**SKU:**

`DPK-LOCADD-POP`

Field Name | Definition | Type | Example |

geometry_id 🔑 | Unique identifier of a geometry (which is a standard subset of location). Use it to recognise the specific geometry or as a foreign key to link different files and/or packages together. | STRING | `1202213221112` |

geometry 🔑 | Spatial information in `.WKT ` format, outlining the defined polygon through specific longitude and latitude coordinates. | STRING | `POLYGON ((9.052734375 45.52174389699363, 9.0966796875 45.52174389699363, 9.0966796875 45.55252525134013, 9.052734375 45.55252525134013, 9.052734375 45.52174389699363))` |

date 🔑 | The analysis date on which the KPI is calculated.This date is based on the chosen aggregation period, which is determined on the selected sample rate that slices the total timeframe, and is expressed in YYYY-MM-DD format. The sample rate can assume 3 values: MONTHLY: monthly time series, starting on the first day of each month (e.g. 2023-01-01, 2023-02-01, 2023-03-01...)QUARTERLY: quarterly time series, starting on the first day of each quarter (e.g. 2023-01-01, 2023-04-01, 2023-07-01...) YEARLY: yearly time series (e.g. 2023, 2022, 2021). | DATE | `2023-01-01` |

popularity | Proprietary percentage KPI (uncapped range) that measures the popularity of a geometry over time.The score is calculated over a period of time based on the sample rate affecting the total timeframe that has been chosen. For example: for a timeframe equal to one year and with a monthly sample rate, the KPI will be calculated through the analysis of multiple factors such as the number of geo-localised reviews and social media content contained in the calculation month. In this way, an objective trend is obtained on the time series variation of the KPI.
More info about the Popularity Index here. | DOUBLE | `30.12` |

## Popularity Scale Explanation

Value | Interpretation |

0 | Not enough data to provide an estimate |

.01 - 10 | Very poor attendance |

10 - 20 | Poor attendance |

21 - 40 | Light attendance, mostly concentrated in certain time slots |

41 - 60 | Average attendance, distribution with significant peaks |

61 - 80 | Good attendance, even distribution |

81 - 100 | Strong attendance |

101 -120 | Very strong attendance |

> 120 | Extraordinarily high attendance |