TMW Case Study #001 | Scaling Martech QA with computer vision and robots

Making Sense of Martech

Welcome to our very first TMW case study! Kicking off this series, we’re featuring Rappi, the Latin American super-app that connects consumers with merchants that sell a wide variety of products, and drivers that can bring those products to their doorstep. The three-sided business is not only a logistical challenge, but also a Martech challenge.

Rappi’s array of marketing campaigns and offers, driven by a sophisticated deep-linking strategy, is crucial to its success. It did, however, lead to the need for an impossibly large amount of QA to ensure the successful delivery of customer experience workflows, ensuring that would-be customers don’t fall off their buying journey at any point, from clicking on an ad through to landing in the app and making a purchase.

Leading the Martech and Adtech practice at Rappi is Satya Ramachandran, who brings over 12 years of Martech experience to the table, having previously worked as a data engineer building distributed databases.

In this case study, we’ll walk through how Satya not only scaled the Martech QA process using computer vision and robots, but turned QA into a profit-driving initiative with champions throughout the business, rather than just a cost center.

Satya’s responses have been edited for clarity and congruency.

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