---
title: Tutorial: Analyze eCommerce data with aggregations using Query DSL
description: This hands-on tutorial shows you how to analyze eCommerce data using Elasticsearch aggregations with the _search API and Query DSL. You’ll learn how to:...
url: https://www.elastic.co/docs/explore-analyze/query-filter/aggregations/tutorial-analyze-ecommerce-data-with-aggregations-using-query-dsl
products:
  - Elastic Documentation
  - Elasticsearch
applies_to:
  - Elastic Cloud Serverless: Generally available
  - Elastic Stack: Generally available
---

# Tutorial: Analyze eCommerce data with aggregations using Query DSL
This hands-on tutorial shows you how to analyze eCommerce data using Elasticsearch [aggregations](https://www.elastic.co/docs/explore-analyze/query-filter/aggregations) with the `_search` API and Query DSL.
You’ll learn how to:
- Calculate key business metrics such as average order value
- Analyze sales patterns over time
- Compare performance across product categories
- Track moving averages and cumulative totals


## Requirements

You’ll need:
1. A running instance of [Elasticsearch](https://www.elastic.co/docs/get-started/deployment-options), either on Elastic Cloud Serverless or together with Kibana on Elastic Cloud Hosted/Self Managed deployments.
   - If you don’t have a deployment, you can run the following command in your terminal to set up a [local dev environment](https://www.elastic.co/docs/solutions/search/get-started):
     ```sh
     curl -fsSL https://elastic.co/start-local | sh
     ```
2. The [sample eCommerce data](/docs/explore-analyze#gs-get-data-into-kibana) loaded into Elasticsearch. To load sample data follow these steps in your UI:
   - Open the **Integrations** pages by searching in the global search field.
   - Search for `sample data` in the **Integrations** search field.
   - Open the **Sample data** page.
   - <applies-to>Elastic Stack: Generally available from 9.0 to 9.3</applies-to> Select the **Other sample data sets** collapsible.
   - Add the **Sample eCommerce orders** data set. This will create and populate an index called `kibana_sample_data_ecommerce`.


## Inspect index structure

Before we start analyzing the data, let’s examine the structure of the documents in our sample eCommerce index. Run this command to see the field [mappings](/docs/manage-data/data-store/index-basics#elasticsearch-intro-documents-fields-mappings):
```json
```

The response shows the field mappings for the `kibana_sample_data_ecommerce` index.
<dropdown title="Example response">
  ```json
  {
    "kibana_sample_data_ecommerce": {
      "mappings": {
        "properties": {
          "category": {
            "type": "text",
            "fields": { 
              "keyword": {
                "type": "keyword"
              }
            }
          },
          "currency": {
            "type": "keyword"
          },
          "customer_birth_date": {
            "type": "date"
          },
          "customer_first_name": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword",
                "ignore_above": 256
              }
            }
          },
          "customer_full_name": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword",
                "ignore_above": 256
              }
            }
          },
          "customer_gender": {
            "type": "keyword"
          },
          "customer_id": {
            "type": "keyword"
          },
          "customer_last_name": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword",
                "ignore_above": 256
              }
            }
          },
          "customer_phone": {
            "type": "keyword"
          },
          "day_of_week": {
            "type": "keyword"
          },
          "day_of_week_i": {
            "type": "integer"
          },
          "email": {
            "type": "keyword"
          },
          "event": {
            "properties": {
              "dataset": {
                "type": "keyword"
              }
            }
          },
          "geoip": {
            "properties": { 
              "city_name": {
                "type": "keyword"
              },
              "continent_name": {
                "type": "keyword"
              },
              "country_iso_code": {
                "type": "keyword"
              },
              "location": {
                "type": "geo_point" 
              },
              "region_name": {
                "type": "keyword"
              }
            }
          },
          "manufacturer": {
            "type": "text",
            "fields": {
              "keyword": {
                "type": "keyword"
              }
            }
          },
          "order_date": {
            "type": "date"
          },
          "order_id": {
            "type": "keyword"
          },
          "products": {
            "properties": { 
              "_id": {
                "type": "text",
                "fields": {
                  "keyword": {
                    "type": "keyword",
                    "ignore_above": 256
                  }
                }
              },
              "base_price": {
                "type": "half_float"
              },
              "base_unit_price": {
                "type": "half_float"
              },
              "category": {
                "type": "text",
                "fields": {
                  "keyword": {
                    "type": "keyword"
                  }
                }
              },
              "created_on": {
                "type": "date"
              },
              "discount_amount": {
                "type": "half_float"
              },
              "discount_percentage": {
                "type": "half_float"
              },
              "manufacturer": {
                "type": "text",
                "fields": {
                  "keyword": {
                    "type": "keyword"
                  }
                }
              },
              "min_price": {
                "type": "half_float"
              },
              "price": {
                "type": "half_float"
              },
              "product_id": {
                "type": "long"
              },
              "product_name": {
                "type": "text",
                "fields": {
                  "keyword": {
                    "type": "keyword"
                  }
                },
                "analyzer": "english"
              },
              "quantity": {
                "type": "integer"
              },
              "sku": {
                "type": "keyword"
              },
              "tax_amount": {
                "type": "half_float"
              },
              "taxful_price": {
                "type": "half_float"
              },
              "taxless_price": {
                "type": "half_float"
              },
              "unit_discount_amount": {
                "type": "half_float"
              }
            }
          },
          "sku": {
            "type": "keyword"
          },
          "taxful_total_price": {
            "type": "half_float"
          },
          "taxless_total_price": {
            "type": "half_float"
          },
          "total_quantity": {
            "type": "integer"
          },
          "total_unique_products": {
            "type": "integer"
          },
          "type": {
            "type": "keyword"
          },
          "user": {
            "type": "keyword"
          }
        }
      }
    }
  }
  ```
</dropdown>

