Pizzeria_Sales_Analysis

This dataset contains a year's worth of sales data from a pizza place. This dataset includes detailed information about each order, such asthe date and time, the pizzas served (type, size, quantity, price, and ingredients), and additional details.I perform comprehensive analysis and extract actionable insights to optimize business operations and maximize revenue.

Business Understanding

PIZZERIA is the business of selling delicious, freshly made pizzas to a diversecustomer base. Our focus is on quality, variety, and exceptional customerservice to satisfy cravings and build loyalty. We prioritize efficient operations,menu innovation, and data-driven decision-making to stay competitive anddrive growth in the dynamic food industry.

Business Objective

1)Gain insights into customer behavior and preferences.
2) Identify peak hours and busiest days to optimize staffing and resources.
3) Determine the average number of pizzas per order and identify bestsellers.
4) Analyze overall revenue and identify any seasonality in sales.
5) Evaluate the performance of individual pizzas and categories to optimize the menu.
6) Develop targeted promotions or menu adjustments to increase sales and customer satisfaction.

Data Info

Key Insights

Order Analysis

1)Average order value is 38.31 2)Typically 2 pizzas are order per parsel. 3)Top selling pizza are big_meat of small size and the top selling category is classic

Total Orders and Revenue:

With 21,350 total orders generating $817.86k in revenue, it's evidentthat the pizza business is thriving.

Average Order Value:

The average order value of $38.31 suggests that customers tend to spendmoderately per order, indicating a balanced pricing strategy.

Price Analysis:

The Greek Pizza stands out with the highest price of $35.95. This indicates potentialfor premium pricing strategies for specialty pizzas.

Pizza Variety:

Veggie and Supreme pizzas lead with 9 varieties each, indicating strong customerdemand for these options. Classic and Chicken pizzas also have significant variety.

Busiest Hours and Days:

Peak order hours from 12 to 8 pm, particularly on Thursdays and Fridays,suggest targeted marketing and staffing efforts during these periods.

Popular Pizza Sizes:

Large pizzas are the most commonly ordered size, followed by medium,indicating customer preferences for larger portions.

Quarterly Performance:

While order volumes generally increase with each quarter, the 4th quarter shows a slight decline compared to the 1st quarter. Seasonality factor is there in holiday seasons people preferred to go out of the town this might be a factor.

Monthly Performance:

July emerges as the month with the highest number of orders, while November and December have relatively lower order volumes. Seasonal factors and promotional activities may influence these variations.

Weekday Revenue:

Friday and Saturday consistently generate the highest revenue, suggesting increased customer engagement during weekends. However, Sunday revenue is relatively lower, indicating potential opportunities fo targeted promotions or menu offerings to boost sales on this day.

Bestselling Pizzas:

Classic Deluxe and Barbecue Chicken are the most ordered pizzas, indicating strong customer preferences for these flavors. Promotions or special deals on these pizzas can further capitalize on their popularity.

Revenue by Category:

Classic pizzas contribute the highest revenue, indicating their popularity among customers. However, it's important to explore opportunities to promote other categoriesand diversify revenue streams

Recommendations:

Menu Optimization:

We can use customer feedback and sales data to refine the menu, focusing on bestselling pizzas and introducingnew flavors to attract diverse customer preferences. Also we can ask for low and medium range pizza.

Promotional Strategies:

We can leverage peak hours and days to run targeted promotions, discounts, or bundle offers to drive sales during slower periods.

Seasonal Campaigns:

We use tailor marketing campaigns and menu offerings to align with seasonal trends and capitalize on peak demand periods.

Customer Engagement:

By implementing loyalty programs or rewards to incentivize repeat purchases and foster customer loyalty.

Operational Efficiency:

Optimize staffing and operations during peak hours to ensure timely order fulfillment and enhance customer satisfaction.

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