Please be aware that on certain occasions, a Point of Interest (POI) may be represented solely by our Core Attributes. This indicates a scenario where the available data does not suffice to generate enriched insights, including Rich Attributes, Trends, or additional Add-ons. For example, a bus stop, due to its nature, might lack extensive online content, resulting in only Core Attributes being ascertainable. This distinction highlights our platform's adaptability in providing essential information, while continuously striving to enrich the POI's data profile as more information becomes available.
Core Attributes
SKU:
DPK-LOC-COREField Name | Defintion | 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. | NUMBER | 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)) |
poi_density_index | Proprietary Index that serves as a quantitative representation of the geometry's density, which is directly influenced by the concentration of POIs within the designated area.
This represents an uncapped KPI, which has been developed based on robust statistical analysis of the distribution of POIs across a uniformly referenced area.
More information on how to read the values here. | DOUBLE | 81.58 |
review_coverage_index | Proprietary Index that functions as a representative metric for assessing the review coverage of a particular geometry. This review coverage is contingent upon the cumulative count of reviews associated with each POI situated within the specified confines.
This represents an uncapped KPI, which has been developed based on robust statistical analysis of the distribution of POIs across a uniformly referenced area.
More information on how to read the values here. | DOUBLE | 30.11 |
industry_distribution | The percentage distribution of Points of Interest (POI) by industry provides a proportional breakdown of POIs across various sectors, tailored to the selected industries and/or categories.
This distribution offers insight into the prevalence of different business types or services within a specific area, reflecting the economic and commercial landscape.
→ find the full list here. | STRING (JSON) | [{"industry": "Transportation","percentage": 51.68},{"industry": "Food & Beverage","percentage": 24.58},{"industry": "Attractions","percentage": 17.08},{"industry": "Entertainment","percentage": 2.50},{"industry": "Hospitality","percentage": 2.08},{"industry": "Short Term Rentals","percentage": 2.08}] |
most_popular_categories | The percentage distribution of Points of Interest (POI) showcases the spread of POIs across the top five categories, taking into account the chosen industries and/or categories.
It’s important to note that the percentage values of all other categories not included in the top five are collectively categorised and presented as the Other category.
This approach provides a clear and concise view of the dominant categories in a specific area, while also acknowledging the presence of additional categories.
→ find the full list here. | STRING (JSON) | [{"category": "Bus stop","percentage": 32.09},{"category": "Parking lot","percentage": 11.25},{"category": "Restaurant","percentage": 7.50},{"category": "Church","percentage": 5.00},{"category": "Park","percentage": 4.58},{"category": "Other","percentage": 39.58}] |
most_popular_poi | The list encapsulates the five most frequented Points of Interest (POI), considering the specified industries and/or categories. Each entry includes:
Rank: The position of the POI in terms of popularity compared to others.
Name: The official designation of the POI.
Address: The precise geographical location.
Industry: The sector or field to which the POI belongs.
Category: The specific classification within the industry.
This compilation serves to highlight the premier POIs, offering valuable insights based on public preference and engagement. | STRING (JSON) | [{"rank": 1,"name": "Extrò Grill Cafè","street_address": "Via Alcide De Gasperi, 105, 20017 Rho MI, Italy","industry": "Food & Beverage","category": "Restaurant"},{"rank": 2,"name": "The new Grancaffè","street_address": "Viale Luigi Einaudi, 21, 20044 Arese MI, Italy","industry": "Food & Beverage","category": "Cafe"},{"rank": 3,"name": "Green Pub Rho","street_address": "Via Pace, 89, 20017 Rho MI, Italy","industry": "Food & Beverage","category": "Pub"},{"rank": 4,"name": "Pasticceria Palma","street_address": "Via Don Virgilio Sioli, 1c, 20017 Rho MI, Italy","industry": "Food & Beverage","category": "Pastry"},{"rank": 5,"name": "Barriera di Terrazzano","street_address": "20017 Rho, Metropolitan City of Milan, Italy","industry": "Transportation","category": "Highway toll booth"}] |
has_phone | The provided metric indicates the proportion of Points of Interest (POIs) within the geometry that possess a listed phone number. | DOUBLE | 32.08 |
has_website | The provided metric indicates the proportion of Points of Interest (POIs) within the geometry that possess a listed website. | DOUBLE | 27.5 |
date_refreshed | The date on which the geometry data were last updated. Please note that due to technical reasons this date might not be the same for all rows in the same file. We strive to always provide you with the most updated information. | DATE | 2023-10-06 |
Rich Attributes
SKU:
DPK-LOC-RICHPlease note the Core Attributes are always included in this file.
Field Name | Defintion | Type | Example |
sentiment | Proprietary percentage KPI (valid range from 1 to 100) which measures the level of customers global satisfaction of a geometry.The score is calculated over a period of time equal to the last 12 months, starting from the value of the date_refreshed attribute, and is obtained through a proprietary semantic algorithm that takes into consideration multiple attributes of the online content (feedbacks, topics, opinions, languages...).