The sample data includes the following [field data types](https://docs-demo.elastic.dev/docs/reference/elasticsearch/mapping-reference/field-data-types):
- [`text`](https://docs-demo.elastic.dev/docs/reference/elasticsearch/mapping-reference/text) and [`keyword`](https://docs-demo.elastic.dev/docs/reference/elasticsearch/mapping-reference/keyword) for text fields
  - Most `text` fields have a `.keyword` subfield for exact matching using [multi-fields](https://docs-demo.elastic.dev/docs/reference/elasticsearch/mapping-reference/multi-fields)
- [`date`](https://docs-demo.elastic.dev/docs/reference/elasticsearch/mapping-reference/date) for date fields
- 3 [numeric](https://docs-demo.elastic.dev/docs/reference/elasticsearch/mapping-reference/number) types:
  - `integer` for whole numbers
  - `long` for large whole numbers
  - `half_float` for floating-point numbers
- [`geo_point`](https://docs-demo.elastic.dev/docs/reference/elasticsearch/mapping-reference/geo-point) for geographic coordinates
- [`object`](https://docs-demo.elastic.dev/docs/reference/elasticsearch/mapping-reference/object) for nested structures such as `products`, `geoip`, `event`

Now that we understand the structure of our sample data, let’s start analyzing it.

## Get key business metrics

Let’s start by calculating important metrics about orders and customers.

### Get average order size

Calculate the average order value across all orders in the dataset using the [`avg`](https://docs-demo.elastic.dev/docs/reference/aggregations/search-aggregations-metrics-avg-aggregation) aggregation.
```json

{
 "size": 0, <1>
 "aggs": {
   "avg_order_value": { <2>
     "avg": { <3>
       "field": "taxful_total_price"
     }
   }
 }
}
```

<dropdown title="Example response">
  ```json
  {
    "took": 0,
    "timed_out": false,
    "_shards": {
      "total": 1,
      "successful": 1,
      "skipped": 0,
      "failed": 0
    },
    "hits": {
      "total": {
        "value": 4675, 
        "relation": "eq"
      },
      "max_score": null,
      "hits": [] 
    },
    "aggregations": {
      "avg_order_value": { 
        "value": 75.05542864304813 
      }
    }
  }
  ```
</dropdown>


### Get multiple order statistics at once

Calculate multiple statistics about orders in one request using the [`stats`](https://docs-demo.elastic.dev/docs/reference/aggregations/search-aggregations-metrics-stats-aggregation) aggregation.
```json

{
 "size": 0,
 "aggs": {
   "order_stats": { <1>
     "stats": { <2>
       "field": "taxful_total_price"
     }
   }
 }
}
```

<dropdown title="Example response">
  ```json
  {
   "aggregations": {
     "order_stats": {
       "count": 4675, 
       "min": 6.98828125, 
       "max": 2250, 
       "avg": 75.05542864304813, 
       "sum": 350884.12890625 
     }
   }
  }
  ```
</dropdown>

<tip>
  The [stats aggregation](https://docs-demo.elastic.dev/docs/reference/aggregations/search-aggregations-metrics-stats-aggregation) is more efficient than running individual min, max, avg, and sum aggregations.
</tip>


## Analyze sales patterns

Let’s group orders in different ways to understand sales patterns.

### Break down sales by category

Group orders by category to see which product categories are most popular, using the [`terms`](https://docs-demo.elastic.dev/docs/reference/aggregations/search-aggregations-bucket-terms-aggregation) aggregation.
```json

{
 "size": 0,
 "aggs": {
   "sales_by_category": { <1>
     "terms": { <2>
       "field": "category.keyword", <3>
       "size": 5, <4>
       "order": { "_count": "desc" } <5>
     }
   }
 }
}
```

<dropdown title="Example response">
  ```json
  {
    "took": 4,
    "timed_out": false,
    "_shards": {
      "total": 5,
      "successful": 5,
      "skipped": 0,
      "failed": 0
    },
    "hits": {
      "total": {
        "value": 4675,
        "relation": "eq"
      },
      "max_score": null,
      "hits": []
    },
    "aggregations": {
      "sales_by_category": {
        "doc_count_error_upper_bound": 0, 
        "sum_other_doc_count": 572, 
        "buckets": [ 
          {
            "key": "Men's Clothing", 
            "doc_count": 2024 
          },
          {
            "key": "Women's Clothing",
            "doc_count": 1903
          },
          {
            "key": "Women's Shoes",
            "doc_count": 1136
          },
          {
            "key": "Men's Shoes",
            "doc_count": 944
          },
          {
            "key": "Women's Accessories",
            "doc_count": 830
          }
        ]
      }
    }
  }
  ```
</dropdown>


