Pricing research involves first a pricing strategy assessment supported by strong pricing research capabilities.
Sound pricing market research requires a broad strategic
perspective together with a focus on your pricing decision options.
Pricing research finds optimum price-product-feature
configurations in the context of market positioning opportunities. In Pricing
studies, we employ both qualitative research and quantitative research tools.
Pricing research usually concentrates on customers' sensitivity to
pricing. This price sensitivity is driven by the nature of the market, the
target within that market, the differentiation level of product or service, and
the value of brand.
Pricing is one of the more technical areas of market research.
There are four main approaches:
Several different research methods are commonly used in pricing
research—each with their own strengths and weaknesses. There are four
techniques that are commonly used the four techniques are:
1. Gabor-Granger or Van Westendorp Price Sensitivity Meter
2. Concept Test
3. Conjoint Analysis
4. Discrete Choice Modeling
1. Gabor-Granger or Van Westendorp Price Sensitivity Meter
(PSM)
In Gabor-Granger pricing research customers are
asked to complete a survey where they are asked to say if they would buy a
product at a particular price.
The price is changed and respondents again say if they would buy
or not. From the results we can work out what the optimum price is for each
individual.
By taking a sample of customers we can work out what levels of
demand would be expected at each price point across the market as a whole.
Using this estimate of demand, the price elasticity (or expected
revenue) can be calculated and so the optimum price-point in the market
established.
The Price Sensitivity Meter (PSM) is used frequently by some
researchers. The premise of the PSM is to ask respondents four price-related
questions and then evaluate the cumulative distributions for each question.
Specifically, respondents are asked:
1. At what price would you consider the product to be so
expensive that you would not consider buying it? (Too expensive)
2. At what price would you consider the product to be priced so
low that you would feel the quality couldn’t be very good? (Too cheap)
3. At what price would you consider the product starting to get
expensive, so that it is not out of the question, but you would have to give
some thought to buying it? (Expensive)
4. At what price would you consider the product to be a
bargain—a great buy for the money? (Cheap)
In this method, the optimal price point for a product is the point
at which the same number of respondents indicate that the price is too
expensive as those who indicate that the price is too cheap. Many pricing researchers
question that this is the definitive optimal price for a product.
2. Concept Test/Concept Evaluation
The standard purchase intent question from a concept test is also
commonly used for pricing research.
Respondents are presented with a product concept and asked how
likely they would be to purchase this product at a specific price.
Typically the researcher will expose independent samples of
respondents to different prices. The standard purchase intent question is shown
below.
• (After introducing the product concept)
• How likely, would you be to purchase this product in the next
12 months if it costs Rs 9000?
• Definitely would purchase
• Probably would purchase
• Might or might not purchase
• Probably would not purchase
• Definitely would not purchase
• To evaluate price sensitivity using this example, a sample of
respondents evaluates this concept at Rs 9000, a different sample of
respondents evaluates the same concept at Rs5000, and another sample of respondents
evaluates the concept at Rs 14000.
A demand curve is constructed by evaluating purchase intent at
each price.
3. Conjoint analysis:
Conjoint (trade-off) analysis is one of the most widely-used
quantitative methods in Marketing Research.
It is used to measure preferences for product features, to learn
how changes to price affect demand for products or service, and to forecast the
likely acceptance of a product if brought to market.
Like concept tests, conjoint analysis presents concepts to respondents. However, instead of exposing each respondent to a single concept, in conjoint analysis each respondent is exposed to many concepts. For each treatment, respondents are asked to make hypothetical trade-offs between configured products. For example, a respondent might be asked to express his preference between two smart phone hand sets alternatives or between two VCR alternatives.
In conjoint analysis, respondents are forced to make trade-offs
between products and product features, much as buyers are forced to do when
actually shopping.
Each respondent answers a series of trade-off questions; in each question the combination of features shown together changes. In this way, a large number of product features can be evaluated.
Each respondent provides enough information through his or her
trade-offs that the utility of each product characteristic (including price)
can be estimated for each respondent.
This individual-level estimation allows for the identification of
individual differences that can lead to a market segmentation scheme and can be
used to help predict acceptance of products by different individuals in a heterogeneous
market.
These utilities also allow prediction of preference for any
product that can be defined using the product characteristics in the study.
These preferences can be modeled in a market simulator. A market
simulator allows “what-if” analysis for any configuration of products in any
competitive environment. A demand curve can be produced from these simulations.
4. Discrete Choice
Choice-Based Conjoint (CBC) is used for discrete choice
modeling, a research technique that is now the most often used
conjoint-related method in the world. The main characteristic distinguishing
choice-based from other types of conjoint analysis is that the respondent
expresses preferences by choosing from sets of concepts, rather than by rating
or ranking them. The choice-based task is similar to what buyers actually do in
the marketplace. Choosing a preferred product from a group of products is a
simple and natural task that everyone can understand.
CBC is often used to study the relationship between price and
demand, and is especially useful when the price-demand relationship differs
from brand to brand, and when only a few features need to be considered.
One of the strengths of CBC is its ability to deal with
interactions, such as when different brands have different sensitivities to
price changes. Most conjoint methods are based on "main effects only"
models that ignore the existence of such interactions. In contrast, CBC may be
used to evaluate all two-way interactions.
The researcher must decide on attributes and their levels, and
compose whatever explanatory text is desired for the interview screens. Apart
from that, everything can be done automatically. The CBC System provides all
the tools needed to conduct a choice-based conjoint study via Web, CAPI (PCs
not connected to the Web), or paper-based surveys. The CBC system includes
three analysis modules and a market simulation module for testing "what
if" scenarios.
In discrete choice, the respondent is presented with a set of products and the respondent is asked to pick one.
The results from discrete choice modeling are very similar to
those from conjoint. For instance, both approaches are able to produce
utilities at the individual level, and both discrete choice and conjoint allow what-if
simulations. Discrete choice modeling has been used with great success in
pricing research.
