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Being a Fierce Advocate for Yourself and Thriving During Career Transitions: Growth Stories Podcast


Aditya Reddy, a growth investor at Sapphire Ventures, joins this episode of the Growth Stories podcast! Growing up a multi-sport athlete, Aditya tore his ACL, which caused him to take a step back from his identity as an athlete. This became a pivotal point in Adtiya's life and helped strengthened his grit, tenacity, and confidence towards his career journey and transitions.


In this episode, Aditya offers some of the best practices for post-sales customer success or account management, the future of PLG, and why Net Dollar Retention is so important when investors look at company valuations.


Watch the full episode here, or find it on your favorite platform, and be sure to subscribe to the Growth Stories podcast!


Aditya Reddy joined Sapphire Ventures in 2021 as a member of the growth investment team. Prior to Sapphire, Aditya worked on the FP&A team at Sapphire’s portfolio company, Outreach, where he helped drive the consolidated top-line forecasting and reporting function for the business and supported the Marketing organization with ongoing business planning. Aditya began his career at J.P. Morgan in the Technology M&A group where he helped advise large technology clients on an array of strategic initiatives including M&A, divestitures and partnerships.


Aditya graduated from the University of California, Berkeley with a degree in Business Administration. Born and raised in the Bay Area, he enjoys playing basketball, traveling (adventure-style) and trying new foods.


involve.ai is an early warning system, like a credit score for revenue retention, that gives teams complete visibility into all their customers, allowing them to drive more revenue through smarter renewals and upsells. With the most up-to-date data, recommendations for action & collaboration across the customer journey, teams can proactively deliver an amazing customer experience.










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Our AI predicts customer behavior with greater than 90% accuracy. How do we know? We test and measure the performance of our models regularly, in a variety of ways. Model training test accuracy - 94

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