Engage your customers in creating their ideal products and services.
Optimize market potential through innovative applications.
Stimulate organic growth of your products.
Harness understanding of customer attitudes and dynamics.
"...exceptionally knowledgeable about all aspects of market research and has helped us with innovative thinking on how and why products compete with each other."
      - HRCP Insights, a subsidiary of McKinsey & Company
"...would recommend without question for any marketing science engagement, but especially where standard approaches are unlikely to crack the problem."
      - Partner, Booz & Company
"...outstanding judgment in making trade-offs during the data-cleaning and modeling processes. I've never worked with anyone consistently better."
      - Division President, The NPD Group
No business can sustain growth – especially profitable growth – unless it develops an understanding of its customers. Marketing and Innovation offers the technical subject-field expertise as well as dynamic, creative thinking to truly understand customer behavior.
There are many tools available to help gain that understanding... Market Research, Customer Relationship Management (CRM), Data Analysis are three of the catch-all tools to help businesses understand their customers better. But, to most business people these terms are vague.
While it is generally acknowledged that such tools are important, the application of them tends to be the purview of some “analytical types” buried somewhere within the corporate structure. There are a seemingly endless number of alternatives – all with strengths and weaknesses – that require significant time commitment in order to appropriately choose and eventually use for the specific issues at hand.
Unfortunately, these three categories of tools are very poorly integrated. It is understandable why this is the case, however, since each set of tools arose from a different group of professionals. There are certainly some synergies and overlap between two or even all three of these providers, but rarely any direct intergration of the components that leverage customer insight to develop better relationships and sustainable, profitable business growth. Marketing and Innovation offers that integration with the end result being a very powerful means of growing profitable businesses.
T H E    T E A M

Lionel Wang

Founder and Chief Research Officer.
Lionel Wang set up Marketing and Innovation, L.L.C in June 2001 and Engage 123, Inc. in 2006. Since starting up the operation, he successfully implemented several marketing research and clickstream applications to major advertising agencies, management consulting firms, marketing research companies, and a global e-Commerce firm. His work in CRM received an honorable mention in Asia's First 1-to-1 Innovator Awards sponsored by Peppers and Rogers Group.
Prior to founding Marketing and Innovation, Lionel Wang was Vice President of Product Development at NFO Interactive from June 2000 to June 2001. In that capacity, he evaluated and implemented numerous Web-based Marketing Science applications.

Lionel Wang joined The NPD Group in 1996 as Director of Analytical Services. He was responsible for providing analytical support, research design, and consultation to both NPD clients and staff. Mr. Wang specialized in Market Structure, Consumer Segmentation, Brand Equity, Choice Modeling, New Product Forecasting, Advertising Analysis, and Point of Sales Modeling. He also developed Web-based Marketing Science applications for The NPD Online Research Group. He played a dominant analytical role in developing Forrester's Technographics and FCB's Relationship Monitor.

Before NPD, Mr. Wang was Vice President of Analytics at A.C. Nielsen where he managed an analytical modeling group on Kraft Foods/White Plains account. Before that he was the Director of Product Development at Information Resources from 1989 to 1994. In that position, he developed and implemented several household panel and store level applications. Between 1984 and 1989, Mr. Wang held two separate positions in Corporate Planning and Marketing Research at The Gillette Company.

Mr. Wang presented several research studies at the Marketing Science conferences, ESOMAR, AMA/Advanced Research Technique forums and DMA conferences. His works on media effectiveness and consumer segmentation analyses received outstanding accomplishment recognition at the Kraft Foods research conference. His visionary research on incorporating brand equity into baseline analysis broadens the scope of standard marketing mix modeling.

Mr. Wang holds a Master of Science Degree in Operations Research from Stanford University, an MBA from California State Polytechnic University, and a Bachelor of Commerce degree from Tamkang University, Taipei.

