Data Science

Knowledge is not useful in the hands of people that explore data all day. It is useful in the hands of those that don’t have that role in the organizations but need fast access to what data brings.

More than knowing what happened (Descriptive Analytics), high-performing companies need to know what will happen (Predict Analytics) and what actions they should take to make it happen (Prescriptive Analytics).

Those companies are using Advanced Analytics Techniques such as Machine Learning, Optimization, Sentiment Analysis, Cluster Analysis or Predictive Modeling to collect, analyze and process data that generate insights to make better business decisions, improving operations, creating smarter products and developing personalized marketing campaigns.

At Closer, we develop algorithms and customized mathematical models based on our Data Science, Data Analytics and Data Engineering experience, enabling companies to use the data at their disposal and converting it into competitive advantages.

Transforming data into wisdom

What are your business challenges?

Some examples that we address:

Customer acquisition

Should I approve this credit line?
Who is the best target for my campaign?

Customer usage and growth

Which campaign is the most promising one for which customer?
Which clients will buy a car and when?
Whom do we approach with a differentiated offer?

Risk and profitability

How can we optimize our pricing model?
How can we optimize our scoring models further?
Apply PufferFish portfolio optimization

Churn

Who will leave us and when? What should I do to avoid it?

Tools & Techniques

Case Study

Automotive

Vehicle Stock Optimization

Closer developed a data asset that comprises all the information to enable the development of insightful dashboards, mathematical optimizations and deep learning model training. It was also implemented local surrogate models so that a multinational automotive manufacturer understood the important features that drive sales.

Results

Improved vehicle stock levels;
Implemented best practices in data engineering and data science.

Case Study

Manufacturing

Optimize Distribution Orders

A data-driven approach to a specific logistics/industrial challenge: the development of an algorithm that optimize the distribution process of manufacturing orders to fulfill the whole production capacity within 3 different factories.

Results

€1.5M in savings per year.

Case Study

Banking

Customer Complaints’ Root Cause Analysis

Based on each customer's behavior and interaction with the bank via several channels, Closer developed a deep learning solution that identifies the possible causes of the complaint. The deep learning model allowed to calculate proximities between several entities, possible causes and the actions of each customer journey.

Results

Increase customer satisfaction;
17% reduction of complaints.

Case Study

Insurance

NLP Multi-Class Classification

Insurance agents are faced by the challenge of correctly identifying a company's Business Activity when selling products. Closer built a machine learning model to automatically classify the BA code of a company (composed of 6 hierarchical digits), based on its text description (german, french, italian and english). An hierarchical model composed of several machine learning classifiers was developed.

Results

89% accuracy for the first 3 digits;
75% accuracy for the whole 6 digits.

Articles

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