Data-Driven Amazon Forecasting With Todd VanderStelt and Sam Hager

The Digital Deep Dive With Aaron Conant

Todd VanderStelt is the Co-founder of MixShift, a firm that helps Amazon agencies, aggregators, and brands scale operations and reporting for their Amazon accounts. He is also the Managing Partner at Dash Applications, which delivers software to improve operations and sales for retailers and brands, and the Founder of TidalBore Group, a management consulting firm specializing in retail. Previously, Todd held leadership roles at Amazon, where he built forecasting tools and operational systems.

Sam Hager is the Co-founder and CEO of MixShift. He began his career in the Amazon space, managing multimillion-dollar business books across advertising and agency services. Before MixShift, Sam was the Marketplace Strategist and Amazon Advertising Manager at Booyah Advertising.

In this episode…

Forecasting in the Amazon ecosystem is one of the most frustrating challenges for brands and agencies. With so many shifting variables — from ad spend to competition to inventory fluctuations — how can companies predict sales and plan budgets without wasting resources or missing opportunities?

Amazon forecasting and automation veteran Todd VanderStelt and eCommerce strategist Sam Hager have developed a forecasting method for Amazon brands. They emphasize simplifying forecasting through a top-down model that uses a few key data inputs — ad spend, seasonality, and organic growth — to generate highly accurate predictions. Sam and Todd advise building forecasting tools that align teams around data, tie budgets directly to performance, and factor in real-world contexts, like promotions or unexpected press coverage, to make informed decisions.

In this episode of The Digital Deep Dive, Aaron Conant talks with Todd VanderStelt and Sam Hager, Co-founders of MixShift, about building accurate and actionable Amazon forecasting models. Together, they explain why top-down forecasting outperforms traditional methods, how linking ad spend to revenue improves planning, and the future innovations transforming eCommerce analytics.