### Track daily sales patterns

Group orders by day to track daily sales patterns using the [`date_histogram`](https://docs-demo.elastic.dev/docs/reference/aggregations/search-aggregations-bucket-datehistogram-aggregation) aggregation.
```json

{
 "size": 0,
 "aggs": {
   "daily_orders": { <1>
     "date_histogram": { <2>
       "field": "order_date",
       "calendar_interval": "day", <3>
       "format": "yyyy-MM-dd", <4>
       "min_doc_count": 0 <5>
     }
   }
 }
}
```

<dropdown title="Example response">
  ```json
  {
    "took": 2,
    "timed_out": false,
    "_shards": {
      "total": 5,
      "successful": 5,
      "skipped": 0,
      "failed": 0
    },
    "hits": {
      "total": {
        "value": 4675,
        "relation": "eq"
      },
      "max_score": null,
      "hits": []
    },
    "aggregations": {
      "daily_orders": { 
        "buckets": [ 
          {
            "key_as_string": "2024-11-28", 
            "key": 1732752000000, 
            "doc_count": 146 
          },
          {
            "key_as_string": "2024-11-29",
            "key": 1732838400000,
            "doc_count": 153
          },
          {
            "key_as_string": "2024-11-30",
            "key": 1732924800000,
            "doc_count": 143
          },
          {
            "key_as_string": "2024-12-01",
            "key": 1733011200000,
            "doc_count": 140
          },
          {
            "key_as_string": "2024-12-02",
            "key": 1733097600000,
            "doc_count": 139
          },
          {
            "key_as_string": "2024-12-03",
            "key": 1733184000000,
            "doc_count": 157
          },
          {
            "key_as_string": "2024-12-04",
            "key": 1733270400000,
            "doc_count": 145
          },
          {
            "key_as_string": "2024-12-05",
            "key": 1733356800000,
            "doc_count": 152
          },
          {
            "key_as_string": "2024-12-06",
            "key": 1733443200000,
            "doc_count": 163
          },
          {
            "key_as_string": "2024-12-07",
            "key": 1733529600000,
            "doc_count": 141
          },
          {
            "key_as_string": "2024-12-08",
            "key": 1733616000000,
            "doc_count": 151
          },
          {
            "key_as_string": "2024-12-09",
            "key": 1733702400000,
            "doc_count": 143
          },
          {
            "key_as_string": "2024-12-10",
            "key": 1733788800000,
            "doc_count": 143
          },
          {
            "key_as_string": "2024-12-11",
            "key": 1733875200000,
            "doc_count": 142
          },
          {
            "key_as_string": "2024-12-12",
            "key": 1733961600000,
            "doc_count": 161
          },
          {
            "key_as_string": "2024-12-13",
            "key": 1734048000000,
            "doc_count": 144
          },
          {
            "key_as_string": "2024-12-14",
            "key": 1734134400000,
            "doc_count": 157
          },
          {
            "key_as_string": "2024-12-15",
            "key": 1734220800000,
            "doc_count": 158
          },
          {
            "key_as_string": "2024-12-16",
            "key": 1734307200000,
            "doc_count": 144
          },
          {
            "key_as_string": "2024-12-17",
            "key": 1734393600000,
            "doc_count": 151
          },
          {
            "key_as_string": "2024-12-18",
            "key": 1734480000000,
            "doc_count": 145
          },
          {
            "key_as_string": "2024-12-19",
            "key": 1734566400000,
            "doc_count": 157
          },
          {
            "key_as_string": "2024-12-20",
            "key": 1734652800000,
            "doc_count": 158
          },
          {
            "key_as_string": "2024-12-21",
            "key": 1734739200000,
            "doc_count": 153
          },
          {
            "key_as_string": "2024-12-22",
            "key": 1734825600000,
            "doc_count": 165
          },
          {
            "key_as_string": "2024-12-23",
            "key": 1734912000000,
            "doc_count": 153
          },
          {
            "key_as_string": "2024-12-24",
            "key": 1734998400000,
            "doc_count": 158
          },
          {
            "key_as_string": "2024-12-25",
            "key": 1735084800000,
            "doc_count": 160
          },
          {
            "key_as_string": "2024-12-26",
            "key": 1735171200000,
            "doc_count": 159
          },
          {
            "key_as_string": "2024-12-27",
            "key": 1735257600000,
            "doc_count": 152
          },
          {
            "key_as_string": "2024-12-28",
            "key": 1735344000000,
            "doc_count": 142
          }
        ]
      }
    }
  }
  ```
</dropdown>


## Combine metrics with groupings

Now let’s calculate [metrics](https://docs-demo.elastic.dev/docs/reference/aggregations/metrics) within each group to get deeper insights.

