Instacart Grocery Basket Analysis
Analyzed Instacart order data to uncover purchasing patterns, predict future buys, and optimize product recommendations, providing insights to enhance customer experience and marketing strategies.
Audience
Instacart stakeholders
Data
Instacart provided us with four datasets:
Orders
Products
Orders_products_prior
customers
Techniques used for the project:
Jupyter Notebook
Writing and executing Python code
Data wrangling and subsetting
Consistency checks and merging data frames
Grouping, aggregating and deriving variables
Data visualization with Python
Key Busniess Questions
● What are the busiest days of the week and hours of the day?
● Are there particular days of the week when people spend the most money?
● Can we use a simpler price range category for our products?
● Which departments have the highest frequency of
product orders?
● What’s the distribution among users in regards to their brand loyalty?
● Are there differences in ordering habits based on a customer’s region?
What are the busiest days of the week and hours of the day?
Busiest Days:
Saturday
Sunday
Friday
Busiest Hours:
Between 9:00 am - 3:00 pm
Slowest Days:
Wednesday
Tuesday
Slowest Hours:
Between 11:00 pm - 6:00 am
Are there particular days of the week when people spend the most money?
Days when customers spend the most money:
Saturday
Friday
Which departments have the highest frequency of product orders?
Busiest Departments:
Produce
Dairy/Eggs
Snacks
Can we use a simpler price range category for our products?
Price Range Groupings:
Low Range Products = Less than $5
Mid Range Products = Between $5-15
High Range Products = Over $15
What’s the distribution among users in regards to their brand loyalty?
Customer Loyalty Categories:
1. Loyal Customer = 41+ orders
2. Regular Customer = 11-40 orders
3. New Customer = 1-10 orders
Are there differences in ordering habits based on a customer’s region?
No strong trends were discovered for regional ordering habits. The South region is Instacart’s biggest, while the Northeast is the smallest.
Instacart Insights and Recommendations
Insight:
1. Busiest days: Saturday and Sunday. Least busy days: Wednesday and Thursday.
Advertise and run commercials on Tuesdays and Wednesdays to boost sales on the slower days. Offer free incentives such as free delivery and/or free gallon of milk or dozen eggs with every purchase over $50 on Tuesday and Wednesday.
Recommendation:
Insight:
2. Customers spend the most on Friday and Saturday.
Instacart could use this for marketing purposes by running ads and promotions for more expensive products such as alcohol, steak, seafood to drive sales even further.
Recommendation:
There could be a marketing campaign advertising that alcohol is available for delivery through Instacart. Instacart may be able to 1) Gain new customers who want the convenience of liquor delivery, and 2) Grow sales by selling alcohol to loyal customers. Most alcohol purchases are minimum $15, with some being over $100. This would be a great way to add in and sell more ‘high-range’ products.
3. Instacart doesn’t have many ‘high range’ priced products.
Insight:
Recommendation:
Insight:
4. Instacart's has tons of ‘mid range’ price level products, and not as many ‘low range’ products. There should be a push to sell more ‘low range’ products to boost each sale by $1.00-5.00. That can equate to millions of dollars in additional revenue over the course of a year.
One of the biggest ways companies can boost sales and revenue is by encouraging impulse purchases and upselling low-range products. Instacart could have a little pop up at the end of the checkout process that encourage purchasing things like gum, drinks, candy, etc.
Recommendation:
Insight:
5. Most of Instacart’s customers are Regular customers.. New customers are Instacart's smallest group.
The fact that the vast majority of Instacart customers have ordered 10+ times, means that customers are happy with Instacart. We just need people to order from Instacart once to get them hooked on the service. Instacart should offer very generous deals to first time customers in order to get people to try the service and get hooked on using it.
Recommendation: