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Were Kettle’s Sales Calls Effective In Tesco? Nigel Marriott Chartered Statistician May 2007

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Data Used In Analysis Total Kettle Crisp Brand sales per store only. Value sales & % uplifts from control period as calculated by Storecheck. Sales from all 1454 stores were included Stores grouped into Call/No Call only. –The type of sales call was not analysed.

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Sales teams called upon 188 stores in the 4 weeks prior to Xmas. These sales have been compared with the stores not visited. Rather than use weeks, I have grouped the weeks into 4 weekly periods as shown for clarity. We see that sales trends in the two periods prior to the Calls were similar for both groups of stores. This means we can compare the two groups during the sales call period.

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What we want to see are similar uplifts in the Baseline & PreCall periods and higher uplifts in the stores called upon in both the Call & PostCall periods. Statistically this is known as an Interaction effect between Time Period & Call Status. Based on this chart it appears that the sales calls led to an additional uplift of 72% during the Call period and -14% during the post call period.

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A 2-factorial ANOVA is the simplest way to see if the sales calls achieved a statistically uplift. The two effects we are interested in are Time Period & Call Status. In addition, there is a 3 rd effect which is the Interaction between Time Period & Call Status. We want all three effects to be statistically significant since 1.We want uplifts to be higher during the Call period (Period effect) 2.We want uplifts to be higher in stores that called upon (Call Status effect) 3.We want uplifts to be higher in stores called upon during the Call period (Interaction effect) For these effects to be statistically significant we would be looking for P-values under 10% for all 3 effects and this is definitely the case here. Therefore we conclude that the sales call did lead to a statistically significant uplift.

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Conclusions & Recommendations Kettle’s sales calls in the run up to Christmas 2006 had a statistically significant effect on the total value sales of the brand. The effect was an additional uplift of 72% in the stores called upon. The ANOVA test used here to establish statistically significant differences is quite easy to code into a software package to allow users to perform their own statistical tests. However, the 2-sample T-tests and the ANCOVA tests would also need to be coded as sometimes these tests are more appropriate than ANOVA.

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