Karl Irons

Strategic Advisor
Karl Irons specializes in empowering research companies to develop more efficient processes and resolve pending new business initiatives. Until September of 2002, he was employed by the NPD Group in a number of capacities. He spent most of 2002 designing more cost-efficient production processes that spanned the scope of NPD's various businesses.
As President of NPD Online Research, Karl shared responsibility for developing and implementing the online strategy for The NPD Group's various businesses. Previously, he had been President of NPD's Custom Research Services business unit. Mr. Irons joined NPD in 1994 as Vice President, Analytical Services where he oversaw the growth of NPD's value-added products.

Before joining NPD, Mr. Irons held a variety of positions in Product Development, Business Management, Marketing Consulting and General Management with BASES Burke International and its predecessors, Management Decision Systems and Irons Consulting & Analytics. He has degrees in mathematics from Case Institute of Technology and the University of Toledo.

Jeongwen Chiang

Academic Advisor
Dr. Chiang Jeongwen is a Professor of Marketing at CEIBS since January 2010, where he is also the Chair of the Department of Marketing. He previously taught at Cheung Kong Graduate School of Business and the National University of Singapore as Professor of Marketing. Dr. Chiang’s previous academic experiences include University of Rochester, Washington University in Saint Louis, and Hong Kong University of Science and Technology.
Dr. Chiang received his B.A. at National Taiwan University, his M.A. at Rutgers University, and his Ph.D. at the University of Minnesota, all in Economics. His research areas cover competitive analysis, consumer choice, new product development, market forecasting, and consumer satisfaction. Dr. Chiang's research has been published in journals including Marketing Science, Management Science, and Strategy Management Journal. He served as the regional editor-in-chief of International Journal of Research in Marketing and International Journal of Marketing Education, and on the editorial board of Journal of Marketing Science.

Dr. Chiang often teaches executive programs for companies such as China Telecom, Hainan Airline, and China Mobile. Additionally, he consults for multinational companies including Xerox, Merck Sharp & Dohme, and HSBC (Hong Kong).
C O N T A C T    U S

Affiliations: AMA, ESOMAR, INFORMS

©Engage123, Inc.
U N L O C K    C U S T O M E R    V A L U E

Engage your customers in creating and evaluating their ideal products and services.

Consumers "create" their ideal product on a kiosk or desktop computer. You can view demos of these products on our "Demonstrations" page. Consumers are then asked to similarly "create" a second choice product to evaluate.
Then they are asked to compare the two.
O P T I M I Z E    R E T U R N
We developed an innovative approach that enables customer-focused organizations to maximize the lifetime value of each individual customer. Personal relationships are at the core of this model.
  • Our approach captures the “R” of CRM (Customer Relationship Management), such as partnerships, family/friends, practical relationships, and causal relationships.
It includes competitive dynamics
  • Our approach measures both own effect and cross effect of key drivers on your and your competitors' customer lifetime value.
It is an integration of attitudes and behavior
  • Our approach shows how making improvement in key drivers results in an improved customer lifetime value and an improved relationship.
It has a hierarchical structure
  • Functional satisfaction (quality, service, ease, etc.,) is a necessary, but not a sufficient condition for building a strong relationship. Our approach separates functional drivers from relationship drivers.
Value Relationship Optimizer Model
We calculate the lifetime value for each customer
  • Customer Lifetime Value (CLV) is derived from margin, discount rate, and retention.
  • Retention is estimated from both historical pattern and future purchase intent.
We identify the relationship pyramid status that each customer establishes with your company
  • We developed a relationship scoring that properly places each customer to a dominant relationship segment – partnership (commitment-driven), family/friends (trust-driven), practical relationship (leadership-driven), and causal relationship (satisfaction-driven).
  • Relationship scoring is developed based on a variety of relationship drivers - I can’t be temped away from this brand, I trust this brand, this brand rewards me for my business, this brand is a market leader, I buy this brand because it’s less expensive, I keep my eyes open for other alternatives, etc.
We connect CLV and relationship status with a common measure – retention
  • Establish a predictive link between retention and relationship drivers using multinomial logit model.
  • Changes in relationship drivers lead to improvement in both relationship and CLV.
  • Different strategic options can be implemented for different combinations of relationship status and CLV.
We further identify the role of functional satisfaction (quality, service, ease, etc.,) in the relationship pyramid. Please contact us for further information.

