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Implementation of A/B testing in a study of a fast-food restaurant aiming to identify which marketing strategy is most successful in generating the highest sales of their new product.

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Implementation-of-A-B-Testing

Case Study

Here, I will attempt A/B testing in a study of a fast-food restaurant aiming to identify which marketing strategy is most successful in introducing their new product. The success metric will be measured by the total sales of the new product.

  • Promotion type 1: Flash sale discount
  • Promotion type 2: Special cashback point
  • Promotion type 3: Bundling deals

Data Source

Fast Food Marketing Campaign (https://www.kaggle.com/datasets/chebotinaa/fast-food-marketing-campaign-ab-test/data)

Output, Method, and Tools

  • Output: Difference test result, post-hoc test, and dashboard
  • Method: test of mean difference (parametric test: ANOVA) and test of median difference (Kruskal-Wallis Test)
  • Tools: python and power bi

Results

  • In general, the total sales achieved by each restaurant varied significantly depending on characteristics such as location, market size, and the restaurant’s age.
  • Some findings also revealed that certain groups of restaurants achieved higher sales compared to others.
  • Furthermore, under certain conditions, the three marketing strategies showed significant differences in total sales. This indicates that one or two strategies were deemed more effective than the others.
  • For more detailed analysis and recommendations, please refer to the listed pdf documentation.

If you have any suggestions or feedback, please don't hesitate to contact to me in direct message on Email or LinkedIn: [email protected] or https://www.linkedin.com/in/novia-anggita-aprilianti/

#abtesting #marketresearch #marketingcampaign #python #anova #kruskalwallis #dashboard #powerbi

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Implementation of A/B testing in a study of a fast-food restaurant aiming to identify which marketing strategy is most successful in generating the highest sales of their new product.

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