Analyze the laptop sales across multiple retail outlets in the year 2015 to determine optimal pricing strategies and store locations for maximum sales in 2016.
- Tableau Public
- Tableau Desktop Public Edition
- The best-selling laptop configurations are identified.
- The avg. price for these configurations over the course of the year, along with store-wise monthly and daily sales volumes, are analyzed.
- The avg. distance between customers and retail outlets is analyzed.
- The impact of store proximity to the customer on store sales is studied.
- Finally, a dashboard and storyline are used to weave the above analysis together.
- The best-selling laptop configurations show a downward trend in price (month-on-month basis).
- Some stores have a considerable dip in price in the months of March, June and December. It is worth exploring the root cause for this, and further analyzing whether this leads to higher/lower sales at the corresponding stores. If this strategy leads to higher sales, it can be applied across more stores.
- Overall laptop sales are greater in the 2nd half of the year. The retail chain can either double down on this period to increase sales, or introduce attractive offers in the first half of the year to drive up sales in the lean season.
- Low avg. prices in stores dont necessarily lead to high sales volumes. This means that the retail chain can consider maintaining a higher avg. price (at least for top config laptops) to achieve higher margins, as low prices dont attract more customers.
- Laptops with low-grade attributes are priced lower. The stores can experiment with inventory levels of these models to make room for the more lucrative ones.
- Customers travel an avg. distance of 4210 units to reach an outlet. Stores with lower avg. distance (i.e. higher proximity to customers) yield higher laptop sales, indicating the customers may spend more if they have to travel less. Thus, the chain should scout locations for new stores for 2016 and subsequent years that are closer to customers.