Automobile Case Study
A case of optimizing customer value from the perspective of relationship building.


A recent study from a global market research company showed how customer needs can be applied to brand positioning in automobiles. Their study showed that both BMW and Mercedes Benz (MB) ultimately tap into the need for leadership, yet they each satisfy different customer needs. BMW satisfies the need for fun, attractiveness, and self-indulgence, while MB satisfies the need for respect, knowledge, security, and tradition. Their study, like many others, claims that understanding customer needs leads to building strong customer relationships. However, they did not discuss how to measure customer relationships nor did they discuss how improving those relationships can lead to improving customer value. We find this to be a common shortcoming or possibly oversight in studies such as the automobile brand positioning one. It is our intent to address these unanswered issues in the following automobile example.

Bridge the gap between customer understanding and customer relationship

Different customer needs lead to different relationships with brands. Many references can be found discussing ways to define a customer’s relationship with a brand. For our purposes, we think of a customer relationship as a hierarchy. We use the image of a pyramid to make clear the different levels of this hierarchy. Our relationship pyramid consists of five different layers or styles. From the top, they are: partnership, trust, leadership, cost consciousness, and causal relationship. Obviously, the higher a customer is on the pyramid, the stronger his or her relationship with a brand. For example, we found that MB customers form a strong trust relationship with Mercedes Benz, while BMW customers value their brand as a partner. In this example, partnership style is mostly driven by caring, excitement, and uniqueness among others.

We use two separate approaches – an analytical approach vs. a visual approach -- to identify the relationship that each customer establishes with his/her brand. Under the analytical approach, we ask each customer a battery of 10 attribute questions such as “I trust this brand”, “This brand cares about my needs”, “This brand is exciting”, “There is simply no other brand likes this brand”, “This brand is a market leader”, etc. Confirmatory factor analysis on these attributes detects the relative distribution of five relationship styles for each customer. The most dominant relationship style is then identified. Five relationship styles are further validated by a Flash-enabled visual approach where customers tell us which relationship style best describes their experience with their brand.

It is well documented that trust is a necessary but not a sufficient condition to build the strongest customer relationships. We did observe in our auto study that partnership style yields the highest loyalty score (90%), followed by trust (83%), leadership (75%), cost consciousness (70%), and causal relationship (55%). Our Loyalty score metric is a composite measure of brand loyalty, willingness to make recommendations, and new product/service.

Each brand has its own relationship migration pattern

Although partnership style is the most preferred relationship that a brand wants to have with its customers, it sometimes makes sense to focus on building a trust or leadership relationship. In our auto study, trust-driven attributes turn out to be more significant than partnership-driven attributes in predicting loyalty for BMW, while the reverse sequence is observed for Mercedes Benz.
Our understanding of customers’ relationships to these luxury automobile brands offers a deeper insight to RI’s consumer findings. BMW is positioned as a brand that generates fun, attractiveness, and self-indulgence. From the perspective of customer relationship, BMW should also communicate trust (I trust BMW, I can count on BMW, etc.) to its customers since improving consumers’ trust in the brand is likely to lead to a significant increase in loyalty or retention.
In contrast to BMW’s position, Mercedes Benz is positioned as a brand that generates respect, knowledge, security, and tradition. Although MB’s position fosters a trust relationship, it is important to be viewed as a true partner by its customers. This can be accomplished by improving such attributes as uniqueness and care about my needs.

Optimize customer lifetime value

In categories such as financial services and telecommunications where individual customer transactions are more frequent, marketers not only want to build strong customer relationships but also want to maximize those customers’ lifetime value (CLV) to their company or brand. CLV is a measure of the value of a customer over the lifetime of that customer’s relationship to the company or brand. It is derived from margin, discount rate, and retention rate.

