CHAPTER 4 PRICE SENSITIVITY
The objective in trying to measure price sensitivity must be, not only to determine the relative price sensitivities of different segments, but also to measure the absolute price sensitivity, or the price elasticity of demand for a specific segment. Where a number of segments use exactly the same product and the actual average transaction prices are known, this information
should provide an approximate rank order of the price sensitivities of the
segments. This is very useful but only applies when the same product is used. Also, even in this case, the average prices do not indicate the degree of price sensitivity of each segment, only the rank order.
4.1 Estimation of price sensitivity
The approach taken initially to resolve this dilemma was to try to determine what weight the customers in a segment would apply to the need for a low
price using the same rating scale as was used in the last chapter for non-price needs. However, while it seemed likely that price would always be as important as anything else it was difficult to decide how important it is in
reality. After experimenting with downstream oil products such as lubricants, aviation fuel, gasoline etc. and reviewing these with industry participants, we
could agree on rank orders of price sensitivity for segments using the same
products but we were unable to develop realistic price weights based solely
on their judgement.
The next step was to compare the importance of a low price with everything else in total, or, in other words to add all the weights for the non-price needs and try to develop a weight for the low price relative to this total. The low
price need weight would thus be based on a ratio of the price need weight to the total of all the other need weights. After further experimentation, it
became clear that the importance of price was related to how much variability existed in the actual prices paid in each segment and, in particular,
that the more variability there was the less important price was to the buyers.
Also, the idea of the price weight increasing the more like a commodity the
market segment is and vice versa also seemed to make sense. In fact it is very
easy to think of segments that would fit at either extreme. For example, large
volume gold transactions, a pure commodity market, take place within an
extremely narrow range of pricing at any point in time, i.e. very low percent price variability, and the only determinant of whether or not a transaction
takes place is price, since the product is by definition, gold of a certain purity.
At the other extreme we find segments for which the value of a product lies largely in the eye of the beholder such as artwork, perfume, designer clothes
etc. However, what is also very obvious is that for these extreme cases, the
curve is not very useful and if all markets were either commodities or highly
personal products we would not need a curve at all; what obviously does matter is what the curve looks like between these extreme
There are three ways to determine the shape of the curve. The first, and easiest is to try different shapes, calculate the price weight and test the results with people who know a particular business very well. This has been done with many groups and in many markets until those groups are comfortable with the end results produced.
The second test is to use the resulting need profiles in combination with the performance ratings for the various competitors and see how accurately market shares can be predicted. This process is described in Chapter 8 of this book; for the present, suffice it to say that it has been done very successfully in a wide variety of industries and geographic locations.
The third test, assuming that the second test has been satisfactorily completed, would be to change one competitors price and see what effect this has in practice, in terms of the changes in shares and how that result compares with the theoretical expectation.
Unfortunately, conditions in the real world do not remain constant long enough, in most instances, for this test to be completed, since other competitors react to the price changes before the full impact of the first price change can be calculated. However, it would certainly be worth tracking some real situations in which this occurred and measuring the timing of reactions and the end result.
Nevertheless, the curve has been used in enough situations using the first two tests, for there to be a reasonable confidence level in its utility for practical marketing purposes.
It transpired that the curve is extremely simple an looks like Figure1 below.