Our client, a Florida-based retailer, was using qualitative techniques to forecast sales using limited available information: expert opinions and information about special events. Store sales are influenced by many more factors such as promotions, competition, school and state holidays, seasonality, locality, etc. They wanted to analyze historical data, to find patterns in the dynamics of the data like cyclical patterns, trends and growth rates. They also wanted to explore social factors influencing sales.
This is a major American designer and marketer of children’s apparel. The use of a line assortment application for mapping product attributes to facilitate planning. This process is manual-intensive and takes a lot of time. On average there are 130 attributes per product and around 4 million attributes are being managed per year. The sales and marketing teams needed a new, better way to describe the product. They wanted to leverage artificial intelligence for recognizing images of children’s clothing and predict labels with respect to certain attributes such as sleeve length, leg length, and patterns to reduce manual intervention. The situation demanded the need for an integrated platform for data scientists equipped with accelerators and tools to manage the entire AI application development life-cycle.
Press Ganey is a leading provider of patient experience measurement & performance analytics. They conduct a variety of patient experience surveys in hospitals and collect feedback to analyze every dimension of the patient experience. Healthcare providers are then provided a rating (on a five-point scale), based on the feedback. While it may be relatively easy to analyze the structured ratings provided in the feedback, additional effort is required for the analysis of unstructured comments. Reading all the comments in every section of each feedback form is humanly impossible.
Client – Multi-Asset & Macro (MA&M) are in the process of developing strategies that can be used in existing products, decision tools that can help in managing existing portfolio risks, and also the development of new products and solutions that combine both. The desired outcome is to optimize existing products as well as developing additional strategies that seek to exploit non-traditional risk premia such as value, momentum, or carry-based strategies. This work is currently being undertaken by various team members across MA&M. However, the work is generally siloed, manually intensive, and time-consuming, performed in an unstable environment, is not scalable in its current form, and cannot utilize the multiple, large data sets required. Additionally, there is no current resource available to store this data as a time series, which frustrates further avenues of analysis to be done. The situation demanded the need for an integrated platform for data scientists equipped with accelerators and tools to experiment, discover, share, and deliver insights. The xpresso.ai platform brings together best-of-breed tools into one integrated and intuitive platform.
An American multinational consumer credit reporting agency and is one of the three largest agencies. They collect and aggregate information on over 800 million individual consumers and more than 88 million businesses worldwide to create insights that help organizations make more informed decisions. The mortgage is one of the industries our client serves. They provide mortgage lenders with a 360-degree view of a borrower’s credit, capacity and collateral. Risk models eventually become less predictive or relevant due to evolving market conditions.
This is a major American designer and marketer of children’s apparel. The use a line assortment application for mapping product attributes to facilitate planning.