Hidden potential. Enhanced decisions.

Boost your company's performance leveraging holistic data science and machine learning solutions.

Opportunity and problem analysis:

Let’s discuss the challenges you are facing. We are happy to discuss what problems you have and determine how to help you utilize your data, translate the question into data science problem and recommend the most suitable project with high ROI. Contact us for a free initial consultation.

 

Results and Deployment:

 

No data science project is finished until the results of the analysis are implemented or acted upon.

 

Data science services we do:

  • Identifying appropriate algorithms for the business-case being worked upon
  • Preparing data for modeling purposes
  • Developing Machine Learning and Statistical Models
  • Training models
  • Scoring data
  • Deployment of models
  • Retraining models

Use cases:

Credit scoring

Predicts creditworthiness of your repeated clients based on their past behavior or entirely new customers (application). We can provide services with regards to modeling and sustainability of your scorecard.
Input: all data available on the customers and their past performance
Output: credit score

Segmentation

Discover different types of customers and classify them based on their behavior. This allows you to align your marketing tactics and target marketing outreach to these groups. Using segmentation, you can discover new ways to form your business strategy.
Input: customer/item data
Output: customers/items split into coherent segments

Customer lifetime value

Shows an estimated prediction of your future cash flow. It will give you an idea what to expect from customers.
Input: data about behavior and cash flow on customer basis
Output: future estimates of expected cash flows


Churn prediction

Enables you to flag customers before they leave your service and launch retention campaign.
Input: usage data,
Output: churn score for every customer

Upsale and recommendation

What is the best product to offer the customer?
Input: information about other products bought, transaction data, customer data
Output: products, which are the most likely to be bought by a customer, next best product

Clients/projects: