NEUSREL Find and Exploit Success Levers with Your Dataset

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NEUSREL Find and Exploit Success Levers with
Your Dataset
These charts are not made to be self explanatory
and are not complete without personal explanation.
May 2009
Dr. Frank BucklerNEUSREL Causal Analytics,
Jungbergerstr. 7, 51105 Cologne49 163 282 55
37, www.neusrel.com , Buckler_at_neusrel.de
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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

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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
• doesnt 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.

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NEUSREL

• Already applied by leading researchers

• 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

• First commercial users in consulting services and
  market research.

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NEUSREL Algorithm Scheme
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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

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Case Image on Loyalty
PLS
NEUSREL
High
High
Low
High
Low
Low
High
Low
Result with NEUSREL If you increase
environmental perception, you might loose up to
4 of customers.
Result with classic methods If you increase
environmental perception, 3 of customers will
refrain from switching
Recommendation to utility company Dont invest
in environmentally focused image campaign.
Result 2 Mio savings and established high
loyalty.
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Case Satisfaction Levers
PLS
NEUSREL
Effect on satisfaction 0,1
Effect on satisfaction 0,1
Effect on satisfaction 0,2
Customer satisfaction
Customer satisfaction
Availability
Availability
Result with classic methods Increase in
availability by 1, increase satisfaction by 0,2
Result with NEUSREL Increase in availability by
1, increase satisfaction just by 0,1
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.
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Case Satisfaction on Loyalty
PLS
NEUSREL
Effect on loyalty 0,5
Effect on loyalty 0,2
Result with NEUSREL Loyalty is most effectively
increased by addressing not satisfied customers
Result with classic methods Increasing customer
satisfaction will increase significantly your
customer loyalty
Recommendation to telecommunication company
Focus on eliminating dissatisfaction (e.g.
improve complaint handling) and less on
increasing overall satisfaction.
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Case Satisfaction on Loyalty
PLS
NEUSREL
High
High
Low
Low
High
Low
High
Low
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.
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Case Complaints on Loyalty
PLS
NEUSREL
Hoch
Hoch
Niedrig
Niedrig
Hoch
Niedrig
Hoch
Niedrig
This is a threshold function an increase from
unsure to satisfied has a huge effect on
loyalty.
Increase complaint satisfaction to increase
loyalty.
Do not interrupt complaint interaction unless
customer is satisfied. Probe for it. Stimulate
complaints in order to win sleeping unsatisfied
customers.
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Case Sales Promotion
PLS
NEUSREL

Perceived. Relationship investment

Perceived. Relationship investment
Tangible rewards
Interpersonal Communications
Result with NEUSREL Increase either tangible
rewards or interpersonal communication (depending
on costs/effect ration)
Result with classic methods Increase tangible
rewards and interpersonal communications.
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.
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Case Confusion
PLS
NEUSREL

Confusion
Confusion

Confusion
Income
Education
Income
Education
Result with classic methods No significant
effect. Confusion is quite unexplained.
Result with NEUSREL Education decreases
confusion only for medium income segments
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.
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Case Branding
PLS
NEUSREL

Confusion
Brand Loyalty

Brand Loyalty
Rational Co
Income
Emotional Components
Result with classic methods Emotional and
rational brand components independently effect
brand loyalty.
Result with NEUSREL Emotional and rational
components support each other when influencing
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.
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Case Willingness-to-Pay
PLS
NEUSREL
Result with NEUSREL Willingness To Pay is
increased most effectively by Cross Buying and WoM
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..
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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)
• Scholars
• interested in incorporating the method in their
  own research, Im happy to help -when possible-
  with a methodical co-authorship.

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Dr. Frank BucklerNEUSREL Causal
Analytics Jungbergerstr. 7 51105 Cologne,
GERMANY49 163 282 55 37 www.neusrel.com 
Buckler_at_neusrel.de