<div> <p><img src="https://geekbrains.ru/apple-touch-icon-57x57.png" align="right" alt="GeekBrains" width=100></p> <p style="font-size:120%">Customer data analysis for e-commerce</p> <br> <br> <p style="font-size:60%"><b>Author:</b> Dmitry Doni</p> <p style="font-size:60%"><b>Mentor:</b> Artem Gogin</p> </div> --- ### About the project This project aims to provide customer analytics based on operational data of an e-commerce product in the financial industry. --- ### Business needs - **Marketing** team purchase digital ad traffic to attract new customers and partners, they need to understand which customers can bring most value to the company. - **Sales** team need to know which existing customers to contact with special offers and discounts. - **Engineering** team need to know which devices and platforms are most popular among the customers, so they can focus their development and testing efforts on these platforms. --- ### Solution - Descriptive analytics: - [x] Customer segmentation using RFM analysis - [x] Customer devices and platforms report - Predictive analytics: - [x] Prediction of customer LTV --- ### Data used in the project | Data | Used for | | -------------------- | ---------------------------------- | | Transactions history | RFM analysis, training ML model | | New transactions | LTV prediction with ML model | | Device data | Customer devices & platforms report| --- ### Data fields **Transaction record:** ```typescript | order_id | client_id | date | amount | product_id | partner_id | client_country | bank_name | ... ``` **Device data record:** ```typescript | order_id | osname | osversion | browsername | browsermajor | device_model | device_type ``` --- ### Solution Architecture [View diagram](https://viewer.diagrams.net/?highlight=0000ff&edit=_blank&layers=1&nav=1&title=big_data_project.drawio#Uhttps%3A%2F%2Fdrive.google.com%2Fuc%3Fid%3D12JJmgNIXWwR56OX74I4kaBzEjCpxWCLl%26export%3Ddownload) --- ### Architecture ![](https://i.imgur.com/t8Jq0U3.png) --- ### Next steps - Prepare source data (download, feature selection) - EDA - Data cleansing --- # :bulb: ### Ideas for improvement TBD --- ### References - GitHub project: - Technical specification: - BI dashboards: --- <code class="blue">/* code sample */</code> ---
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