Using Data Reduction Techniques And Brand Performance Measures

918 WordsAug 23, 20154 Pages
Question 1 The data provided has been analysed using Data Reduction Techniques and Brand Performance Measures including Market Share, Penetration and Purchase Frequency to expose the empirical generalisations seen in the snack market. Data reduction principals were used to organise the information and provide ease of understanding to the data. These techniques include inputting the data into a condensed and presentable table, ordering rows and columns by decreasing market share and rounding to two significant numbers (Ehrenberg 1975). Applying these techniques clearly demonstrates the brand that ranks fifth in terms of Market Share, that being Brand E. Brand E has a Market Share of 7%, a Penetration rate of 17% and a Purchase Frequency of 3.65, in comparison to the market leader Brand A, which holds a 35% Market Share. The table demonstrates how larger brands (A, B and C) have higher penetrations compared to the smaller brands. This establishes that the Double Jeopardy Law is in action. The larger brands have more consumers who purchase more often, in comparison with smaller brands, like Brand E, which have fewer customers, which purchase less often (Sharp 2010). This demonstrates that Brand E will have lower loyalty metrics in comparison to the market leaders. Table 1 – Brand Performance Metrics Brand Penetration (%) Purchase Frequency Market Share (%) A 57 5.35 35 B 36 4.59 19 C 28 4.18 13 D 23 3.84 10 E 17 3.65 7 F 13 3.46 5 G 12 3.43 5 H 5 6.78 4 Average 24 4.4 13
Open Document