The Segmentation Snapshot functions enable you to determine the pre-calculated population segment for a location. Segmentation is a method that divides a populations into subclassifications based on common traits. For example, you can take the a store location and determine what classification of population exists around that location. If you need help creating coordinates from addresses, see the [Geocoding Functions](https://carto.com/docs/carto-engine/dataservices-api/geocoding-functions/) documentation.
_**Note:** The Segmentation Snapshot functions are only available for the United States. Our first release (May 18, 2016) is derived from Census 2010 variables. Our next release will be based on Census 2014 data. For the latest information, see the [Open Segments](https://github.com/CartoDB/open-segments) project repository._
point geometry | A point geometry. You can use the helper function, `CDB_LatLng` to quickly generate one from latitude and longitude | `CDB_LatLng(40.760410,-73.964242)`
The segmentation function returns two segment levels for the point you requests, the x10\_segment and x55\_segment. These segmentation levels contain different classifications of population within with each segment. The function also returns the quantile of a number of census variables. For example, if total_poulation is at 90% quantile level then this tract has a higher total population than 90% of the other tracts.
x10\_segment | text | The demographic segment location at the 10 segment level, containing populations at high-levels, broken down into 10 broad categories
x55\_segment | text | The demographic segment location at the 55 segment level, containing more granular sub-levels to categorize the population
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #a3ce57'></div> Low Income on Urban Periphery</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #add468'></div> Suburban, Young and Low-income </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #cbe598'></div> Young, working class and rural </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #d5eba8'></div> Low-Income with gentrification </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #52BCA3'></div> High school education Long Commuters, Black, White Hispanic mix</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #66c5ae'></div> Rural, Bachelors or college degree, Rent owned mix</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #79cdb7'></div> Rural,High School Education, Owns property</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #8bd5c1'></div> Young, City based renters in Sparse neighborhoods, Low poverty </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #5D69B1'></div> Predominantly black, high high school attainment, home owners </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #7b83c6'></div> White and minority mix multilingual, mixed income / education. Married </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #9095d2'></div> Hispanic Black mix multilingual, high poverty, renters, uses public transport</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #a3a7df'></div> Predominantly black renters, rent own mix </td></tr>
<tr><td>Middle income, single family homes</td><td></td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #E58606'></div> Lower Middle Income with higher rent burden </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #f0983b'></div> Black and mixed community with rent burden</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #f4a24e'></div> Lower Middle Income with affordable housing</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #ffc792'></div> Struggling lower middle class with rent burden</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #ffd0a3'></div> Older white home owners, less comfortable financially </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #ffdab4'></div> Older home owners, more financially comfortable, some diversity</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background: #77b8ee'></div>Older, middle income Native Americans once married and Educated </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#388d7e'></div> Works from home, Highly Educated, Super Wealthy </td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#87decc'></div> Wealthy Diverse Suburbanites On the Coasts</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#8a64b1'></div>College town with poverty</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#b491d5'></div>City Outskirt University Campuses</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#c9a8e8'></div>City Center University Campuses</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ee7655'></div>Younger, Long Commuter in dense neighborhood</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#f38060'></div>Long commuters White black mix</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#f98a6b'></div>Low rent in built up neighborhoods</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#fe9576'></div>Renters within cities, mixed income areas, White/Hispanic mix, Unmarried</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ff9f82'></div>Older Home owners with high income</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ffa98d'></div>Older home owners and very high income</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ffb399'></div>White Asian Mix Big City Burbs Dwellers</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ffbda5'></div>Bachelors degree Mid income With Mortgages</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#ffd2bd'></div>Bachelors degree Higher income Home Owners</td></tr>
<tr><td></td><td><divstyle='float:left;margin-right:10px;width:20px; height:20px; border-radius:20px;background:#e488c9'></div>Very wealthy, multiple million dollar homes</td></tr>
