Applying Advanced Analytics
to B-to-B Branding Research
by
John Colias, Ph.D.
The importance of branding is understood by serious business-to-business marketing
researchers, but when it comes to analyzing brand equity, most companies fail
to use advanced analytics to its full potential. All too often, branding studies
simply track key measures; they fail to quantify causal relationships, and deliver
weak predictive power. Or, if research attempts to deliver statistical models,
the models identify key attributes and their relative importance, but do little
else.
To be sure, some useful information and knowledge can be gleaned from these
expedient solutions. In most cases, however, there is little insight to guide
branding strategy and define concrete actions that impact brand equity. When
it comes to the practical application of branding research, senior management
is usually underwhelmed.
Most senior managers are not very patient when it comes to long-term branding
assessments. They want to know what customers expect from their brand and why
they choose it versus competitive brands. When they invest in marketing research,
they are looking to the findings for guidance on achieving immediate marketing
goals and for making strategic decisions that will impact the future.
With the increased emphasis on accountability, measurement and ROI in B-to-B
marketing, the focus is often on measuring the efficacy of tactical programs.
While necessary, these assessments don’t lead to insights that impact
strategic decisions about what new direction a business should take.
Management is asking questions such as: Where should resources be allocated
for differentiation? What actions should be taken to have the greatest impact
on customers choosing our brand? What will be the impact of these actions on
our competitors?
New Tools Enhance the Value of B-to-B Branding Research
B-to-B branding research can be a far more effective strategic tool for understanding
a company’s brand and factors that make up its brand equity. Advanced
factor analysis, regression and simulation tools enable B-to-B marketing researchers
to quantify brand equity and predict, virtually in real-time, the impact of
specific actions on the company’s brand and on competitive brands.
As shown in Diagram 1, Factor Analysis identifies examples of observed brand
attribute ratings which best indicate the relative performance of firms, as
perceived by those who influence the buying decision. A rational assessment
of the brand is formulated based on objective personal experience or verifiable
information from others. Rational assessments are typically empirical in nature.
Simultaneously, an emotional assessment of the brand is based on experience
and communications, filtered through personal beliefs and attitudes. The rational
and emotional assessments influence each other and ultimately cause changes
in brand attributes reflected in survey ratings.
Diagram 1
Additional Factor Analysis identifies which overall indicators
best measure Brand Equity. Diagram 2 shows how Brand Equity has three dimensions—exposure,
affinity and preference. The overall indicators of brand equity measure success
within each of these dimensions. For example, high levels of awareness, familiarity
and purchases indicate high exposure.
Diagram 2
Latent-Class Factor models quantify the structures in Diagrams 1 and 2. For
example, when the desired observed ratings (Diagram 1) are selected, the model
Latent-Class Factor models quantify the structures in Diagrams 1 and 2. For
example, when the desired observed ratings (Diagram 1) are selected, the model
provides the appropriate weighting of these ratings which are used in the next
step in the analysis: Latent-Class Regression
Latent-Class Regression quantifies the causal linkages from
perceptions (rational and emotional) to the components of brand equity (exposure,
affinity and preference). Latent-Class Regression delivers the added benefit
of greater predictive accuracy. Greater accuracy is attained by breaking the
unrealistic assumption that all customers are alike, an assumption ingrained
in older regression techniques.
Diagram 3 shows a comprehensive analysis beginning on the left with observed
brand ratings and perceptions of the brand (from Diagram 1). In the center is
the Latent-Class Regression model that links brand perceptions with brand equity
components. On the right are the overall indicators of brand equity (from Diagram
2). This model allows marketers to predict changes in brand equity and its overall
indicators by inputting changes in observed ratings.
Diagram 3
For example, if the model were to be used to simulate an improvement of the
quality rating by 5%, then brand equity might be predicted to improve by 3%.
This 3% improvement in brand equity might, in turn, be predicted to increase
Recommendations for the brand by 2%. Combining Latent-Class Factor and Regression
models into a simulation tool allows marketers to simulate alternative strategies
causing changes in brand equity. This helps senior management define a viable
brand strategy and investigate dozens of strategic alternatives to achieving
set goals. Building advanced analytics, simulation and modeling into branding
research transcends measuring awareness, interest and perception, and offers
marketers the ability to make better strategic decisions faster, and with what
implications. Marketing research has a seat at the decision-making table thanks
to the strategic value it brings.
How Does B-to-B Brand Equity Monitor Stack Up Against
Conventional B-to-B Awareness and Branding Studies
| Key Strategic Marketing Questions |
Awareness Studies |
Branding Studies
|
B-to-B BEA |
| To what extent
are our customers aware of us vs. our competition |
x |
x |
x |
What is their
level of affinity for our company?
|
|
x |
x |
| To what extent
do they prefer our competitors? |
x |
x |
x |
| How do certain
actions impact the strength of our brand? |
|
|
x |
| How will certain
actions impact the strength of our competition? |
|
|
x |
| Can I discern
the impact of the considered actions virtually and in real-time? |
|
|
x |
The B-to-B Brand Equity Monitor is a purpose-built tool for B-to-B marketers,
jointly developed by Godfrey and Decision Analyst, a leading global marketing
research company headquartered in Arlington, Texas. The B-to-B Brand Equity
Monitor is a strategic tool for assessing the strength of a company’s
brand relative to competitors in its market. Through the use of advanced analytics
and modeling, it offers insight executives need to make better strategic decisions
that will drive business success. The B-to-B Brand Equity Monitor is the only
business tool that fits this requirement.
Copyright © 2009 by Decision Analyst, Inc.
This article may not be copied, published, or used in any way without written
permission of Decision Analyst.
About the Author
John Colias (jcolias@decisionanalyst.com)
is a Senior Vice President and Director of Advanced Analytics at Dallas-Fort
Worth based Decision Analyst. He may be reached at 1-800-262-5974
or 1-817-640-6166.
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