Getting Started with Machine Learning in Retail
While There's No One-Size-Fits-All Approach, Getting Started Isn’t as Scary as You Think
Machine learning (ML) has the potential to transform enterprises in almost all industries especially retail. From fraud detection, buyer segmentation, product recommendations, to inventory/supply chain and price optimization, the benefits to retailers can be a game-changer.
So, how do you start benefiting from machine learning? What are the common misconceptions when starting down the path of applying ML?
While there’s no one-size fits all approach, our experts provide candid insight on everything machine learning, including four areas where retailers can apply ML to yield measurable results, AWS tools to get started even faster, and the seven steps to follow when selecting your first ML project.
Retailers that don't wade into the ML pond may soon find themselves falling behind the competition. This white paper makes helps you get started.
Specifically, this whitepaper explores:
- What machine learning is (and is not), as well as critical misconceptions that can derail your ML project
- The challenges and pitfalls retailers face starting with ML
- Seven steps for selecting your first ML project (and avoiding all those pitfalls)
- The most significant opportunities for retailers to boost the customer experience, revenue, and operational efficiencies
- The difficulties in getting started (and why there's no one-size-fits-all answer)
- How to get off the mark, into production, and start benefitting from ML