Michael Tambe, Head of Data Science for Amazon Advertising Field Sales, discusses the challenges and possibilities of building a data-driven go-to-market engine in retail. They cover topics such as aligning sales and marketing, optimizing the sales force, creating a data-driven sales strategy, and the challenges and opportunities of building data-driven go-to-market systems.
Read more
AI Summary
AI Chapters
Episode notes
auto_awesome
Podcast summary created with Snipd AI
Quick takeaways
A data-driven go-to market engine involves leveraging data to optimize sales, marketing, and in-product messaging, resulting in enhanced product offerings and improved customer experience.
Breaking down organizational silos is a significant challenge in the retail and e-commerce space, and companies need to connect the dots between sales and marketing to add value for salespeople and improve sales and customer engagement.
Deep dives
Building a Data-Driven Go-To Market Engine
A data-driven go-to market engine involves leveraging data to optimize sales, marketing, and in-product messaging. By continuously improving and delivering the right message to the right person at the right time, enterprises can enhance their product offerings and improve customer experience.
Challenges in Retail and E-commerce
Breaking down organizational silos is a significant challenge in the retail and e-commerce space. Optimizing sales force planning and ensuring sales productivity are essential. Companies need to connect the dots between sales and marketing, and focus on delivering the right insights and tools to add value for salespeople in their day-to-day activities.
Moving towards a Bottoms-Up View
A bottoms-up view involves gaining insights into salespeople's interactions with customers and leveraging those insights to improve sales and customer engagement. Companies need to close the loop and gather accurate information about sales activities. By providing sales reps with a centralized tool that saves time and delivers insights, companies can create a virtuous cycle and improve their bottom-up view.
Today’s guest is Michael Tambe, Head of Scaled Insight Science, Amazon Ads. Mike has led data science efforts in sales and marketing and leading edge companies like Amazon Ads and LinkedIn. Through these experiences he’s become an advocate of enterprises building a “data-driven go-to-market engine.” He joins Emerj Senior Editor Matthew DeMello on today’s podcast to talk about what that means, along with the challenges and possibilities of new emerging AI capabilities. To access Emerj’s frameworks for AI readiness, ROI, and strategy, visit Emerj Plus at emerj.com/p1.
Get the Snipd podcast app
Unlock the knowledge in podcasts with the podcast player of the future.
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode
Save any moment
Hear something you like? Tap your headphones to save it with AI-generated key takeaways
Share & Export
Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode