Merchant Business Development manager recognized the dramatic difference between their old data and dataPlor's data:

"dataPlor's leads were 90% qualified versus 10% with a previous vendor."

Prior to engaging dataPlor the sales team wasted valuable time on data that was only 10% qualified from a previous vendor. With dataPlor's highly accurate dataset, it could move forward with expansion plans in Mexico.

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