In this section, we provide a set of tutorials that showcase how to get the most out of the CARTO platform, in particular through the Workspace, Builder and Workflows interfaces that are detailed in this User Manual.
These tutorials leverage the demo data provided by default via the CARTO Data Warehouse connection, so you can start creating maps and exploring our tools from the very beginning.
Planning for product launch by shortlisting merchants in high-potential segments
We identify merchants to launch a healthy beverage product through customer segmentation and filtering based on trade area characteristics.
Identifying target area for marketing campaign using consumer sentiment data
We find coffee-loving areas to launch a marketing campaign, based on consumer sentiment data.
Territory planning for a personal care product
We divide the Chicago metropolitan area into territories and report on their Total Addressable Market for a personal care product.
Score areas based on demographics to select advertising panels
In this tutorial we explore the best locations to place panels for Starbucks advertisements, using geosegmentation and spatial indexes.
Identifying billboards around POIs using proximity analysis
We find the OOH panels closest to a certain point of interest, in this case Starbucks, using proximity analysis .
Build a store performance monitoring dashboard
In this tutorial we are going to visualize revenue performance and surface area of retail stores across the USA. We will construct two views, one of individual store performance using bubbles, and one of aggregated performance using hexagons. By visualizing this information on a map we can easily identify where our business is performing better and which are the most successful stores (revenue inversely correlated with surface area).
Selecting a new restaurant location with spatial analysis
We find the best new location for a specific target demographic using spatial indexes and advanced statistical functions such as Commercial Hotspots.
Analysing urban areas affected by earthquakes
In this section, we provide a tutorial that showcases how easy it is to perform geospatial analysis operations using CARTO Builder. In this example, we will analyse the total of urban areas affected in Spain by earthquakes over 2021. This type of analysis can be useful to show the general situation of risks threatening a given population in order to be able to plan measures and actions to mitigate their possible negative effects (human, economic and environmental).
Build an interactive map and embed it
In this section, we provide a tutorial that showcases how easy it is to create an interactive map using CARTO Builder and share it, embed it on your web page, or using a low code tool to create a story map.
Analysing AirBnb ratings in Los Angeles
In this tutorial we will analyze which factors drive the overall impression of Airbnb users by relating the overall rating score with different variables through a Geographically Weighted Regression model. Additionally, we'll analyze more in-depth the areas where the location score drives the overall rating, and inspect sociodemographic attributes on these by enriching our visualization with data from the Data Observatory.
Assessing the damages of La Palma Volcano
Since 11 September 2021, a swarm of seismic activity had been ongoing in the southern part of the Spanish Canary Island of La Palma (Cumbre Vieja region). The increasing frequency, magnitude, and shallowness of the seismic events were an indication of a pending volcanic eruption; which occurred on 16th September, leading to evacuation of people living in the vicinity. In this tutorial we are going to assess the number of buildings and population that may get affected by the lava flow and its deposits. We'll also estimate the value of damaged residential properties affected by the volcano eruption.
Build a categories and bubbles visualization
Understanding population distribution has important implications in a wide range of geospatial analysis such as human exposure to hazards and climate change or improving geomarketing and site selection strategies. In this tutorial we are going to represent the distribution of the most populated places by applying colors to each type of place and a point size based on the maximum population. Therefore, we can easily understand how the human settlement areas is distributed with a simple visualization that we can use in further analysis.
Build a dashboard with a local CSV file
In this tutorial we are going to showcase how to upload a local CSV file to your CARTO Data Warehouse and then use it to build an interactive dashboard with our map-making tool, Builder.
Subscribe to public data from the Data Observatory
In this tutorial we are going to showcase how to leverage the public data offering from our Data Observatory and use the data from a subscription to build an interactive dashboard in our map-making tool, Builder.
Build an animated visualization with time series
There is an increasing need for conservation and connection with nature in cities. In this sense, geospatial analysis plays an important role in the effective management of our natural resources. In this tutorial we are going to represent the distribution of tree species in the streets of San Francisco by color and we will add some interaction through widgets, which will allow us to explore the map by selecting targered filters of interest. In this example, filters are applied by specie and date of planting.
Create a tileset and build a basic visualization
Understanding the urban areas has important implications in a wide range of geospatial analysis, for example, to inform decision-makers in sectors such as urban planning. In this example we are creating a tileset in which each building in Madrid is represented by a polygon and each of them is assigned a graduated color from the lowest to the highest value of the gross floor area. This visualization allows us to represent at a glance how the surface area in Madrid is distributed.
Pinpoint new store locations closest to your customers
Understanding & analyzing spatial data is critical to the future of your business. CARTO 3 Location Intelligence platform allows organizations to store, enrich, analyze & visualize their data to make spatially-aware decisions. In this example we are going to use points clustering to analyze how to find the best place to locate six stores in Portland city based on proximity to customers.
Creating a tileset from a Data Observatory subscription
In this tutorial we are going to showcase how to leverage the public data offering from our Data Observatory and use the data from a subscription to build an interactive dashboard in our map-making tool, Builder. In order to build this dashboard we are going to first create a tileset in order to be able to visualize a larger amount of data.
Build a 3D map with a tileset
A geospatial analysis of land use dynamics has special relevance for the management of many phenomena, such as the assessment of the loss of soil due to erosion or the reduction of rural land in favour of the built-up areas. In this regard, Digital elevation Models (DEM) are important inputs to quantify the characteristics of the land surface. In this example we are building a map from a tileset created by CARTO from a new NASA Digital Elevation Model (NASADEM). We are going to represent the distribution of land elevation by using a gradual color palette and then build a 3D visualization by assigning heights to polygons.
Identifying customers potentially affected by an active fire in California
Use CARTO Workflows to import and filter a public dataset that contains all active fires worldwide; apply a spatial filter to select only those happening in California. Create buffers around the fires and intersect with the location of customers to find those potentially affected by an active fire.
Finding stores in areas with weather risks
Leverage CARTO Workflows and Builder to analyze weather risk data from NOAA, to figure out which retail stores locations are exposed to a weather-related risk in the US.
Calculate walk-time isolines for top retail locations
Create walk time isolines for selected retail locations. It includes some examples of simple data manipulation, including filtering, ordering and limiting datasets.
Estimate the population covered by LTE cells
Leverage CARTO Workflows and Builder to estimate and analyze the population that is covered by telecom network cells based on the LTE technology.