### Compare category performance

Calculate metrics within each category to compare performance across categories.
```json

{
 "size": 0,
 "aggs": {
   "categories": {
     "terms": {
       "field": "category.keyword",
       "size": 5,
       "order": { "total_revenue": "desc" } <1>
     },
     "aggs": { <2>
       "total_revenue": { <3>
         "sum": {
           "field": "taxful_total_price"
         }
       },
       "avg_order_value": { <4>
         "avg": {
           "field": "taxful_total_price"
         }
       },
       "total_items": { <5>
         "sum": {
           "field": "total_quantity"
         }
       }
     }
   }
 }
}
```

<dropdown title="Example response">
  ```json
  {
   "aggregations": {
     "categories": {
       "buckets": [
         {
           "key": "Men's Clothing", 
           "doc_count": 2179, 
           "total_revenue": { 
             "value": 156729.453125
           },
           "avg_order_value": { 
             "value": 71.92726898715927
           },
           "total_items": { 
             "value": 8716
           }
         },
         {
           "key": "Women's Clothing",
           "doc_count": 2262,
           ...
         }
       ]
     }
   }
  }
  ```
</dropdown>


### Analyze daily sales performance

Let’s combine metrics to track daily trends: daily revenue, unique customers, and average basket size.
```json

{
 "size": 0,
 "aggs": {
   "daily_sales": {
     "date_histogram": {
       "field": "order_date",
       "calendar_interval": "day",
       "format": "yyyy-MM-dd"
     },
     "aggs": {
       "revenue": { <1>
         "sum": {
           "field": "taxful_total_price"
         }
       },
       "unique_customers": { <2>
         "cardinality": {
           "field": "customer_id"
         }
       },
       "avg_basket_size": { <3>
         "avg": {
           "field": "total_quantity"
         }
       }
     }
   }
 }
}
```

