Customer Value & Loyalty Breakout Sessions

Hear how today’s leading organisations harness the power of customer knowledge to maximise customer value. Learn how CRM departments and marketing departments can benefit from Predictive Analytics to increase marketing staff productivity and efficiency, reduce costs and generate a bigger return on investment (ROI).

Speakers and session(s) subject to change.
Some sessions might apply to more than one track.

Click here for the complete agenda

Marketing Optimisation at AIDA

Björn Conrad
Manager CRM / Direct Marketing
AIDA Cruises
Germany

AIDA Cruises is the number one provider of holiday cruises based in Germany.  With plans to double cruise liner capacity by adding three new ships over the coming years, AIDA needed a solution to help the company better target, plan, execute and report on its direct marketing campaigns.  Attend this presentation and hear how AIDA has implemented SPSS’ PredictiveMarketing solution to support the needs of their enterprise, from analysis to cross-campaign optimization and reporting.  You’ll learn how AIDA has used PredictiveMarketing to meet business and growth goals with marketing and professional campaign activities, as well as how to optimize campaigns, especially in relation to the tourism/leisure industry.

Breakout Session 1: Monday, 14 May 2007

Pushing SPSS Output to the Corporate Intranet ASAP: An American Airlines Success Story

King Douglas
Senior Analyst
American Airlines
USA

In July 2006, American Airlines announced its best quarterly results since 9/11. In the struggle from near-bankruptcy to profitability, the extensive sharing of information—including customer research data—throughout all departments and workgroups has been an important success. With SPSS technologies, American Airlines accelerated the pace at which it distributes customer research information to executives and managers—both at headquarters and in the far-flung locations the world’s largest airline serves. New threats to profitability, including intensive competition from low-cost carriers and the astounding increase in fuel costs, continue to make it extremely important to quickly deploy information to decision makers throughout the organization.

In this session, American Airlines will share how it used SPSS programming capabilities to speed the delivery of research results to executives and managers.

Breakout Session 1: Monday, 14 May 2007

Improved Clustering Using Simple Ranks

Dr. Michael Weichert
Senior Analyst
Vodafone D2
Germany

Aimed at intermediate users such as marketing analysts, database marketers and consumer insight statisticians, this session will build on Vodafone Germany’s experience dealing with live data analysis, where data transformations are often not appropriate or intuitive enough, nor result in anything suitable for analytical procedures.
The company has been able to perform detailed market segmentation, allowing a much more precise calculation of a global business case for the product, improved one-to-one marketing targeting – resulting in higher take rates – and more detailed tariff calculations.
The presentation will demonstrate how to handle heavily skewed data in statistical procedures, the power of simple rank transformations, and how to use SPSS to carry out robust clustering.

Breakout Session 1: Monday, 14 May 2007

Commercial Insight in Action at Debenhams: Styling the Nation through Clementine

Andre Grant
Commercial Insight Analyst
Debenhams Retail PLC
United Kingdom

UK department store group Debenhams operates within a fiercely competitive market, which requires both the quantity and level of analysis to increase across all areas of the business. The newly-formed Commercial Insight Team applies both hard and soft modelling, statistical, and data mining techniques, using the capabilities of Clementine to unlock the wealth of information available to optimise decision-making at all levels.

From the direct marketing function to elements of buying and merchandising, this presentation will reveal how Clementine is an integral asset in helping the company to understand the plethora of data captured about its customers.

The session will illustrate where Debenhams has used Clementine to better understand customer data in order to support a variety of activities: from direct marketing, to buying and merchandising. It will also enable attendees to discuss the future direction for analysis tools such as Clementine.

Breakout Session 2: Monday, 14 May 2007

CRM Optimisation: A Direct Marketing Case Study

Arthur Seck
CRM Manager
Natixis Assurances
France

When Natixis Assurances was looking for an analytical CRM strategy, they turned to SPSS PredictiveMarketing. Come hear the fascinating story of how Natixis implemented a successful analytical strategy  - which resulted doubling their revenue on direct marketing campaigns from 1.5 million Euro to 3.1 Million Euro. In addition, this solution lowered their costs by 50 percent, saving 1.6 Million Euro! With this successful implementation, Natixis is now able to predict response rates by marketing campaign. Don’t miss your chance to hear how SPSS’ PredictiveMarketing is rapidly delivering competitive advantages for Natixis.

