Uploaded by Paweł Tomasz Kracki


Pawel Kracki
INDIVIDUAL ASSIGNMENT (30%), Deadline >> February 12th 2019
Answer the following questions in max. 20 lines.
You sell a given product through 1000 shops, and the average revenue for that product is K€2.4 per
week per shop, with a standard deviation of K€3.1. You want to analyze if the offer "Three for the
price of two!", in short 3x2, would be effective on your revenue. To do that, you introduce the offer
in 50 shops for 1 week. Describe which data you would collect and what you would do with them.
Would you recommend any special care in selecting the shops?
We can observe that the standard deviation is higher than the mean what means that the data are
widely spread. If we assume Gauss distribution, the probability that the shop will not generate
income or generate loss is on the level of 0.22 (integral from - to 0). If all shops would be ‘the
same’ we could select them randomly, however in reality this is not true and different shops
selection may result in different results especially when the test sample is only 0.05 of the
population. Important factor to consider is the buying frequency. If we promote the product in
wrong time and wrong shop, we will not see any improvement. The shop location and size is also
important factor – selecting all the shops in small area most probably give worst results than
selecting bigger shops in more dispersed locations. ‘Attractiveness’ of the shop is also important
especially if they offer delivery or on-line services. 3x2 is a common form of sales promotion derived
from BOGOF (Buy one, get one free). The data we will need to collect before, during and after the
promotion in all of the shops (with and without promotion). We need to see if our product is sold
separately or it is bought together with other products. This let us verify kind and strength of the
correlation between them and maybe decide to adjust the offer. We will need to know how often
people are buying more than one our product at the same time. This will tell us how new offer is
impacting the sales volume – we can do the mean test. Based on this we will be able to calculate
and compare average revenue and costs (delivery/storage…) before, during and after the offer. In
the end we can verify if the revenue increased by doing the mean test (or 2 means) and check the
impact on the standard deviation (we can try to use the variance test). Checking if the customer
satisfaction and repurchase intention are corelated can be used for forecasting.
Less than 0: Standard normal: area to the right of 0.774194 = 0.780592, (to the left: 0.219408)
“Focus of the business in BOGO scheme is volume and not
price, the factor price is not found to be significant. The aim
is to increase sales, attract new customers and keep the old
customers. “ by
Thomas, P. and Chrystal, A. (2013). Explaining the “Buy One Get One Free” Promotion: The Golden
Ratio as a Marketing Tool. American Journal of Industrial and Business Management, 3(8), pp. 655673. doi: 10.4236/ajibm.2013.38075 - http://openaccess.city.ac.uk/16301/1/BOGOF.pdf