Product Positioning Analysis

Introduction:
This data analysis looks into how product positioning may or may not have an impact on sales & revenue.

Business question:
Does product positioning influence sales and revenue? Gain insight that can be used to optimise sales.

Data:
The dataset (Impact of Product Positioning on Sales) is sourced from Kaggle.
Data cleaning and wrangling were done using Python libraries.
The product positions provided by the dataset are front of store, end-cap and aisle.

Finding:
1. Sales trend
The three most purchased products are clothing, electronics and food. Seasonal items generated higher revenue than all-year items. This is especially true for Clothing category. Whilst the dataset suggests that competitors offer lower price, sales and revenue trend did not seem to be influenced by this.

2. Product positioning
Taken on its own, product positioning does not have significant impact on sales volume and revenue. However, when taking customer demographics into consideration, the dataset provided several insights.
Aisle: most liked by the Seniors, but most revenue driven from Families
End-cap: most liked by College students, but most revenue driven from Young adults
Front of Store: most liked by College students, but most revenue driven from Families

Recommendation:
1. Families category is the highest revenue generating, so keeping them engaged is crucial. Company could try to introduce some new products in Families-preferred positions to try and increase more sales. Company could also enrich their loyalty programmes by including more family-targeted deals and/or rewards.
2. College-students were the biggest spenders in End-cap and front of store. Company could include more college-preferred products such as affordable food items, sporting equipment and study necessities (reading lights, hooks etc).

Conclusion:
Whilst there is no significant contribution was observed between different positions and sales & revenue, the data suggests that different customer demography prefers different positions. This insight can inform decision makers on shop layout to maximise sales & revenue.