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Event details

Topic: Analytics & Statistics for CRM
Date: November 7th, 2-5pm
Place: Hotel Mövenpick, Avenue de Rhodanie 4, Lausanne, Switzerland
Type: free event (2-5pm) followed by a networking apero (5-7pm)
 

 

International keynote speaker

 

    

Dean Abbott
Chief Data Scientist at Smarter Remarketer, Inc.

Dean Abbott is Co-Founder and Chief Data Scientist of Smarter Remarketer, Inc., and President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology.

Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs, and has served multiples times on the program committee for the industrial track of KDD conferences. He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

 

Confirmed speakers

 

             Valerie Ameel (SAS) and Raquel Fandos (Aduno Gruppe)

  

     Olivier Gosset (Nestlé)

  

     Jukka Hekanaho (SandSIV)

 

     Werner Zürcher (DiaSys)

 

 

Detailed program

13h00 – General Assembly of the Swiss Association for Analytics (SAA)

 

14h00 – Start of the event – introduction from the Committee

 

1st Half – Customer Intelligence

 

14h10 Keynote Speech – Dean Abbott - The Revolution in Retail Customer Intelligence (50 + 10 mins)

In this new era of big data, companies collect data in ever-increasing volume and variety. In the midst of big data, a revolution is taking place in digital customer intelligence. Predictive analytics and the related disciplines machine learning and data science have led the way in this revolution.  This session will describe approaches to achieve multi-channel customer intelligence. Case studies will illustrate shopping cart funnel management, shopping cart abandonment, marketing attribution, churn, and purchase propensity

 

15h10 Valérie Ameel and Raquel Fandos Marin - Recommendation Systems in CRM (20 + 5mins)

Thanks to consumer-facing shopping sites like Amazon or Netflix, recommender systems are growing in popularity in the marketing world. A product recommendation engine provides the ability to automatically predict the interests of an individual by analyzing preference information (ratings) from many users. Recommender platforms are a useful alternative to search algorithms as they help potential customers discover products they might not have found by themselves. A variety of approaches have been proposed as the basis for recommender systems: collaborative, content-based, knowledge-based ... and most of the underlying algorithms come from the Machine Learning/Data Mining field. This presentation will focus on the terminology, techniques and challenges of recommender systems with a focus on an actual implementation in the context of a credit card Viseca loyalty program. With a portfolio of about 1 million customers, Viseca is a Swiss company that offers Visa and Mastercard credit cards to Swiss banks clients and final customers. The loyalty program “surprize” was launched in March 2014. Customers earn points with every transaction that can be exchanged for redemption items. The recommendation system has been implemented on the “surprise” website in order to present the most relevant items to each customer.

 

15h35 – 15 mins break

 

2nd Half  - CRM

 

15h50 – Sponsor Presentation from PwC (10 mins)

 

16h00 Dr. Jukka Hekanaho - Incorporate Voice of Customer into CRM Analytics (20 + 5 mins)

Traditional CRM deals with internal company data of the customer, including his/her profile and transactional information. Consequently, the traditional CRM Analytics or data mining has dealt with segmenting and predicting customer behaviour based on the static profile and the interaction data with the company. Many companies have used this approach with considerable sophistication to produce effective predictive models and targeted customer campaigns. However, this approach ignores the most important factor in the company-customer relationship, the customer feelings and emotions created by the interactions. In order to include these, we extend the CRM data with Voice of the Customer (VOC) data and use VOC Analytics to derive actionable insights. We show how open customer feedbacks can be analysed and how the insights generated can be automatised and used in different processes to improve customer experience. We will also show practical examples from several different industries.

 

16h25 Werner Zürcher - Using survival analysis to identify profitable members (20 + 5 mins)

Profitablity is an issue for non profit organizations (NPO) too. A high net income means more money for their projects. And loyal Donors and members are more profitable. Not all. But those with higher donations or membership fees. A large german charity with more than a million members wanted to improve the reporting of their membership program. One aspect was to identify the factors which affect the life time value of their members.First we used Life Tables and the resulting survival function plots to explore the influence of different  factors (univariate). We were surprised by the high acceptance of the survival function plots. Then we used Cox Regression to explore and quantify the influence of each factor given the other factors (multivariate). The factor which influences survival most is the new member’s age. A severe  problem we were confronted with was sample size. With a sample of 200’000 “everything” is significant. Cox Regression diagnostics based on statistics were misleading. We could only trust diagnostic plots. The target was to identify profitable members. Therefore we used the regression parameter and the Base Hazard function to build a predicting model to optimize acquisition of profitable members.

 

16h50 Olivier Gosset - How to marry CRM & big data and make it (more) real? (20 + 5 mins)

Sources of data now generate a lot of new business opportunities and BIG DATA seems to be the new “Eldorado” for merchant websites. Actually, this quest looks like the Holy Grail’s quest … which remains inaccessible. The presented approach will try to define concrete ways to address these new challenges, make data meaningful and establish a richer relationship between online customers and merchant websites.

 

17h15 – Networking apéro

 

Speaker biography

Olivier Gosset

Coming from the analytical-CRM world, Olivier Gosset could quickly invest a business strongly driven by data … e-commerce.  After having deployed e-commerce strategies in fashion & photo-finishing industries, he is now in charge of the e-commerce strategy for Nestlé Switzerland and its 40 brands.

 

Dean Abbott

Dean Abbott is Co-Founder and Chief Data Scientist of Smarter Remarketer, Inc., and President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology. 
Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs, and has served multiples times on the program committee for the industrial track of KDD conferences. He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

 

Dr. Jukka Hekanaho

Dr. Jukka Hekanaho has 20 years of experience in data mining and is an expert in customer intelligence and in delivering client-centric solutions within customer experience management and customer relationship management. He is currently the Chief Experience Officer of SandSIV AG and heads the consulting arm of SandSIV. Prior to joining SandSIV Dr. Hekanaho held various senior management positions in the financial industry and worked as customer experience consultant for various industries. Dr. Hekanaho has a PhD in Data Mining from Åbo Akademi University.

 

Valérie Ameel

Valérie Ameel is a sales support consultant at SAS Institute in Geneva. Valérie has been working for 10 years in predictive analytics with SAS and IBM SPSS and she has extensive experience of the Telecommunication industry.

She has an engineering degree in computer science and a master of Business Administration from University of Ottawa.

 

Raquel Fandos Marin

Raquel Fandos is a data mining consultant at Viseca Card Services in Zurich. Raquel has an engineering degree in Telecommunications and a PhD in the fields of data mining and machine learning. She has been working for Viseca for the last two years.

 

Werner Zürcher

Werner Zürcher is the President of DiaSys Marketing Engineering AG and Senior Fundraising Consultant. DiaSys is a provider of Database Fundraising services (includes analytics) for charities in Switzerland and Germany since 1999. Werner Zürcher is a Certified Fundraising Executive with degrees in engineering (ETH Zürich) and applied statistics (University Bern).

 

Sponsors

Gold sponsors:

 

      

 

Partner sponsor:

 

Organization 

    

 

 


Cancellation policy

The number of places is limited: if you can't come, please cancel your reservation or send an email to info@swiss-analytics.ch

Location

Hotel Mövenpick Avenue de Rhodanie 4, Lausanne, Vaud, 1000, Switzerland Get Directions

Organizer

Swiss Association for Analytics (SAA) and Swiss Statistical Society (SSS)

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