I recently caught up with Paulo Sampaio, Data Scientist at EDITED, to talk about applying machine learning, neural networks, natural language processing, and big data analytics to the retail industry. Paulo and his team are applying neural networks, machine learning and other models to analyze over 520 million products in real-time across 42 countries to make gradual distinctions in clothing styles, sizes and categories.
Set against a backdrop of declining profitability and significant changes in consumer lifestyles, retailers are under pressure to deliver the best freshness and optimal availability to their customers without the ability manage cost to serve. Typically, 40 percent of grocery revenue is driven by fresh, according to the latest McKinsey report: get this right and the rest will follow, including the customer and profits. Grocery has traditionally struggled to deliver the right customer experience in fresh without forsaking margin.
Few industries have greater access to data around consumers, products, and channels than the retail industry. Data coupled with insights are at the heart of what drives this business. It’s a logical consequence then that retail is the vertical market that adopted big data and technologies like Hadoop earlier than many other industries. Retail started with diverse transactional data but is now much more sophisticated in the way technology is being applied toward gaining competitive advantage. Learn more by downloading this guide.
ClearStory Boosts Top-Line Growth with Automated Analytics that Blend Disparate Data Sources Into Insights
ClearStory Data, the company bringing business-oriented Analytics and Data Intelligence to everyone through fast-cycle, disparate data analysis, announced faster, more meaningful brand analytics insights.
In this new insideBIGDATA Guide to Retail, the goal is directed toward line of business leaders in conjunction with enterprise technologists with a focus on the above opportunities for retailers and how Dell can help them get started. The guide also will serve as a resource for retailers that are farther along the big data path and have more advanced technology requirements.
This article is the first in a series that explores a high-level view of how the retail industry has been influenced by big data technologies.