In retail, product designers rely on experience and intuition, merchants use instinct to pick new items, and sourcing teams leverage their experience and relationships to identify new suppliers.
But what if these instincts could be shaped by reason and analysis?
At LiveWorx 2017, Kalypso's use case showed how to use ThingWorx Analytics to turn social content into data, and combine it with information about web and store traffic, sales and returns to see patterns and immediately act on them.
Kalypso can help you use machine learning to blend what you hear with what you know to make truly informed decisions. Analyze PLM product data, transactional data from sales and returns, and external data from additional sources like social media, fashion blogs and other websites, in order to identify opportunities to better meet customer needs and wants.
As the quantity of big data expands, retailers need to become more efficient at collecting, organizing and managing data. Here are some ways retailers can monetize data with machine learning.
Retail product development is changing more now than it has in the past 15 years. Leaders must transform their product development lifecycles to survive in a digital world, and PLM alone can't produce the required results. It's time for retailers…
To understand where leaders are focusing their product development transformation investments, Kalypso and Indiana University partnered on a research study of leading product development practices in the industry. Here are some key findings.
Siloed data. Unstructured data. Lack of connectivity. Lost opportunity. With all the data being generated and collected, internally and on the Web, machine learning can address the challenge of connecting the dots, drawing insights, and making…