# New vs Returning Customers ## Model Scenario In this report, we want to divide customers into returning and new customers (this is the most fundamental type of [customer segmentation](https://graphite-note.com/machine-learning-for-customer-segmentation)). The new customers have made only one purchase from your business, while the returning ones have made more than one.

Let’s go through their basic characteristics. New customers are: * forming the foundation of your customer base * telling you if your marketing campaigns are working (improving current offerings, what to add to your repertoire of products or services) while returning customers are: * giving you feedback on your business (if you have a high number of returning customers it suggests that customers are finding value in your products or service) * saving you a lot of time, effort, and money. Let's go through the New vs returning customer analysis inside Graphite. The dataset on which you will run your model must contain a **time-related column**.

Since the dataset contains data for a certain period, it's important to choose the **aggregation level**.

For example, if weekly aggregation is selected, Graphite will generate a new vs returning customers dataset with a weekly frequency. It is necessary to contain data such as **Customer ID**

Additionally, if you want, you can choose the **Monetary (amount spent)** variable.

With Graphite, compare absolute figures and percentages, and learn how many customers you are currently retaining on a daily, weekly, or monthly basis. ## Model Results The model results consist of 4 tabs: [New vs Returning](#new-vs-returning), [Retention %](#retention), [Revenue New vs Returning](#revenue-new-vs-returning), and [Details ](#details)Tab. ### New vs Returning Depending on the aggregation level, you can see the number of distinct and returning customers detected in the period on the **New vs Returning Tab**.

Chart showing New and Returning customers in a period in a monthly representation

For example, in December 2020, there were a total of 2.88k customers, of which 1.84K were new and 1.05K returning. You can also choose a daily representation that is more precise.

Chart showing New and Returning customers in a period in a daily representation

### Retention % If you are interested in retention, the percentage of your returning customers, through a period, use the **Retention % Tab**.

Chart showing the percentage of returning customers in a period in a monthly representation

### Revenue New vs Returning The results in the **Revenue New vs Returning Tab** depend on the Model Scenario: if you have selected a monetary variable in the [Model Scenario](#model-scenario), you can observe her behavior, depending on the new and returning customers.

Chart showing the revenue spent depending if they are new customers or not in a period in a monthly representation

### Details Last but not least, on the **Details Tab**, you can find a detailed table where you can see all relevant values which were used for the above results.

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