1. NEUSREL Find and Exploit Success Levers with Your Dataset Dr. Frank Buckler NEUSREL Causal Analytics, Jungbergerstr. 7, 51105 Cologne +49 163 282 55 37, www.neusrel.com, Buckler@neusrel.de These charts are not made to be self explanatory and are not complete without personal explanation. May 2009

2. Situation Today Success lever studies are widely examined e.g. Customer satisfaction Marketing mix efficiency Sales force effectiveness Long-term ROI driver Image impact studies … Causal / path analysis needed to prevent spurious correlation and missing of indirect effects … but methods available today as Lisrel, Amos or PLS are … not acknowledging the fact that in most cases solid hypothesis for paths are not available. The confirmatory approaches are not practical. not able to detect unknown nonlinearities, something that we know exist in nearly every dataset not able to detect unknown interactions (dito) not able to integrate categorial variables in one holistic model …

3. Consequences Because of lack of analysis methods that are able to cope with complexity of tasks: Causal / path analysis is rarely used. Instead semi-optimal surrogates find application Results of causal / path analysis are often misleading Results are not reflecting complexity of reality Results lead often to wrong recommended action Leading to negative, not intended outcomes A method solving the problem… doesn’t need to build on wrong hypothesis and therefore enables wide application of causal path modeling. helps to learn about precious details of cause-effect relations between levers and outcomes. leads to recommended actions that helps to achieve intended outcomes in the most efficient way.

4. NEUSREL First published in the dissertation thesis “NEUSREL” in 2001 (only German) Global attention of NEUSREL since end of 2008 along with appearance of MJRM journal article Already applied by leading researchers First commercial users in consulting services and market research.

5. NEUSREL Algorithm Scheme

6. Quotes from Users "... congratulations on creating a wonderful product--I am going to be recommending it at places that I already have connections with." John Steele, M. S., ABD, Kansas State University & Army Research Institute (ARI) "... thank NEUSREL we were able to uncover important nonlinearities within a psychologic brand impact model.„, Gregor Waller, lic.phil. Scientific Director, Brandezza AG “I had the chance to read the book NEUSREL in 2001 as an early draft. Within the scientific tradition of data-mining, I believe that both NEUSREL and Universal Structure Modeling (USM) add a powerful instrument to uncover hidden, more complex, and perhaps meaningful relationships among variables." Prof. Dr. Dr. Rene Weber, University of California at Santa BaMcKara, USA “I use USM whenever I am working on a problem that falls within its capabilities, for example, to estimate structural equation models with many nominal variables such as gender. In the field of customer confusion we found that confusion is particularly prevalent among medium-income consumers, whereas low- and high-income consumers employ buying heuristics that shield them from confusion. A simple finding, however one we would have never found without USM”, Professor Dr. Gianfranco Walsh, Strathclyde Business School, University Glasgow & University of Koblenz “We are planning to apply NEUSREL for communication controlling and planning in the advertising-intensive food industry. We estimate to save companies a considerable part of their communication spendings”, Professor Dr. Holger Buxel, University of Applied Science Muenster “I used to be a strong advocate of Structural Equation Modeling methods. After many long fruitful discussion nights with Frank, I have to admit: NEUSREL is simply what was missing - not only in science. It is the missing link which brings causal analysis into practical applications”, Professor Dr. Alexander Klee, University of Applied Science Flensburg “With NEUSREL Dr Buckler introduces an outstanding contribution to marketing research, that has the potential to close a major research gap" Professor Dr. Klaus-Peter Wiedmann, University of Hanover "Best wishes as you expand the influence of this exciting software", Christopher P. Blocker, Ph.D. Assistant Professor, Hankamer School of Business, Baylor University "[The inventor of PLS] Wold talked about a dialog between the researcher and the data, facilitated by the method.... I think a tool like NEUSREL brings PLS closer to Wold's original intent for PLS.". Edward E. Rigdon, Professor, Department of Marketing, Georgia State University

7. Case: Image on Loyalty Result with classic methods: If you increase environmental perception, 3% of customers will refrain from switching Result with NEUSREL: If you increase environmental perception, you might loose up to 4% of customers. Recommendation to utility company: Don’t invest in environmentally focused image campaign. Result: 2 Mio € savings and established high loyalty. High LowHighLow High LowHighLow PLS NEUSREL

