In the completely randomized design, which is the simplest of the formal designs, treatments are assigned to test units on a random basis. Thereafter, analysis of variance is performed to determine whether these treatments caused a significant difference in outcome amount these units (test units). The design can, however measure only type of variance which occurs between treatments.Suppose, a supermarket chain is selling washing soap in packets of one kilogram each. but they don’t know that what price should be charged for a packet exactly. They test three different price per packet Rs. 7.00, Rs. 6.50 and Rs. 6.00. They record the sales by each prices. They randomly assign these prices to the twelve experimental stores four of which are using each price.

The analysis in this case would emphasis the average amount of the soap sold at each price. The analysis can show whether the differences in sales are significant ones or whether sampling error might have been involved. It does hardly take into account various extraneous factors such as competitors’ prices, climatic conditions, store, size, etc., such factors have wide ranging influences on the results of such studies.

It is assumed that all the extraneous variables have an equal impact on the units under test. This is also listed as a limitation of previously discussed informal designs. Such an assumption may hold good in laboratory y experiment but not for the experiments conducted in the real world situations of the environment. It is this reason that the design is not very popular for use in experiments of marketing research problem conducted in the field settings.

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