<dropdown title="Example response">
  ```json
  {
    "took": 119,
    "timed_out": false,
    "_shards": {
      "total": 5,
      "successful": 5,
      "skipped": 0,
      "failed": 0
    },
    "hits": {
      "total": {
        "value": 4675,
        "relation": "eq"
      },
      "max_score": null,
      "hits": []
    },
    "aggregations": {
      "daily_sales": {
        "buckets": [
          {
            "key_as_string": "2024-11-14",
            "key": 1731542400000,
            "doc_count": 146,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 10578.53125
            },
            "avg_basket_size": {
              "value": 2.1780821917808217
            }
          },
          {
            "key_as_string": "2024-11-15",
            "key": 1731628800000,
            "doc_count": 153,
            "unique_customers": {
              "value": 44
            },
            "revenue": {
              "value": 10448
            },
            "avg_basket_size": {
              "value": 2.183006535947712
            }
          },
          {
            "key_as_string": "2024-11-16",
            "key": 1731715200000,
            "doc_count": 143,
            "unique_customers": {
              "value": 45
            },
            "revenue": {
              "value": 10283.484375
            },
            "avg_basket_size": {
              "value": 2.111888111888112
            }
          },
          {
            "key_as_string": "2024-11-17",
            "key": 1731801600000,
            "doc_count": 140,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 10145.5234375
            },
            "avg_basket_size": {
              "value": 2.142857142857143
            }
          },
          {
            "key_as_string": "2024-11-18",
            "key": 1731888000000,
            "doc_count": 139,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 12012.609375
            },
            "avg_basket_size": {
              "value": 2.158273381294964
            }
          },
          {
            "key_as_string": "2024-11-19",
            "key": 1731974400000,
            "doc_count": 157,
            "unique_customers": {
              "value": 43
            },
            "revenue": {
              "value": 11009.45703125
            },
            "avg_basket_size": {
              "value": 2.0955414012738856
            }
          },
          {
            "key_as_string": "2024-11-20",
            "key": 1732060800000,
            "doc_count": 145,
            "unique_customers": {
              "value": 44
            },
            "revenue": {
              "value": 10720.59375
            },
            "avg_basket_size": {
              "value": 2.179310344827586
            }
          },
          {
            "key_as_string": "2024-11-21",
            "key": 1732147200000,
            "doc_count": 152,
            "unique_customers": {
              "value": 43
            },
            "revenue": {
              "value": 11185.3671875
            },
            "avg_basket_size": {
              "value": 2.1710526315789473
            }
          },
          {
            "key_as_string": "2024-11-22",
            "key": 1732233600000,
            "doc_count": 163,
            "unique_customers": {
              "value": 44
            },
            "revenue": {
              "value": 13560.140625
            },
            "avg_basket_size": {
              "value": 2.2576687116564416
            }
          },
          {
            "key_as_string": "2024-11-23",
            "key": 1732320000000,
            "doc_count": 141,
            "unique_customers": {
              "value": 45
            },
            "revenue": {
              "value": 9884.78125
            },
            "avg_basket_size": {
              "value": 2.099290780141844
            }
          },
          {
            "key_as_string": "2024-11-24",
            "key": 1732406400000,
            "doc_count": 151,
            "unique_customers": {
              "value": 44
            },
            "revenue": {
              "value": 11075.65625
            },
            "avg_basket_size": {
              "value": 2.0927152317880795
            }
          },
          {
            "key_as_string": "2024-11-25",
            "key": 1732492800000,
            "doc_count": 143,
            "unique_customers": {
              "value": 41
            },
            "revenue": {
              "value": 10323.8515625
            },
            "avg_basket_size": {
              "value": 2.167832167832168
            }
          },
          {
            "key_as_string": "2024-11-26",
            "key": 1732579200000,
            "doc_count": 143,
            "unique_customers": {
              "value": 44
            },
            "revenue": {
              "value": 10369.546875
            },
            "avg_basket_size": {
              "value": 2.167832167832168
            }
          },
          {
            "key_as_string": "2024-11-27",
            "key": 1732665600000,
            "doc_count": 142,
            "unique_customers": {
              "value": 46
            },
            "revenue": {
              "value": 11711.890625
            },
            "avg_basket_size": {
              "value": 2.1971830985915495
            }
          },
          {
            "key_as_string": "2024-11-28",
            "key": 1732752000000,
            "doc_count": 161,
            "unique_customers": {
              "value": 43
            },
            "revenue": {
              "value": 12612.6640625
            },
            "avg_basket_size": {
              "value": 2.1180124223602483
            }
          },
          {
            "key_as_string": "2024-11-29",
            "key": 1732838400000,
            "doc_count": 144,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 10176.87890625
            },
            "avg_basket_size": {
              "value": 2.0347222222222223
            }
          },
          {
            "key_as_string": "2024-11-30",
            "key": 1732924800000,
            "doc_count": 157,
            "unique_customers": {
              "value": 43
            },
            "revenue": {
              "value": 11480.33203125
            },
            "avg_basket_size": {
              "value": 2.159235668789809
            }
          },
          {
            "key_as_string": "2024-12-01",
            "key": 1733011200000,
            "doc_count": 158,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 11533.265625
            },
            "avg_basket_size": {
              "value": 2.0822784810126582
            }
          },
          {
            "key_as_string": "2024-12-02",
            "key": 1733097600000,
            "doc_count": 144,
            "unique_customers": {
              "value": 43
            },
            "revenue": {
              "value": 10499.8125
            },
            "avg_basket_size": {
              "value": 2.201388888888889
            }
          },
          {
            "key_as_string": "2024-12-03",
            "key": 1733184000000,
            "doc_count": 151,
            "unique_customers": {
              "value": 40
            },
            "revenue": {
              "value": 12111.6875
            },
            "avg_basket_size": {
              "value": 2.172185430463576
            }
          },
          {
            "key_as_string": "2024-12-04",
            "key": 1733270400000,
            "doc_count": 145,
            "unique_customers": {
              "value": 40
            },
            "revenue": {
              "value": 10530.765625
            },
            "avg_basket_size": {
              "value": 2.0965517241379312
            }
          },
          {
            "key_as_string": "2024-12-05",
            "key": 1733356800000,
            "doc_count": 157,
            "unique_customers": {
              "value": 43
            },
            "revenue": {
              "value": 11872.5625
            },
            "avg_basket_size": {
              "value": 2.1464968152866244
            }
          },
          {
            "key_as_string": "2024-12-06",
            "key": 1733443200000,
            "doc_count": 158,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 12109.453125
            },
            "avg_basket_size": {
              "value": 2.151898734177215
            }
          },
          {
            "key_as_string": "2024-12-07",
            "key": 1733529600000,
            "doc_count": 153,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 11057.40625
            },
            "avg_basket_size": {
              "value": 2.111111111111111
            }
          },
          {
            "key_as_string": "2024-12-08",
            "key": 1733616000000,
            "doc_count": 165,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 13095.609375
            },
            "avg_basket_size": {
              "value": 2.1818181818181817
            }
          },
          {
            "key_as_string": "2024-12-09",
            "key": 1733702400000,
            "doc_count": 153,
            "unique_customers": {
              "value": 41
            },
            "revenue": {
              "value": 12574.015625
            },
            "avg_basket_size": {
              "value": 2.2287581699346406
            }
          },
          {
            "key_as_string": "2024-12-10",
            "key": 1733788800000,
            "doc_count": 158,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 11188.1875
            },
            "avg_basket_size": {
              "value": 2.151898734177215
            }
          },
          {
            "key_as_string": "2024-12-11",
            "key": 1733875200000,
            "doc_count": 160,
            "unique_customers": {
              "value": 42
            },
            "revenue": {
              "value": 12117.65625
            },
            "avg_basket_size": {
              "value": 2.20625
            }
          },
          {
            "key_as_string": "2024-12-12",
            "key": 1733961600000,
            "doc_count": 159,
            "unique_customers": {
              "value": 45
            },
            "revenue": {
              "value": 11558.25
            },
            "avg_basket_size": {
              "value": 2.1823899371069184
            }
          },
          {
            "key_as_string": "2024-12-13",
            "key": 1734048000000,
            "doc_count": 152,
            "unique_customers": {
              "value": 45
            },
            "revenue": {
              "value": 11921.1171875
            },
            "avg_basket_size": {
              "value": 2.289473684210526
            }
          },
          {
            "key_as_string": "2024-12-14",
            "key": 1734134400000,
            "doc_count": 142,
            "unique_customers": {
              "value": 45
            },
            "revenue": {
              "value": 11135.03125
            },
            "avg_basket_size": {
              "value": 2.183098591549296
            }
          }
        ]
      }
    }
  }
  ```
</dropdown>


## Track trends and patterns

You can use [pipeline aggregations](https://docs-demo.elastic.dev/docs/reference/aggregations/pipeline) on the results of other aggregations. Let’s analyze how metrics change over time.

