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Analyzing business performance using PostgreSQL based on several business metrics : Customer Growth, Product Quality, & Payment Types

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Data-Portofolio/Analyzing-eCommerce-Business-Performance-with-SQL

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🎨ERD
🏡List of Datasets
TableAtribut
Customerscustomer_id
customer_unique_id
customer_zip_code_prefix
customer_city
customer_state
Productproduct_id
product_category_name
product_name_lenght
product_description_lenght
product_photos_qty
product_weight_g
product_length_cm
product_height_cm
product_width_cm
Sellersseller_id
seller_zip_code_prefix
seller_city
seller_state
Ordersorder_id
payment_sequential
payment_type
payment_installments
payment_value
Order_itemsorder_id
order_item_id
product_id
seller_id
shipping_limit_date
price
freight_value
Reviewsorder_id
review_id
order_id
review_score
review_comment_title
review_comment_message
review_creation_date
review_answer_timestamp
Paymentsorder_id
payment_sequential
payment_type
payment_installments
payment_value
Geolocationgeolocation_zip_code_prefix
geolocation_lat
geolocation_lng
geolocation_city
geolocation_state

Annual Customer Activity Growth Analysis

  • Monthly Active User (MAU) : metrik yang digunakan untuk mengukur jumlah total pengguna unik yang berinteraksi dengan aplikasi selama 30 hari. Menghitung MAU juga membantu pemasar produk memahami perilaku pengguna di aplikasi mereka dengan lebih jelas. Memahami perilaku pengguna dapat membantu menginformasikan keputusan tentang fitur produk dan pembaruan desain berdasarkan umpan balik pengguna atau tren dalam pola penggunaan di berbagai versi atau demografi.MAU dapat membantu untuk mengevaluasi beberapa hal berikut:
    • Ketertarikan pengguna untuk mengunjungi situs Anda
    • Kesuksesan marketing campaign
    • Revenue-growth rate

Acknowledgments

We are very grateful for suggestion and encouragement from mentor

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Analyzing business performance using PostgreSQL based on several business metrics : Customer Growth, Product Quality, & Payment Types

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