Retention is the single most important measure that links customers’ relationships and their lifetime value for frequently purchased product or service categories. For automobiles, an infrequently purchased product category, we chose a composite loyalty measure since retention isn’t as meaningful a measure. Whether we predict loyalty or retention, our logic of identifying relevant relationship styles remains unchanged.

Insofar as we can develop a reasonable prediction of retention based on both a battery of 10 relationship attributes and other individual customer data, we are able to develop marketing programs that simultaneously create powerful relationships and maximize customer lifetime value. In our work to date, we have been able to develop those reasonable predictions.

G R O W    O R G A N I C A L L Y

Growth Potential Structure

Growth Potential Structure Web Application
We offer a three-step road map that can help you achieve organic growth for your products.

1. Usage Domain Structure

What market are we in?
A Usage Domain is a cluster of products drawn together by a similarity of end-uses by consumers.

2. Category Purchase Structure

Explain how brand, form, type and other product attributes factor into consumers’ decision to purchase. Category Purchase Structure is hierarchical in nature. The higher a brand is in its structure, the more efficient is its marketing budget.

3. Need States Structure

Define how consumers’ needs explain competition between and interaction with products in each usage domain. Properly developed need states enable marketers to make a clear product association between need states and usage domain.
Loyalty Identifier: this tool analyzes purchase data to determine the switching behavior of consumers and identify where loyalty lies.
Categories, such as flavor or health features, are compared against each other to determine which category carries greater weight in customer loyalty. Within each category, the individual attributes (such as chocolate, peanut butter, fruit, etc under flavor) are also compared against each other to identify customer tendencies to switch to other products.

Benefits & Needs Profiler: this tool analyzes survey data regarding what qualities customers attribute to what brands and creates a map highlighting the strength of these connections.
Like attributes in the Structure Identifier, brands and categories can be combined into new entities. The resulting grid below shows the correlation between attributes and brands/categories/domains. The "Cutoff" input in the toolbar allows you to dictate a percentage of the column's average, where brands higher than (100+input%) * column average will be in green and brands lower than (100-input%) * column average will be in red.

Top Attributes grid: this grid shows the top performing attributes for any given brand/category/domain. By clicking them, you get a pop up of all other brands where the selected attribute also performs well (within the "Threshold" input in the toolbar).

P R O D U C T    D E S I G N
Automobile Interior
Automobile Exterior
A N A L Y T I C A L    T O O L S
We use our industry expertise to tailor solutions to our client's exact needs and situation, creating results that are both foundationally strong and dynamic.
Consumer Research
  • Brand Equity
  • Segmentation
  • Market Structure
  • Choice Modeling
  • New Product Forecasting
  • Concept/Product Testing
CRM Analytics
  • Customer Equity
  • 1-to-1 Personalization
  • Return on Marketing
  • Customer Lifetime Value Analysis
  • Data Mining
Marketing Mix Model
  • Baseline Equity
  • Advertising
  • Pricing
  • Promotion
  • Test/Control

T E C H N I C A L    T O O L S
Our technical expertise provides us the quantitative firepower behind our knowledgebase. All tech solutions are similarly crafted for our clients' particular needs.
Desktop Applications
  • C# and .NET (for Windows)
  • JAVA (Cross-platform)
  • JAVA Web-start (apps deployable from the web)
  • Macromedia Flash
Web Design and Programming
  • HTML and DHTML
  • Javascript, JQuery, AngularJS
  • CSS
  • PHP
  • Apache Tomcat
  • Microsoft IIS
  • Design of user accounts and permissioning
  • Excel Add-ins
  • Word Add-ins
  • PowerPoint Add-ins
  • VBA and Macros
  • Windows Presentation Foundation (WPF)
Software Engineering
  • Microsoft SharePoint
  • Microsoft Project
  • Rational SUITE
  • Developer 2000
  • Visual SourceSafe
  • Oracle
  • DB2
  • Sybase
  • MS SQL Server
  • MS Access
  • MySQL
  • Interbase
  • Postgre
Report Tools
  • Crystal reports
  • JReport
  • Microsoft SSRS
  • Tableau
  • Hyperion
Currently under review by the Asia Research Community (2015)
"Media optimization and measurement (how much to spend and how to measure it) - a special focus on social media."

"How to allocate your media spending between matured products and new product introductions?"

ESOMAR 2004 Asia/Pacific Conference - ranked among the top papers in overall value.
"A Virtual Testing Approach to Improve New Product Success Rates"

Peppers and Rogers Group Asia's First 1to1 Innovator Awards - received honorable mention.
"An In-Depth View of Your Customers – A Clickstream-Based Study Beyond the Web Logs"

International Conference on e-Business (ICEB) 2002 conference
"CRM/Market Research Integration - Technology, Analytics, and Marketing Implications."

Management Consulting
"Lionel Wang has been an excellent partner across our consulting practice. He is exceptionally knowledgeable about all aspects of market research and has helped us with innovate thinking on how and why products compete with each other, what are the drivers of brand equity, and which consumer segments marketers should target. He has applied some very sophisticated analytic concepts to deepen our understanding of behaviors and attitudes that are highly predictive.
His depth of experience in using general consumer research, multivariate analysis, and econometric modeling makes him invaluable for the creation of a comprehensive body of knowledge to drive optimal marketing strategies. Not only does he deliver best-in-class insights but also works collaboratively with cross-functional teams to ensure the analyses drive outcomes that reflect real business world priorities."
- Managing Director, HRCP Insights, a subsidiary of McKinsey & Company

"Booz & Company engaged Lionel to design and implement an extensive modeling program on behalf of a large CPG manufacturer. Dealing with a very tight timeline and relative sparse data, Lionel employed a mix model approach that allowed us to analyze promotion and price elasticity for over 100 product groups in under three weeks.
The results were incorporated into an ROI analysis that uncovered over $50M in potential profit improvement. Throughout, Lionel's creativity, professionalism and work ethic were key success factors. I would recommend Lionel without question for any marketing science engagement, but especially where standard approaches are unlikely to crack the problem."
- Partner, Booz & Company

"Marketing and Innovation's "design your ideal product" application represents a real breakthrough in understanding what consumers want in new products. The drag-and-drop technology makes the questionnaire come to life for respondents and yields new and helpful insights. Marketing and Innovation is responsive, creative and flexible--a pleasure to work with."
- Partner, Marakon, A Charles River Associates Company

Marketing Research
"We entrusted Marketing and Innovation to model Wal-Mart sales in approximately 300 product categories spanning apparel, appliances, cosmetics, consumer electronics, and many other categories. The project involved linking a number of different data sources, the use of a variety of advanced modeling techniques, and the application of experience and judgment. In general, the results were excellent -- and far better than we had a right to expect.
What made Marketing and Innovation so valuable to us was not their terrific understanding of marketing data or their extremely sophisticated knowledge of many useful modeling approaches, but their outstanding judgment in making trade-offs during the data-cleaning and modeling processes. I've never worked with anyone consistently better."
- Division President, The NPD Group

"Lionel Wang is a top Marketing Scientist and is particularly talented in the modeling of behavioral data. Lionel is conscientious, delivers what he promises, when he promises it. His modeling work is first-rate and his judgment (a key asset of any good modeler) is excellent. We value our long standing relationship with Lionel."
- CEO, IPSOS Vantis Worldwide

"We have asked Lionel to help us on our most challenging projects, ones which are out-of-the-box, leverage high-end analytics, link multiple data sources, and require a focused effort over weeks/months. Cooperation, speed, quality, creativity, and actionability have been excellent and results have very well-received by our clients."
- Global Chief Research Officer, IPSOS

"Marketing and Innovation has given us some very valuable insights into optimizing our national advertising campaign. They helped us decide what type of media and what level of media spending works best with our dealer and consumer business."
- Chief Financial Officer, CARFAX, a subsidiary of POLK