Pepfavs

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  Varities of food offered by PepsiCo. Categorized into 4 clusters.

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  Cluster 1 Demographs insights

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  Cluster 2 Demographs insights

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  Cluster 3 Demographs insights

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  Cluster 4 Demographs insights

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  Overview of the project

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  ETL Process

We are inspired by the problem statement that has pepsico has stated that deals with the customer engagement success which likewise increases the sales of the products ## Inspiration

Our Model emphasizes the owners to make the successive decisions based on the insights drawn to improve the customer success engagement. ## What it does

The tools used to build the model were excel that helped us in the cleansing of the dataset, Tableau prep that has helped us in the ETL process along with the operations on the data and R Studio to develop machine learning model## How we built it

Data cleansing of the open source dataset on PepsiCo products has took most of the time of the development process. Applying the functionalities to achieve the goal of merging the dataset.

Challenges we ran into

We are proud to work on a real time dataset that drawn impactful insights to the corporate. ## Accomplishments that we're proud of

Usually, we have an access to customer profiles or demographic data when crafting a marketing strategy. In this case, we only had sales data to start with. The challenge was to bridge the gap between sales figure and customer demographics to finally arrive to marketing strategizing. We learned a new workflow of marketing analytics. ## What we learned

What's next for Pep co. favorites

Built With

• excel
• tableau
• tableauprep