Please be aware that we enforce rigorous quality checks to uphold a high standard of data quality. Consequently, there may be instances where the value for some geometries is set to null, indicating that the data did not meet our stringent quality criteria. | DOUBLE | 84.78 |
popularity | Proprietary percentage KPI (uncapped range) that measures the level of popularity of a geometry.The score is calculated over a period of time equal to the last 12 months, starting from the value of the date_refreshed attribute, and is obtained through the analysis of multiple factors such as the number of geo-localised reviews and social media content.
This KPI can be used for comparison of geometries belonging to the same Industry. For more info on Industries and Categories, please see this page.
Please be aware that we enforce rigorous quality checks to uphold a high standard of data quality. Consequently, there may be instances where the value for some geometries is set to null, indicating that the data did not meet our stringent quality criteria.
More info about the Popularity Index here. | DOUBLE | 74.66 |
most_discussed_topics | Array in which each element represents a binary pair composed of Sentiment KPI (valid range from 1 to 100) and topic.Each value in the array is calculated over statistically reliable topics, a subject on which a user expresses opinions, that can be inherent to multiple industries and/or categories. All elements are sorted in ascending order, based on the value of the Sentiment KPI, and the array can contain a maximum of five elements that correspond to the most relevant topics identified. For each topic, the score is calculated over a period of time equal to the last 12 months, starting from the value of the date_refreshed attribute, and is obtained through a proprietary semantic algorithm that takes into consideration multiple attributes of the online content (feedbacks, topics, opinions, languages...).Please note that a topic name is supplied in English by default; it is possible to request another language among the following: French, German, Italian, Spanish, Portuguese.
Please be aware that we enforce rigorous quality checks to uphold a high standard of data quality. Consequently, there may be instances where the value for some geometries is set to null, indicating that the data did not meet our stringent quality criteria. | ARRAY (DOUBLE) | [{"topic": "personal","sentiment": 95.00},{"topic": "room","sentiment": 84.99},{"topic": "food","sentiment": 88.03},{"topic": "service","sentiment": 82.71},{"topic": "breakfast","sentiment": 80.16}] |
spoken_languages | JSON representation of the top 5 languages spoken, identified through the online content of the geometry. For each of the languages, two values are provided: Sentiment KPI, obtained through a proprietary semantic algorithm that takes into consideration multiple attributes of the online content in the target language (feedbacks, topics, opinions...); percentage, which expresses the impact ratio of contents identified in the target language with respect to the total contents. | ARRAY (DOUBLE) | [{"language": "it","sentiment": 85.93,"percentage": 94.39},{"language": "en","sentiment": 87.93,"percentage": 3.93},{"language": "de","sentiment": 100,"percentage": 0.56},{"language": "fr","sentiment": 100,"percentage": 0.42},{"language": "pt","sentiment": 100,"percentage": 0.28},{"language": "other","sentiment": 100,"percentage": 0.42}] |
review_date_refreshed | The date on which the geometry reviews were last updated. Please note that due to technical reasons this date might not be the same for all rows in the same file. We strive to always provide you with the most updated information.
Please be aware that the window for gathering and using reviews extends 12 months prior to this update date, including both the start and end dates in the range.
For example, if the review_date_refreshed is 2023-10-16, the reviews employed for KPI calculations are collected from the inclusive period between 2022-10-16 and 2023-10-16 | DATE | 2023-10-16 |
Accommodation Focus
SKU:
DPK-LOC-OTAPlease note the Core Attributes are always included in this file.
Field Name | Defintion | Type | Example |
traveler_origin | JSON representation of the top 5 travellers' countries of origin, identified through the online content of the geometry. For each of the countries, two values are provided: Sentiment KPI, obtained through a proprietary semantic algorithm that takes into consideration multiple attributes of the online content in the target country (feedbacks, topics, opinions...); percentage, which expresses the impact ratio of contents identified in the target country with respect to the total contents. | ARRAY (DOUBLE) | [{"country": "it","sentiment": 84.67,"percentage": 19.93},{"country": "br","sentiment": 84.96,"percentage": 7.89},{"country": "gb","sentiment": 84.87,"percentage": 7.56},{"country": "es","sentiment": 85.37,"percentage": 6.82},{"country": "fr","sentiment": 84.65,"percentage": 5.11},{"country": "other","sentiment": 83.71,"percentage": 52.69}] |
traveler_type | JSON representation of the top 5 traveller's' types, identified through the online content of the geometry.For each of the types, two values are provided: Sentiment KPI, obtained through a proprietary semantic algorithm that takes into consideration multiple attributes of the online content in the target type (feedbacks, topics, opinions...); percentage, which expresses the impact ratio of contents identified in the target type with respect to the total contents. | ARRAY (DOUBLE) | [{"traveler_type": "couple","sentiment": 83.51,"percentage" 44.12},{"traveler_type": "family","sentiment": 85.21,"percentage": 32.63},{"traveler_type": "groups","sentiment": 85.59,"percentage": 15.68},{"traveler_type": "solo","sentiment": 81.81,"percentage": 7.38},{"traveler_type": "business","sentiment": 92.90,"percentage": 0.19}] |