### Smooth out daily fluctuations

Moving averages help identify trends by reducing day-to-day noise in the data. Let’s observe sales trends more clearly by smoothing daily revenue variations, using the [Moving Function](https://docs-demo.elastic.dev/docs/reference/aggregations/search-aggregations-pipeline-movfn-aggregation) aggregation.
```json

{
  "size": 0,
  "aggs": {
    "daily_sales": {
      "date_histogram": {
        "field": "order_date",
        "calendar_interval": "day"
      },
      "aggs": {
        "daily_revenue": {  <1>
          "sum": {
            "field": "taxful_total_price"
          }
        },
        "smoothed_revenue": { <2>
          "moving_fn": { <3>
            "buckets_path": "daily_revenue", <4>
            "window": 3, <5>
            "script": "MovingFunctions.unweightedAvg(values)" <6>
          }
        }
      }
    }
  }
}
```

<dropdown title="Example response">
  ```json
  {
    "took": 13,
    "timed_out": false,
    "_shards": {
      "total": 5,
      "successful": 5,
      "skipped": 0,
      "failed": 0
    },
    "hits": {
      "total": {
        "value": 4675,
        "relation": "eq"
      },
      "max_score": null,
      "hits": []
    },
    "aggregations": {
      "daily_sales": {
        "buckets": [
          {
            "key_as_string": "2024-11-14T00:00:00.000Z",  
            "key": 1731542400000,
            "doc_count": 146, 
            "daily_revenue": { 
              "value": 10578.53125
            },
            "smoothed_revenue": { 
              "value": null
            }
          },
          {
            "key_as_string": "2024-11-15T00:00:00.000Z",
            "key": 1731628800000,
            "doc_count": 153,
            "daily_revenue": {
              "value": 10448
            },
            "smoothed_revenue": { 
              "value": 10578.53125
            }
          },
          {
            "key_as_string": "2024-11-16T00:00:00.000Z",
            "key": 1731715200000,
            "doc_count": 143,
            "daily_revenue": {
              "value": 10283.484375
            },
            "smoothed_revenue": {
              "value": 10513.265625
            }
          },
          {
            "key_as_string": "2024-11-17T00:00:00.000Z",
            "key": 1731801600000,
            "doc_count": 140,
            "daily_revenue": {
              "value": 10145.5234375
            },
            "smoothed_revenue": {
              "value": 10436.671875
            }
          },
          {
            "key_as_string": "2024-11-18T00:00:00.000Z",
            "key": 1731888000000,
            "doc_count": 139,
            "daily_revenue": {
              "value": 12012.609375
            },
            "smoothed_revenue": {
              "value": 10292.3359375
            }
          },
          {
            "key_as_string": "2024-11-19T00:00:00.000Z",
            "key": 1731974400000,
            "doc_count": 157,
            "daily_revenue": {
              "value": 11009.45703125
            },
            "smoothed_revenue": {
              "value": 10813.872395833334
            }
          },
          {
            "key_as_string": "2024-11-20T00:00:00.000Z",
            "key": 1732060800000,
            "doc_count": 145,
            "daily_revenue": {
              "value": 10720.59375
            },
            "smoothed_revenue": {
              "value": 11055.86328125
            }
          },
          {
            "key_as_string": "2024-11-21T00:00:00.000Z",
            "key": 1732147200000,
            "doc_count": 152,
            "daily_revenue": {
              "value": 11185.3671875
            },
            "smoothed_revenue": {
              "value": 11247.553385416666
            }
          },
          {
            "key_as_string": "2024-11-22T00:00:00.000Z",
            "key": 1732233600000,
            "doc_count": 163,
            "daily_revenue": {
              "value": 13560.140625
            },
            "smoothed_revenue": {
              "value": 10971.805989583334
            }
          },
          {
            "key_as_string": "2024-11-23T00:00:00.000Z",
            "key": 1732320000000,
            "doc_count": 141,
            "daily_revenue": {
              "value": 9884.78125
            },
            "smoothed_revenue": {
              "value": 11822.033854166666
            }
          },
          {
            "key_as_string": "2024-11-24T00:00:00.000Z",
            "key": 1732406400000,
            "doc_count": 151,
            "daily_revenue": {
              "value": 11075.65625
            },
            "smoothed_revenue": {
              "value": 11543.4296875
            }
          },
          {
            "key_as_string": "2024-11-25T00:00:00.000Z",
            "key": 1732492800000,
            "doc_count": 143,
            "daily_revenue": {
              "value": 10323.8515625
            },
            "smoothed_revenue": {
              "value": 11506.859375
            }
          },
          {
            "key_as_string": "2024-11-26T00:00:00.000Z",
            "key": 1732579200000,
            "doc_count": 143,
            "daily_revenue": {
              "value": 10369.546875
            },
            "smoothed_revenue": {
              "value": 10428.096354166666
            }
          },
          {
            "key_as_string": "2024-11-27T00:00:00.000Z",
            "key": 1732665600000,
            "doc_count": 142,
            "daily_revenue": {
              "value": 11711.890625
