This example pertaining to the opening of a new petrol station is based on analysis of loyalty panel data. It computes the trial, repeat usage rate and usage index to provide an estimate of the outlet’s share or contribution within chain. It also examines the source of volume of the new station, and the overlap in usage of the motorists frequenting the new station with the chain’s other stations.
For a new outlet to flourish, it must develop a base of regular customers — i.e. motorists who try it and continue using it. The outlet’s success hinges therefore on trial and repeat usage.
Trial or cumulative penetration at a time t is the percentage of customers who transacted at the outlet from the time it was opened till time t.
As can be seen from Exhibit 29.6, the proportion of loyalty card holders who pumped petrol at the new station rose steadily to 21% by the 47th week after its opening. The penetration of the other petrol stations in the chain has also been increasing over time, and total penetration (all stations) is 96% in week 47.
The stable repeat usage rate (RUR) estimate was 28%, and the usage index was 1.02. These measures akin to RBR (repeat buying rate) and buying index are covered in detail under the TRB Share Prediction model in Chapter Product Validation. Based on this model, the estimated contribution of the new petrol station to the chain’s total volume is 6.0% (=21% × 28% × 1.02).
It would interest the chain’s management to know how many of the motorists who frequent the new station exclusively pump at that station, and how many of them are "duplicators" who are also pumping at the chain’s other stations. This information may be gleaned from the overlap analysis which is also presented in Exhibit 29.6.
The overlap analysis splits the chain’s base of loyalty card holders into three groups depending on where they fill petrol — only new station users, new and other stations users (i.e. duplicators) and only users of other stations.
The analysis reveals that 8% of the loyalty card holders pump the chain’s fuels exclusively at the new station. These motorists may also be going to competing chains, but they have not been going to the chain’s other stations. They therefore represent the incremental gain in motorists resulting from the addition of the new station. It is also possible to analyse these motorists further in terms of measures such as their consumption levels, and how that compares with the chain’s other motorists.
The presence of "duplicators" suggests cannibalization. This is inevitable whenever a new station is added to an existing chain. Gain–loss analysis can reveal the extent to which the new station increases the amount of petrol the duplicators consume at the chain, and the extent it cannibalizes other stations belonging to the same chain.
Refer to Chapter Consumer Panel for details on the gain–loss methodology. The analysis depicted in Exhibit 29.7 reveals the sources of volume for the new petrol station. About 21% of the volume is from motorists who started purchasing fuels from the chain only after the new station opened. This is purely incremental volume for the chain.
Also incremental is the 50.4% of the volume of fuels sold at the new station, which represents an increase in fuel consumption at the chain by motorists who were pumping at the chain’s other petrol stations. The remaining 29% is due to cannibalization. This is the proportion of business that the new station acquired from other stations belonging to the chain.
The high incremental volume (50.4% + 20.7%) suggests that the new outlet gained considerable volume from competition. However, since the analysis is based on the chain’s loyalty data, it is not possible to identify which competing petrol stations contributed to the new outlet’s growth.
The data does however reveal which of the chain’s petrol stations were cannibalized by the new station, and how much volume the new station acquired from these outlets. This analysis is presented in Exhibit 29.8. It tells us that the majority of the cannibalized (switching) volume (65%) came from station A. Stations D, B and C were also substantially affected.
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