Breakout Session 2: Monday, 14 May 2007

Increase Marketing Profit with Predictive Analytics

Andrew Yates
SVP and Managing Director, EMEA
Aprimo, Inc.
United Kingdom

SPSS’ predictive technologies are helping organisations take marketing initiatives to the next level. Using data-driven lifestyle, transactional, and attitudinal information, organisations can make more targeted decisions that lead them to understand, predict, and act on customer interactions—regardless of where or how those interactions occur.
Attend this session to learn predictive analytics can be used to drive the segmentation and multi-channel targeting process; how scored segments drive increased response rates; and how your organization can achieve higher ROI on your marketing campaigns and increase company profits.

Breakout Session 4: Monday, 14 May 2007

Customer Lifecycle Marketing: Identifying At-Risk Customers

Michiel van Straten
Senior Data Analyst
KPN
The Netherlands

With around a million business customers in one of today’s fastest-paced industries, Dutch telco provider KPN changed the way they performed market segmentation and conducted marketing campaigns to keep up with the highly competitive marketplace. Starting from scratch with a new Customer Lifecycle Management program, KPN found itself with hundreds of thousands of business customer records to make sense of.  Before any new marketing campaigns could be launched, the company had to find a way gain insight from this surfeit of information, including their qualitative data. 

This presentation will explain KPN’s process of building a Customer Lifecycle Management program from the ground up without possessing overt behavioural data on their customers.  This session will also explore the trade-offs between speed and quality of data analysis, as well as describing how KPN was able to accurately identify 25 percent of the customers representing 75 percent of their total revenue-at-risk.

Breakout Session 4: Monday, 14 May 2007

Using Predictive Analytics to Improve Customer Interactions and Increase Profits

Richard Verhoeff
Director, ICT Services & eCommerce
Center Parcs Europe N.V.
The Netherlands

Optimising their customer knowledge and interaction is high on the list of priorities for Center Parcs Europe.  With its implementation of predictive analytics, Center Parcs accurately predicts individual customer needs and, as a result, targets its activities through direct mail, website and call centres with much greater precision. By contacting only those customers who are likely to respond, the company has reduced their direct marketing costs by $1.5 million. Moreover, they have also increased their revenue by $1.65 million – again through the use of predictive analytics.

Don’t miss the opportunity to hear how this organisation implements real time customer feedback management. You’ll also learn about the next phase in Center Parcs’ predictive analytics journey, in which they plan to optimise their park occupancy through yield management—predicting which price for a given date will lead to maximum occupation.

Breakout Session 5: Tuesday, 15 May 2007

It’s No Game:  Customer Knowledge Makes for Better Predictive Marketing

Eric Munz
CEO
KDP Groupe
France

KDP Groupe is the second largest free online gaming portal in France, which provides free access to lotteries and other games on the web. KDP stores about 1,500 unique criteria for each gamer, including a large amount of personal information that the gamers provide. As a result, it has some 1.5 million unique profiles in its database.

Indeed, KDP sells this customer data to commercial companies, helping them better target prospects during marketing campaigns. In this presentation you will see how data mining is central to this activity, helping KDP collect a variety of member data which is highly valuable to its commercial customer base.

Don’t miss this session, which will highlight how KDP Groupe incorporates data mining to produce more powerful, targeted marketing campaigns, often increasing customer loyalty as a result.

Breakout Session 7: Tuesday, 15 May 2007

Using Data Mining to Optimise Customer Marketing

Martin Saly
Manager, Data Mining
Ceskoslovenska obchodni banka (CSOB)
Czech Republic

Ceskoslovenska obchodni banka (CSOB, a member of the KBC Group) is a major bank in the Czech Republic.  The bank began employing data mining techniques in order to better segment customers and target cross-sell campaigns.  After several successful pilot projects, data mining at CSOB was expanded to additionally model purchasing behaviour, customer attrition, and to make up-sell recommendations.  This presentation will walk you through the data preparation, scoring, and model deployment methods that helped CSOB to increase campaign response rates and more accurately identify customers with a propensity to buy.

Breakout Session 5: Tuesday, 15 May 2007

Driving CRM, Customer Loyalty with Data Mining

Mireille Messine
Decisional Marketing Manager

Valérie Blanchet
Customer Survey Manager
Sephora
France

Sephora has some 700 stores in EMEA, USA and China selling about 8,000 cosmetic products from the likes of Dior and Chanel. In 2004, the organisation launched a customer-centric company strategy, and employed data mining tools to support customer relationship management, call centre optimisation, its e-commerce web site and its loyalty card programme.

The knowledge provided by the data mining activity provided information into the customer value to better align the marketing activities. This presentation will show you how, using this knowledge, Sephora improved targeted campaigns, increased revenue from the loyalty card programme, and increased revenue from customers across both the stores and the web.

This session will explain how robust data mining can provide detailed customer knowledge that can improve the use of all channels to market, while increasing revenue from loyalty card owners.

