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Blog

Find below the collection of our published blog articles. You can filter articles by our services, technology and year published.

Finding customer needs using Cluster Analysis

Published: Author: Oliver Staubli, CEO & Data ScientistTags: ArticleE-CommerceData ScienceExamplesExploratory Data AnalysisData Visualization

Whether your company sells clothes, cars or shampoo, with every product sold you should learn more about the past needs of your customers. The longer the customer relationships and the more customers you have, the greater the chance that exciting patterns are hidden in your transactional data. The knowledge about your customers' needs is ideal for cross- and up-selling. Through improved targeting (matching the right offer to the right customer), your customers are more likely to convert. In addition, customer loyalty increases because the customer feels understood and listened to.

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"Predictive Sales" presentation together with Swiss Post at the Business Innovation Week

Published: Author: Oliver Staubli, CEO & Data ScientistTags: PresentationSolution

Together with Swiss Post, we were invited to present our joint innovation project "Predictive Sales" at Business Innovation Week. The results are also impressive: Thanks to predictive analytics, we were able to improve the repurchase rate by up to a factor of 5 compared with the control group at three different pilot companies. And this even via the offline channel with personalized postcards. The feedback from the pilot companies was correspondingly positive.

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Keynote "Data Adventures" for Tech Data BI Event

Published: Author: Oliver Staubli, CEO & Data ScientistTags: PresentationKeynote

I will give the keynote speech for Tech Data at their Analytics, BI and IoT day event at Porsche Center Zug. The audience will consist of Analytics/BI-software-resellers and their customers. I hope my presentation will set the mood for the events theme "Data as Fuel for the Engine to drive Dititalization". I'm looking forward to the feedback.

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First course lectured at SIB for Chief Digital Officers

Published: Author: Oliver Staubli, CEO & Data ScientistTags: LectureTraining

I was asked by Valérie Vuillerat to lecture at the Schweizerisches Institut für Betriebsökonomie (SIB) the module «Big Data & Analytics» for the first advanced training in Switzerland to optain the title «dipl. Chief Digital Officer NDS HF». A major honor for me, but at the same time a jump in at the deep end: I should lecture right from the start 8 lessons at a stretch, i.e. having to entertain 24 students for 6 hours with teaching material that needed still to be produced first.

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Cohort Analysis with Interactive Simulation

Published: Author: Oliver Staubli, CEO & Data ScientistTags: Data VisualizationE-CommerceMarketingExploratory Data AnalysisRetailSalesExamplesTraining

Cohort Analysis enables you to easily compare how different groups, or cohorts, of customers behave over time. This gives you quick and clear insight into customer retention trends and the health of your business. See how your latest customers compare to those from several years ago, or compare users who joined over the holiday season with another group that joined in the summer and see if those holiday shoppers really stuck around.

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Image: Sawamur

Predictive Customer Lifetime Value

Published: Author: Oliver Staubli, CEO & Data ScientistTags: Predictive AnalyticsE-CommerceMarketingSalesRetailInsuranceUtilitiesBankingTelecommunicationsExamplesTraining

"Customer Lifetime Value" (CLV) describes the amount of profit a customer generates over his or her entire lifetime and is therefore a prediction of the net profit attributed to the entire future relationship with a customer. CLV is probably the single most important metric for understanding your customers. CLV helps you make important business decisions about sales, marketing, product development, and customer support.

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Predictive Analytics and Industry 4.0

Published: Updated 25. March 2016Author: Oliver Staubli, CEO & Data ScientistTags: HandelszeitungArticlePredictive AnalyticsIndustry 4.0Predictive MaintenanceMedia

I was asked again to write an article for the Handelszeitung. This time, in the Special Industrie 2025 on the subject of predictive analytics in the context of industrial 4.0. I tried to illustrate the topic of Predictive Maintenance with a simple coffee-machine example as well as to point out the enormous potential of predictive analytics for the Swiss market. As always, I'm looking forward to the feedback already.

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Image: YMF

SME-Portrait in Gewerbezeitung

Published: Author: Oliver Staubli, CEO & Data ScientistTags: GewerbezeitungInterviewDigitalizationSMEData ScientistMedia

The second interview: After the kick-off in SonntagsZeitung I received a request from the Swiss Trade Association (STA) for a SME-Portrait about REVOLYTICS AG. STA has chosen "digitalization" as its theme for the year 2016 and had therefore many exciting questions for me. I very much enjoyed the interview. Today the article was published in the Gewerbezeitung.

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Interview in SonntagsZeitung

Published: Updated 20. January 2016Author: Oliver Staubli, CEO & Data ScientistTags: SonntagsZeitungInterviewJobsData ScientistData ScienceMedia

What a lucky launch: Just three months after the founding of REVOLYTICS AG an interview about us including a photo gets published in the business section of SonntagsZeitung. The article was written on the eve of this year's World Economic Forums (WEF), in which the implications of digitalization are in focus. Contrary to the recent Handelszeitung article by the WEF-Founder about the dangers of digitalization, this article describes new professions actually created by the increasing digitalization. Of course I was happy to give some insight into my job as a Data Scientist.

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Kaggle Visualization Challenge Winner

Published: Author: Oliver Staubli, CEO & Data ScientistTags: Data VisualizationD3.jsC++HTML5jQuery

I'm a big fan of the Kaggle platform, one of the world's largest community of data scientists. I came across Kaggle two years ago and thought this "crowd sourcing" idea is brilliant: Companies like Netflix, Google, Facebook are able to host competitions about their hardest predictive modeling problems. The data scientists on the other hand try to solve those complex problems best possible in a given time frame. Besides fame and glory, the winner gets prize money of multiple thousand dollars.

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