Data science and advanced analytics

Get ten times more successful campaigns and expand your target audience. Machine learning algorithms can detect weaknesses in the production process and fraudulent behavior of clients.

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Your data is the key to your company's further development in the digital era

Advanced analytics can help you get information such as how likely your clients are to buy other products and services, what services they might be interested in or how they navigate websites and mobile apps.

Machine learning algorithms can detect weak points in the production process or unfair client behaviour. Entrust your data to our care and you will get quality and key information to work better with your clients.

By integrating and processing different data sources, we can prepare richer prediction models or more accurate segmentation. We focus on current business issues, needs and challenges.

We follow current trends and look for ways to use them for better customer knowledge, for personalized interactions based on customer needs detection (and thus better responses for customer retention, loyalty building, service delivery), for more efficient processes within the organization, etc.

Our analyses must have a purpose and a mission! We evaluate big data not only with proven traditional approaches (mathematical-statistical models), but also with modern techniques of machine learning, deep learning and text analytics (NLP).


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


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

Advanced analytics can turn data into key business value. And that’s exactly the kind of analytics Adastra provides:


Prepare prediction models from historical data


Suggest the use of data generated in real time


Help you find added value in unused data and much more

Task types in Data Science

Customer insight

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


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

Target groups segmentation

  • we create groups – segments with similar customers so that at the same time these segments differ significantly from each other

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 recommendation

  • from data on customer behaviour, activities, preferences, we infer what the selected customer might want based on similarities with 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

Equa Bank clients were fully migrated to Raiffeisenbank in 12 hours

When Equa Bank was being mergedintoRaiffeisenbank in November 2022, we handled the migration of Equa Bank’s client data into Raiffeisenbank’s CRM system. We also ensured the client master data was propagated to the bank’s core systems.  

hours instead of 3 weeks – shorter live migration thanks to 10 months of testing and agile development

subjects to migrate

people - each with 200 attributes, added to Raiffeisenbank’s client base after the acquisition of Equa Bank

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Automatic categorization for 98.5% of card transactions

With millions of clients conducting millions of operations every day, the bank needed to automatically assign a unique category to every banking transaction (card...

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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...

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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...

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Get inspired on our blog

Adastra becomes a strategic partner of Škoda Auto University. Its specialists will teach data management, data science, and artificial intelligence courses

Adastra becomes a long-term strategic partner of Škoda Auto University. Its experts will be involved in teaching data management, data science, and artificial intelligence...

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Unraveling the Future: Top 8 Data Management Trends for 2023 and Beyond 

The digital landscape is evolving at an unprecedented pace, and with it comes a new set of challenges and opportunities for IT professionals, data...

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Good data management and the gap between IT and business are the most burning issues for large Czech companies 

Large Czech companies consider the biggest challenge they will face in the next three years to be good data management and business’ inability to...

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