Breakout Session 6: Tuesday, 15 May 2007

Data Mining in an International Context

Jim Jenkins
Senior Database Marketing Analyst

Luc Boeke
Marketing Analyst
UPC Broadband Holding Services B.V.
The Netherlands

UPC provides cable television, internet and telephony services across several countries in Europe and is the largest cable TV provider outside the United States. Two years ago, the company possessed no data mining capability in any of its markets, but increasing competitive pressures led to the decision to build a database marketing function. Although each national affiliate operates as an independent business, UPC believed that a central corporate team would be more effective in getting database marketing up and running.

This presentation describes how this centrally based set up works in practice, what advantages and disadvantages it brings, and what some of the recent highlights have been. The benefits have included:

Breakout Session 7: Tuesday, 15 May 2007

Segmenting Pre-pay Customers in a Highly Competitive and Saturated Marketing

Nebahat Donmez
Manager, Customer Insight
Vodafone Netherlands
The Netherlands

In the telecommunications market, the Netherlands is one of the most competitive countries in the world. Therefore, having an integrated understanding of subscribers’ behaviours and the needs which trigger these behaviours has been essential to the success of Vodafone Netherlands. In response to competitive pressures, the company used a differentiated marketing approach to efficiently promote existing products and launch new offers.  To do this, Vodafone Netherlands selected SPSS to help group their pre-pay mobile customers into 20 unique market segments. 
In this presentation, you will learn:

In addition, this session will address Vodafone’s combined analytical and domain expertise approach to segmentation and you will see examples of targeted campaigns for different segments. You will also hear about the company’s “data building blocks” marketing data repository, which includes nearly 1000 customer data variables, created by using SPSS Clementine.

Breakout Session 3: Monday, 14 May 2007

Maximising Customer Lifetime Value Through PredictiveMarketing

Ben Day
Head of Marketing Control
Saga Group Ltd.
United Kingdom

Saga Holidays is a multi-million pound worldwide travel business for the over-50s market. The Saga Group as a whole also includes insurance services, financial services, and utilities such as gas and electricity.

This wide product range coupled with a fifty-year heritage has created a group marketing database of over seven million households. The Group takes a direct sell approach for all its products, with frequent direct mailings. The market has large disposable incomes and very discerning tastes, so in order to maximise customer satisfaction and lifetime value, Saga must apply successful cross-selling and up-selling.

Attend this presentation to see how the use of Clementine and Predictive Marketing has improved the way Saga targets its customers, enabling the company to add over £1 million to its bottom line in the ensuing six months.
The session will show how predictive analytics can be used to identify customers mostly likely to respond to outbound campaigns and offers, thereby maximising the effectiveness of marketing spend while minimising customer touch fatigue.

Breakout Session 8: Tuesday, 15 May 2007

 

Optimising Direct Marketing to Decrease Churn in Competitive Fundraising Markets

Léonie van de Vijfiejkin
Marketing Analyst
WWF Switzerland
Switzerland

As more and more competitors enter the Swiss fundraising market, The World Wide Fund for Nature (WWF) – tasked with conserving endangered species, protecting threatened habitats and addressing global threats – is finding it increasingly difficult to retain financial support, and is suffering a high level of supporter churn.

To remedy this, it has developed a segmentation model using SPSS tools. As a result, the speaker will show you how the WWF has been able to segment its market to a much more detailed level, enable better allocation of resources, cluster supporters according to their behaviour, and optimise internal business processes.

The presentation will demonstrate how Clementine and SPSS for Windows can be used for detailed market segmentation, preparing data for a churn model, and performing logistic regression, cluster analysis and discriminant analysis.

Breakout Session 3: Monday, 14 May 2007

Improving Business and Financial KPIs with Data Mining

Maria Hristova
Head of Segmentation and Innovation Sector
Mobiltel EAD
Bulgaria

Bulgarian mobile operator Mobiltel, operating in an increasingly competitive market, needed a firm understanding of customer lifecycle management, with a specific emphasis on reducing the churn rate. It began several data mining modelling initiatives, including churn prediction for postpaid and prepaid customers, and ‘propensity to buy’ models with an eye to cross- and up-selling.

Don’t miss the presentation, which will show how since implementing these processes, the company has decreased churn and ncreased service penetration. In addition, they have increased prepaid recharges and acquisitions, and improved revenue streams.

With a focus on data mining and analysis in general, you will hear how to ensure good results with analysis, why to test every analysis model before making it recurrent procedure. You will also learn how often to make updates to models in line with the changing business environment.

Breakout Session 5 : Tuesday, 15 May 2007