SCHICKLER Data Science

90% of all data available worldwide has been generated in the last two years. Less than 1% of all data available worldwide are analysed at all. This discrepancy impressively demonstrates the potential of data science in companies.

Especially for media companies, there are great opportunities because the processes and business relationships to customers and companies are particularly diverse. Artificial intelligence and machine learning create many opportunities for media companies, especially when it comes to improving existing products, services and processes.

SCHICKLER has its own in-house data science team to support media companies in the use of artificial intelligence. This team works hand in hand with the SCHICKLER consultants in projects to identify opportunities for the use of artificial intelligence, to develop algorithms and to program prototypes.

Some examples of how media companies can use Artificial Intelligence:

  • Which advertising customers should be addressed when with which offer? Where are there upselling opportunities, which customers have the highest sales opportunities?
  • Which reader should be addressed for an e-paper upselling? Who has the highest upselling chances?
  • How can an online reader be classified in real time to decide what content needs to be before and behind the paywall to increase conversion to a paid content subscription?
  • In which districts of the delivery logistics must problems be expected the next day? Based on historical data, weather, print specifications, etc.?
  • How can problems in the production process be predicted, for example in print shops, in order to be able to act proactively?

Some examples of the expertise of our Data Science team:

  • Data Cleaning
  • Data Enrichment
  • Explorative Data Analysis
  • Pattern recognition
  • Prediction & Forecasting
  • Recommender systems

A selection of the algorithms we use:

  • Feature extraction and mapping
  • Convolutional Neural Network
  • Supervised Learning
  • Tree-based ensemble learning
  • Classifiers
  • Regression analysis

Examples of our data science projects

Whitespot Analysis

We create transparency about your data, quality and possible use cases of artificial intelligence in your company.

Data Ready Organization

We analyze and cleanse your existing data and make your organization and processes “data-ready” so that you continuously store the most important data efficiently.

A.I. Algorithms

We develop algorithms for your artificial intelligence applications and take your products, services and processes to the next level.

Establishment of in-house teams

We support you in setting up, developing and training in-house data science teams and create the optimal processes for interlocking with your organization.

Data Science Toolset

Wir haben das Know-how

Schickler bringt zwei essentielle Komponenten für erfolgreiche Data Science Projekte mit: 1) Unsere Schickler Berater haben tiefes Verständnis über Prozesse, Systeme und Strategien von Medienunternehmen. 2) Unser Data Science Team hat tiefes technisches und analytisches Know-how rund um Künstliche Intelligenz, Algorithmen und Datenanalyse. In Data Science Projekten kombinieren wir diese Komponenten und schaffen das optimale Projektsetup für erfolgreiche Projekte.

Some of our data science experts

Dr. Christoph Mayer

Head of Data Science, Senior-Principal
  • Doctorate in Computer Science, Karlsruhe Institute of Technology (KIT)
  • with Schickler since 2012, over 100 projects in media companies
  • Focus on strategy, organizational and process optimization
  • High competence in the use of artificial intelligence in media companies
  • Head of Data Science at Schickler

Ole Martin

Data Scientist
  • Doctorate Mathematics, Universities of Kiel, Marbug, Hamburg
  • with Schickler since 2018, several years of consulting experience
  • Stochastic analysis, high-frequency statistics
  • Development of complex data science algorithms
  • Machine Learning Algorithms, Classifiers and Recommender Engines