26 min listen
Understanding the Multiple Amazon Data Streams With Sreenath Reddy
Understanding the Multiple Amazon Data Streams With Sreenath Reddy
ratings:
Length:
42 minutes
Released:
Nov 17, 2022
Format:
Podcast episode
Description
Sreenath Reddy is the Founder of Intentwise, a technology platform that provides professional advertisers, large-scale aggregators, and high-volume agencies with automation, competitive intelligence, and data infrastructure for Amazon and other eCommerce sites. With more than 20 years of experience in the digital advertising and data analytics space, he utilizes AI to solve marketplace eCommerce challenges. Before founding Intentwise, Sreenath was the Senior Director of Marketing Strategy at Orbitz Worldwide. In this episode… When evaluating advertising and marketing campaigns, Amazon offers viable solutions to perform data analytics and generate key insights across multiple channels. But, with so many tools, including Amazon Attribution, Amazon Marketing Cloud, and Amazon Marketing Stream, how can you manage data effectively to optimize campaigns? When utilizing Amazon’s AdTech platforms, Sreenath Reddy emphasizes the importance of deploying a data strategy. This requires executing a multi-pronged approach to organize data practically and securely. The first step involves collecting and owning the key advertising, retail, and media data sets that the platforms generate. Next, it’s essential to evaluate individual use cases based on business goals so you can consolidate the data and view it holistically. Lastly, leverage forecasting or ad optimization strategies to deconstruct the data pieces for effective decision-making. In today’s episode of The Digital Deep Dive, Aaron Conant talks with Sreenath Reddy, Founder of Intentwise, about leveraging Amazon data sets to optimize marketing and ad campaigns. Sreenath discusses the factors influencing Amazon ad performance, the importance of combining retail and media strategies, and how to manage multiple data sets.
Released:
Nov 17, 2022
Format:
Podcast episode
Titles in the series (100)
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