            },
            "smoothed_revenue": {
              "value": 10589.684895833334
            }
          },
          {
            "key_as_string": "2024-11-28T00:00:00.000Z",
            "key": 1732752000000,
            "doc_count": 161,
            "daily_revenue": {
              "value": 12612.6640625
            },
            "smoothed_revenue": {
              "value": 10801.763020833334
            }
          },
          {
            "key_as_string": "2024-11-29T00:00:00.000Z",
            "key": 1732838400000,
            "doc_count": 144,
            "daily_revenue": {
              "value": 10176.87890625
            },
            "smoothed_revenue": {
              "value": 11564.700520833334
            }
          },
          {
            "key_as_string": "2024-11-30T00:00:00.000Z",
            "key": 1732924800000,
            "doc_count": 157,
            "daily_revenue": {
              "value": 11480.33203125
            },
            "smoothed_revenue": {
              "value": 11500.477864583334
            }
          },
          {
            "key_as_string": "2024-12-01T00:00:00.000Z",
            "key": 1733011200000,
            "doc_count": 158,
            "daily_revenue": {
              "value": 11533.265625
            },
            "smoothed_revenue": {
              "value": 11423.291666666666
            }
          },
          {
            "key_as_string": "2024-12-02T00:00:00.000Z",
            "key": 1733097600000,
            "doc_count": 144,
            "daily_revenue": {
              "value": 10499.8125
            },
            "smoothed_revenue": {
              "value": 11063.4921875
            }
          },
          {
            "key_as_string": "2024-12-03T00:00:00.000Z",
            "key": 1733184000000,
            "doc_count": 151,
            "daily_revenue": {
              "value": 12111.6875
            },
            "smoothed_revenue": {
              "value": 11171.13671875
            }
          },
          {
            "key_as_string": "2024-12-04T00:00:00.000Z",
            "key": 1733270400000,
            "doc_count": 145,
            "daily_revenue": {
              "value": 10530.765625
            },
            "smoothed_revenue": {
              "value": 11381.588541666666
            }
          },
          {
            "key_as_string": "2024-12-05T00:00:00.000Z",
            "key": 1733356800000,
            "doc_count": 157,
            "daily_revenue": {
              "value": 11872.5625
            },
            "smoothed_revenue": {
              "value": 11047.421875
            }
          },
          {
            "key_as_string": "2024-12-06T00:00:00.000Z",
            "key": 1733443200000,
            "doc_count": 158,
            "daily_revenue": {
              "value": 12109.453125
            },
            "smoothed_revenue": {
              "value": 11505.005208333334
            }
          },
          {
            "key_as_string": "2024-12-07T00:00:00.000Z",
            "key": 1733529600000,
            "doc_count": 153,
            "daily_revenue": {
              "value": 11057.40625
            },
            "smoothed_revenue": {
              "value": 11504.260416666666
            }
          },
          {
            "key_as_string": "2024-12-08T00:00:00.000Z",
            "key": 1733616000000,
            "doc_count": 165,
            "daily_revenue": {
              "value": 13095.609375
            },
            "smoothed_revenue": {
              "value": 11679.807291666666
            }
          },
          {
            "key_as_string": "2024-12-09T00:00:00.000Z",
            "key": 1733702400000,
            "doc_count": 153,
            "daily_revenue": {
              "value": 12574.015625
            },
            "smoothed_revenue": {
              "value": 12087.489583333334
            }
          },
          {
            "key_as_string": "2024-12-10T00:00:00.000Z",
            "key": 1733788800000,
            "doc_count": 158,
            "daily_revenue": {
              "value": 11188.1875
            },
            "smoothed_revenue": {
              "value": 12242.34375
            }
          },
          {
            "key_as_string": "2024-12-11T00:00:00.000Z",
            "key": 1733875200000,
            "doc_count": 160,
            "daily_revenue": {
              "value": 12117.65625
            },
            "smoothed_revenue": {
              "value": 12285.9375
            }
          },
          {
            "key_as_string": "2024-12-12T00:00:00.000Z",
            "key": 1733961600000,
            "doc_count": 159,
            "daily_revenue": {
              "value": 11558.25
            },
            "smoothed_revenue": {
              "value": 11959.953125
            }
          },
          {
            "key_as_string": "2024-12-13T00:00:00.000Z",
            "key": 1734048000000,
            "doc_count": 152,
            "daily_revenue": {
              "value": 11921.1171875
            },
            "smoothed_revenue": {
              "value": 11621.364583333334
            }
          },
          {
            "key_as_string": "2024-12-14T00:00:00.000Z",
            "key": 1734134400000,
            "doc_count": 142,
            "daily_revenue": {
              "value": 11135.03125
            },
            "smoothed_revenue": {
              "value": 11865.674479166666
            }
          }
        ]
      }
    }
  }
  ```
</dropdown>

