Business analytics and data analysis

Data analysis is the process that aims to highlight useful information in the data, to suggest conclusions, and to support the decision making of a business or organization.


With Business Data Analysis we are capable of understanding the business and the industry, formulating the right questions, and modeling data in order to understand past and current business performance, so future behavior can be predicted. We do this by applying data mining and simulation techniques, and by finding rules and patterns hidden in your data. With them we can understand the best and the worst-case scenarios. By applying modeling tools and techniques, we are able to isolate the causes for a specific event that took place, and we are able to detect further business opportunities.

Our broad experience in business and data allow us to work in two steps:

  1. We formulate the right questions and then find the data suitable for answering them. In order to make this possible, we must analyze which data is available, audit it, clean it, and finally consolidate it. If certain data is not available we suggest the best implementation techniques in order to start gathering it as soon as possible.
  2. We explore your data in a comprehensive way to find the business opportunities hidden in it.

Data must be understood as an asset allowing your organization to be on the head-start at the moment of offering your products or services.

As an example, we can list the following applications:

  • Customer Segmentation and RFM modeling
  • Customer acquisition and retention optimization
  • Up-sell and Cross-sell models
  • Product and basket association
  • Product recommendation techniques
  • Merchandizing and Pricing optimization
  • Shipping costs optimization
  • Discount codes optimization
  • Product discoverability
  • Customer lifetime value and Customer Profitability
  • ​Cohort analysis
  • ROI and attribution modeling
  • Fraud analysis
  • Anomalies detection

​To fulfill these services we rely on the best-of-class tools, such as:

  • R Statistics
  • Python
  • Knime
  • Rapidminer
  • SPSS
  • Excel
  • Clementine