Categorizing preferences of customers or users as they forge relationships (content-based recommendations)
Recommendation systems are an important component for digitalized companies, particularly in the e-commerce sector. We implement data science to provide companies with the foundation for more turnover and improved customer retention.
Why Basefarm?
In developing customized recommender solutions for our clients based on state-of-the-art machine learning processes, we enable them to gain a competitive advantage. We believe there is no such thing as a ready-made solution. We work together with our clients to find the right solution for them, whether that is B2C or B2B. We do not limit ourselves to only the traditional website use cases; we also develop recommenders for internal processes, expert support or process optimization.
Our Big Data Team possesses extensive sector-spanning experience in the field of data science and machine learning. With a mix of mathematicians, psychologists, physicists and computer scientists, the team is able to examine the various facets of a data challenge from a wide range of angles. We stay on the cutting edge of research and do not shy away from technical innovations.
Big data Blog
CASE STUDY:
DATA THINKING
AT C-LEVEL
- Project: Capability assessment and development of a data maturity roadmap for an international retail holding
- Approach: Workshops and individual interviews with business units and IT;
“ There are no best practices out there
– just practices to learn from and get inspired by.”
– Florian Dohmann, Senior Data Scientist
- Capability Assessment – unique model for the evaluation and analysis of operational and organizational skills and competencies within a company (data, algorithms, technology, mindset), fit gap analyses, determination of key insights and recommended actions
- Results: Identification and prioritization of recommended actions, data maturity roadmap (planned for 24 months)