<tip>
  Notice how the smoothed values lag behind the actual values - this is because they need previous days' data to calculate. The first day will always be null when using moving averages.
</tip>


### Track running totals

Track running totals over time using the [`cumulative_sum`](https://docs-demo.elastic.dev/docs/reference/aggregations/search-aggregations-pipeline-cumulative-sum-aggregation) aggregation.
```json

{
 "size": 0,
 "aggs": {
   "daily_sales": {
     "date_histogram": {
       "field": "order_date",
       "calendar_interval": "day"
     },
     "aggs": {
       "revenue": {
         "sum": {
           "field": "taxful_total_price"
         }
       },
       "cumulative_revenue": { <1>
         "cumulative_sum": { <2>
           "buckets_path": "revenue" <3>
         }
       }
     }
   }
 }
}
```

<dropdown title="Example response">
  ```json
  {
    "took": 4,
    "timed_out": false,
    "_shards": {
      "total": 5,
      "successful": 5,
      "skipped": 0,
      "failed": 0
    },
    "hits": {
      "total": {
        "value": 4675,
        "relation": "eq"
      },
      "max_score": null,
      "hits": []
    },
    "aggregations": {
      "daily_sales": { 
        "buckets": [ 
          {
            "key_as_string": "2024-11-14T00:00:00.000Z", 
            "key": 1731542400000,
            "doc_count": 146,
            "revenue": { 
              "value": 10578.53125
            },
            "cumulative_revenue": { 
              "value": 10578.53125
            }
          },
          {
            "key_as_string": "2024-11-15T00:00:00.000Z",
            "key": 1731628800000,
            "doc_count": 153,
            "revenue": {
              "value": 10448
            },
            "cumulative_revenue": {
              "value": 21026.53125
            }
          },
          {
            "key_as_string": "2024-11-16T00:00:00.000Z",
            "key": 1731715200000,
            "doc_count": 143,
            "revenue": {
              "value": 10283.484375
            },
            "cumulative_revenue": {
              "value": 31310.015625
            }
          },
          {
            "key_as_string": "2024-11-17T00:00:00.000Z",
            "key": 1731801600000,
            "doc_count": 140,
            "revenue": {
              "value": 10145.5234375
            },
            "cumulative_revenue": {
              "value": 41455.5390625
            }
          },
          {
            "key_as_string": "2024-11-18T00:00:00.000Z",
            "key": 1731888000000,
            "doc_count": 139,
            "revenue": {
              "value": 12012.609375
            },
            "cumulative_revenue": {
              "value": 53468.1484375
            }
          },
          {
            "key_as_string": "2024-11-19T00:00:00.000Z",
            "key": 1731974400000,
            "doc_count": 157,
            "revenue": {
              "value": 11009.45703125
            },
            "cumulative_revenue": {
              "value": 64477.60546875
            }
          },
          {
            "key_as_string": "2024-11-20T00:00:00.000Z",
            "key": 1732060800000,
            "doc_count": 145,
            "revenue": {
              "value": 10720.59375
            },
            "cumulative_revenue": {
              "value": 75198.19921875
            }
          },
          {
            "key_as_string": "2024-11-21T00:00:00.000Z",
            "key": 1732147200000,
            "doc_count": 152,
            "revenue": {
              "value": 11185.3671875
            },
            "cumulative_revenue": {
              "value": 86383.56640625
            }
          },
          {
            "key_as_string": "2024-11-22T00:00:00.000Z",
            "key": 1732233600000,
            "doc_count": 163,
            "revenue": {
              "value": 13560.140625
            },
            "cumulative_revenue": {
              "value": 99943.70703125
            }
          },
          {
            "key_as_string": "2024-11-23T00:00:00.000Z",
            "key": 1732320000000,
            "doc_count": 141,
            "revenue": {
              "value": 9884.78125
            },
            "cumulative_revenue": {
              "value": 109828.48828125
            }
          },
          {
            "key_as_string": "2024-11-24T00:00:00.000Z",
            "key": 1732406400000,
            "doc_count": 151,
            "revenue": {
              "value": 11075.65625
            },
            "cumulative_revenue": {
              "value": 120904.14453125
            }
          },
          {
            "key_as_string": "2024-11-25T00:00:00.000Z",
            "key": 1732492800000,
            "doc_count": 143,
            "revenue": {
              "value": 10323.8515625
            },
            "cumulative_revenue": {
              "value": 131227.99609375
            }
          },
          {
            "key_as_string": "2024-11-26T00:00:00.000Z",
            "key": 1732579200000,
            "doc_count": 143,
            "revenue": {
              "value": 10369.546875
            },
            "cumulative_revenue": {
              "value": 141597.54296875
            }
          },
          {
            "key_as_string": "2024-11-27T00:00:00.000Z",
            "key": 1732665600000,
            "doc_count": 142,
            "revenue": {
              "value": 11711.890625
            },
            "cumulative_revenue": {
              "value": 153309.43359375
            }
          },
          {
            "key_as_string": "2024-11-28T00:00:00.000Z",
            "key": 1732752000000,
            "doc_count": 161,
            "revenue": {
              "value": 12612.6640625
            },
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          {
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          {
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            "key_as_string": "2024-12-07T00:00:00.000Z",
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          {
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          },
          {
            "key_as_string": "2024-12-09T00:00:00.000Z",
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              "value": 12574.015625
            },
            "cumulative_revenue": {
              "value": 292963.88671875
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          },
          {
            "key_as_string": "2024-12-10T00:00:00.000Z",
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              "value": 11188.1875
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              "value": 304152.07421875
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          {
            "key_as_string": "2024-12-11T00:00:00.000Z",
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              "value": 12117.65625
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            "cumulative_revenue": {
              "value": 316269.73046875
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          {
            "key_as_string": "2024-12-12T00:00:00.000Z",
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              "value": 11558.25
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              "value": 327827.98046875
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          },
          {
            "key_as_string": "2024-12-13T00:00:00.000Z",
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              "value": 11921.1171875
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              "value": 339749.09765625
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          },
          {
            "key_as_string": "2024-12-14T00:00:00.000Z",
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              "value": 11135.03125
            },
            "cumulative_revenue": {
              "value": 350884.12890625
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          }
        ]
      }
    }
  }
  ```
</dropdown>


## Next steps

Refer to the [aggregations reference](https://www.elastic.co/docs/explore-analyze/query-filter/aggregations) for more details on all available aggregation types.