8. Effect on satisfaction +0,1 Case: Satisfaction Levers Result with classic methods: Increase in availability by 1, increase satisfaction by 0,2 Recommendation to transport company: It was discovered that the cost/effect ratio is only half as originally estimated. Hence, budget allocation of efforts was adjusted. Result with NEUSREL: Increase in availability by 1, increase satisfaction just by 0,1 Effect on satisfaction +0,1 Effect on satisfaction +0,2 Availability Customer satisfaction PLS NEUSREL

9. Case: Satisfaction on Loyalty Result with classic methods: Increasing customer satisfaction will increase significantly your customer loyalty Result with NEUSREL: Loyalty is most effectively increased by addressing not satisfied customers Recommendation to telecommunication company: Focus on eliminating dissatisfaction (e.g. improve complaint handling) and less on increasing overall satisfaction. Effect on loyalty + 0,5 Effect on loyalty +0,2 PLS NEUSREL

10. Case: Satisfaction on Loyalty High Low HighLow High Low HighLow PLS NEUSREL Result with classic methods: Increase satisfaction and loyalty will follow Result with NEUSREL: An increase in satisfaction has only an effect for unsatisfied customers. Focusing measures intended to increase satisfaction on unsatisfied customers.

11. Case: Complaints on Loyalty This is a threshold function: an increase from „unsure“ to „satisfied“ has a huge effect on loyalty. Hoch Niedrig HochNiedrig HochNiedrig Hoch PLS NEUSREL Do not interrupt complaint interaction unless customer is satisfied. Probe for it. Stimulate complaints in order to win „sleeping“ unsatisfied customers. Increase complaint satisfaction to increase loyalty.

12. Tangible rewards Case: Sales Promotion Result with classic methods: Increase tangible rewards and interpersonal communications. Result with NEUSREL: Increase either tangible rewards or interpersonal communication (depending on costs/effect ration) Recommendation to cloth chain: Skip tangible rewards and focus on team building and leadership abilities of shop managers. Result: Sales margin increased from 3% to 6%. Interpersonal Communications Perceived. Relationship investment PLS NEUSREL

13. Case: Confusion Result with classic methods: No significant effect. Confusion is quite unexplained. Recommendation: Support usage of decision heuristics by offering clearly branded low- cost and premium products and separate them on POS. Furthermore decrease variety in intermediate product range. Rework customer segmentation approach. Result with NEUSREL: Education decreases confusion only for medium income segments Education Confusion Income Confusion Income Education Confusion PLS NEUSREL

14. Case: Branding Result with classic methods: Emotional and rational brand components independently effect brand loyalty. Recommendation: When crafting a creative briefing as a strategic guide for advertising agencies: it is important to achieve a strong emotional connection with the brand and to convey at the same time strongly the reason-way arguments. Result with NEUSREL: Emotional and rational components support each other when influencing brand loyalty. Emotional Components Brand Loyalty Rational Co Brand Loyalty Income Confusion PLS NEUSREL

15. Case: Willingness-to-Pay Result with classic methods: Higher satisfaction will directly increase e.g. Willingness To Pay Recommendation: Do not invest just in customer satisfaction but in instruments that increase WoM and Cross Buying and by doing this you involve customer with the companies offering. As a result customers will show higher willingness to pay.. Result with NEUSREL: Willingness To Pay is increased most effectively by Cross Buying and WoM PLS NEUSREL

16. Offering Free Analysis for Prospective Customers: –We analyse for every interested researcher one of his models with his data at no costs. You fill an Excel-template-sheet and we will send you an analysis log-file including my brief interpretation of the results. PhD Program: –A restricted number of doctorial students with limited financial means have the opportunity to use NEUSREL at no charge. (www.neusrel.com/PhD)www.neusrel.com/PhD Scholars: –…interested in incorporating the method in their own research, I’m happy to help -when possible- with a methodical co-authorship.

17. Dr. Frank Buckler NEUSREL Causal Analytics Jungbergerstr. 7 51105 Cologne, GERMANY +49 163 282 55 37 www.neusrel.com Buckler@neusrel.de