# eCommerce Orders
1\. If you want to use Graphite Note demo datasets click "Import DEMO Dataset".
2\. Select the dataset you want to use to create machine learning model. In this case we will select eCommerce Orders dataset to create RFM Customer Segmentation (Recency, Frequency, Monetary Value) analysis on ecommerce orders data.
3\. Once selected, the demo dataset will load directly to your account. Dataset view will automatically open.
4\. Adjust your dataset options on Settings tab. Click Columns tab to view list of available columns with their corresponding data types. Explore the dataset details on Summary tab.
5\. To create new model in the Graphite Note main menu click on "Models"
6\. You will get list of available models. Click on "New Model" to create new one.
7\. Select a model type from our templates. In our case we will select "RFM Customer Segmentation" by double clicking on its name.
8\. Select dataset you want to use to produce model. We will use "Demo-eCommerce-Orders.csv".
9\. Name your new model. We will call it "RFM customer segmentation on Demo-eCommerce-Orders".
10\. Write description of the model and select tag. If you want you can also create new tag from pop-up "Tags" window that will appear on the screen.
11\. Click "Create" to create your demo model environment.
12\. Click this text field.
13\. To set up RFM model, you first need to identify and define few parameters. These are: "Time /Date Column", "Customer ID", "Customer Name" (optional) and "Monetary" (amount spent). In our case we will select "created\_at" as date, "user\_id" as customer and "total" as monetary parameter.
14\. To start training model click "Run scenario".
15\. Wait for a few moments and Voilà! Your RFM Customer Segmentation model is trained. Click on the "Results" tab to get model insights.
16\. You can navigate over different tabs to get deep insights into RFM analysis from different perspectives: Recency, Frequency, Monetary.
17\. Tab "RFM Scores" shows detailed explanation on different scores along with RFM segments and descriptions.
18\. Tab "RFM Analysis" gives you more details on different segments
19\. Tab "RFM Matrix" will show you number of customers belonging to different RFM segment. You can export matrix data to use Customer IDs for different business actions (e.g. exporting list of about to churn customers).
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3\. Once selected, the demo dataset will load directly to your account. Dataset view will automatically open.
4\. Adjust your dataset options on Settings tab. Click Columns tab to view list of available columns with their corresponding data types. Explore the dataset details on Summary tab.
5\. To create new model in the Graphite Note main menu click on "Models"
6\. You will get list of available models. Click on "New Model" to create new one.
7\. Select a model type from our templates. In our case we will select "RFM Customer Segmentation" by double clicking on its name.
8\. Select dataset you want to use to produce model. We will use "Demo-eCommerce-Orders.csv".
9\. Name your new model. We will call it "RFM customer segmentation on Demo-eCommerce-Orders".
10\. Write description of the model and select tag. If you want you can also create new tag from pop-up "Tags" window that will appear on the screen.
11\. Click "Create" to create your demo model environment.
12\. Click this text field.
13\. To set up RFM model, you first need to identify and define few parameters. These are: "Time /Date Column", "Customer ID", "Customer Name" (optional) and "Monetary" (amount spent). In our case we will select "created\_at" as date, "user\_id" as customer and "total" as monetary parameter.
14\. To start training model click "Run scenario".
15\. Wait for a few moments and Voilà! Your RFM Customer Segmentation model is trained. Click on the "Results" tab to get model insights.
16\. You can navigate over different tabs to get deep insights into RFM analysis from different perspectives: Recency, Frequency, Monetary.
17\. Tab "RFM Scores" shows detailed explanation on different scores along with RFM segments and descriptions.
18\. Tab "RFM Analysis" gives you more details on different segments
19\. Tab "RFM Matrix" will show you number of customers belonging to different RFM segment. You can export matrix data to use Customer IDs for different business actions (e.g. exporting list of about to churn customers).
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