Data Science and Advanced Analytics

Take advantage of advanced analytics and machine learning for your future growth.

Today, middle-size and large companies have plenty of data and opportunities to capitalise on it while improving their business. For example advanced analytics can be used to provide information about the likelihood of their clients being willing to buy additional products and services, which services might interest them, or their activities on websites and mobile apps

Machine learning algorithms can detect manufacturing bottlenecks or unfair client behaviour. Entrust your data to our care and get high-quality key information for your business.

Trusted by

Komerční banka
UniCredit Bank

Convert data into business value

The increasing volumes of data stored in the Cloud and on Big Data platforms brings with it increased opportunities for its analytical use. Modern business cannot do without advanced data analysis. And that is exactly what Adastra provides. Our team tailors:

  • predictive models from historical data 
  • suggests uses for data generated in real-time 
  •  helps you to find added value in unused data, and much more. 

Advanced analytics can turn data into a key value for business.

Your data is the key to further developing your company in the digital era

Thanks to the integration and processing of various data sources, we can prepare richer predictive models or more accurate segmentation. We focus on current business issues, needs and challenges.

We monitor current trends and look for ways to utilise them for better customer knowledge and personalised interactions, based on the detection of customer needs (and thus better customer retention, loyalty building, and service provision), for more efficient processes within the organisation, and more. 


A September campaign offering loans targeted at families with school-age children was 10 times more successful than standard approaches without Text Analysis.

Our analysis must make sense and have a mission! We evaluate Big Data using not only proven traditional approaches (we create mathematical/statistical models), but also modern machine learning, deep learning, and text analytics (NLP).


The size of the target audience who received the correct advertisement online increased 10 times with the help of Advanced Analytics and predictive models.

Tasks for Data Science

Customer Insight

  • we describe customers’ characteristics and behavior
  • we identify their needs
  • we derive new information
  • we recognize typical patterns
  • we create event triggers


  • we predict the probability of a particular event, such as
    • a customer clicking on your advertisement
    • a failure occurring on the production line


  • we create groups/market segments with similar customers, while simultaneously ensuring that these segments are substantially different from one another

Text Analysis

  • we process data from various text sources, including
    • classifying e-mails from customers
    • identifying the main content of the message

Analysis of semistructured and unstructured data

  • we process and analyze logs, sensor, telemetry and location data
  • we can enrich your data and analysis with external sources and open data

Geolocation data analysis

  • we enrich the analyzes with location data to calculate:
    • driving distances
    • nearest stores
    • optimal distribution of branches
    • availability of communication networks

Product recommendations

  • we use data about customer behavior, activities, and preferences to work out what a given customer might want based on similarities to other customers (pattern analysis)

Web analytics

  • we extract your data from the web and digital channels
  • we evaluate their contribution to sales
  • we connect them into a 360° view of the customer and use them in other analyses

Case studies


Banking - just-in-time loan offers - a 10x higher conversion rate

Together with the bank, we used several years’ worth of transaction descriptions and a number of transactions of a specific type to identify a family with children.

Analyses of behavior patterns have shown that customers in this segment spend the most money in September. As a result, the bank offered this family a personalized loan product at the right time.

10x greater success

The approach was 10 times more successful than using standard procedures without analytics on the top of Big Data. Usually, simpler rules are used for credit offers (for example, account balance and credit limit).


Internet media - an increase in impressions among the target group - a 10x bigger target group

Online advertisers want to target their campaigns accurately and reach the right audiences.

Consequently, online media operators have turned to Adastra to help them model customer behavior on the Internet using log data (cookies).

The relevant target group is 10x bigger

We created predictive models for assessing data on reader demographics using Text Analysis. The solution processes more than 14.5 million cookies daily (more than 100 million records each week). Using Advanced Analytics and predictive models increased the size of the original target group approximately 10 times.



Looking for a solution tailored to your needs? Please, leave us a contact, we will contact you.

Thank you

We will contact you as soon as possible.

Dagmar Bínová

Big Data & Data Science Team Lead

Oleg Masajlo

Senior Data Scientist

Radek Nevyhoštěný

Data scientist

Bohuslav Koukal

Data Scientist