Driver
analysis as a technique is widely used by marketers to understand
which brands or product/service attributes have the greatest influence on
consumers’ purchase decision. For instance, consumers might rate a personal
care product based on its colour, scent, functionality, price, brand
ambassador, whether there is a discount offer, and so on.
All of this
will eventually help marketers in:
-
Identifying the right product offering for
launching a new brand/variant
-
Narrowing in on the right target group for their
brand
-
Designing the right sales & marketing
communication strategy
Consumption is
driven by different kind of needs. As per the Hierarchy of Needs by Maslow,
people are motivated to fulfil the most basic needs before moving onto more
advanced needs. At the lowest level are the most basic, physiological needs. As
we move up, are safety needs, social needs, self-esteem and finally
self-actualization needs at the top of the pyramid.
Driver
analysis helps us identify the consumer needs which translates to purchase
behavior - if it’s functional aspect (physiological or safety needs) or if it’s
imagery in consumers’ mind (having an ipod is considered cool by friends and
adds to the self-esteem) or if the customer is delighted with his experience
and is extremely loyal to the product (“I know this is what I want, don’t
really care what others say about it”--self-actualization).
Driver
analysis is the statistical effect of many independent variables on the
dependent variable, which is our focus. For instance, sales of a product might be driven by a variety of factors like
functional attributes like price, likability, quality or emotional attributes
like brand imagery.
How do we
prioritise the Key Drivers?
There are many statistical techniques for the analysis, simplest being correlation analysis, to determine the association with a product’s overall performance & the perceived performance of brand on separate attributes. Though it is simple, it doesn’t discriminate between the most important & the least important attributes.
A second
method is multivariate regression,
which explains overall market performance as a function of ratings on separate
attributes. However, due to multi-collinearity (correlation amongst the
independent variables) they can cause aberrant results. For instance, it may
appear that 2 attributes are very important, but due to multi-collinearity, we
may not be able to measure their unique influence.
Another
approach used by industry experts which proves to be better than the above
mentioned methods is path analysis. SEM
or Structural Equation Modeling is a widely used Path analysis technique.
SEM
identifies the relationship that an observable customer behaviour (like
purchase intent, satisfaction levels etc.) has with latent constructs. These
latent constructs cannot be measured directly, instead factor together
variables that show similar customer behaviour. SEM however, is a confirmatory
and not an exploratory approach. It requires a clearly defined hypothesis to begin with.
Another
approach developed in the recent times, is Bayesian
networks. It is a graphical model that encodes probabilistic relationships
among variables. This is much simpler to execute as compared to SEM. Combined
with Bayesian statistical techniques, it has the scope for exploratory analysis
and doesn’t require a hypothetical model.
Case
Study: A leading hair
care manufacturer wanted to identify drivers of brand
preference for the category which would aid them in designing the right communication
strategy
Framework:
- Built a Structural Equation Model (SEM) to identify key equity
themes and their hierarchy in terms of importance in driving purchase for the
category, for each of the markets
- Identify the best pathway to improve brand’s equity in target
consumer’s mind for each of the markets
Result:
The following
recommendations were made and implemented by the business:
- Leverage brand’s strength on the “health” dimension which goes in
line with brand’s equity pyramid
- “Ingredient” is one of the key category drivers on which the brand
is performing very well--strengthen communication strategy to capture this
- Even though health benefit is the key, consumers eventually desire
the beauty aspect – redesign communication strategy to convey this as the end
benefit
- Currently “beauty” dimension is weak – build credibility on that
with consistent communication
More details on the case study can be found here.
