About Cherre

Cherre is the leader in real estate data and insight. We connect decision makers to accurate property and market information, and help them make faster, smarter decisions. By providing a unique “single source of truth,” Cherre empowers customers to evaluate opportunities and trends faster and more accurately, while saving millions of dollars in manual data collection and analytics costs.

CoreExplore

Multi-Geography Search

Users are now able to search for properties, owners, and markets across multiple geographies of the same category within a single search. For example, it’s now possible to execute a search for off-market investment opportunities across the Chicago, Boston, and Los Angeles MSAs.

Multi-geography search is enabled for the following categories:

MSAs
REIS Submarkets
Zip Codes

Accessing Multi-Geography Zip Code Search

Note the new Filters button that will open and close the filter panel
Select the Geographies tab on the filter panel and the ZIP subtab
Select a City to filter the list of available zip codes
Select the zip codes you would like to search
The selected zip codes will be drawn on the map and results will instantly update to reflect the selected zip code criteria

Dynamic Filtering

We’ve added dynamic filtering to the property search in CoreExplore! When selecting search filters, your results will now instantly update as soon as a search filter is applied, providing instant feedback on how that filter selection is affecting your result set.

Custom Dashboards: Delete & Rename

You can now delete or rename custom created or edited dashboards! Use this feature to clean up your custom inventory.

Select the action icon on the subject dashboard you would like to delete or rename

Choose “Rename” or “Delete” from the menu

Confirm your the dashboard you are deleting or rename

Data Connections

BuildCentral - Construction Intelligence

We’re happy to announce that BuildCentral is now available as a Cherre Lightning Connection! Cherre Lightning Connections enable customers to add unique datasets to their Cherre data analytics warehouse within hours instead of weeks.

BuildCentral tracks early-stage planned developments prior to permitting through planning, construction and completion. Developments are tracked nationwide and include shopping centers, retail, restaurants, pharmacy, hotels, multi-family and single-family, medical, mining and energy. Attributes such as construction start and end dates, key contacts, tenants, unit counts, square footage are provided and updated through the construction process.

For more information, please see the BuildCentral data dictionary and sample data.

Habidatum - Risk Scores

We’re happy to announce that Habidatuml is now available as a Cherre Lightning Connection! Cherre Lightning Connections enable customers to add unique datasets to their Cherre data analytics warehouse within hours instead of weeks.

Habidatum offers real time property occupancy and mobility metrics, and location risk scoring. Habidatum's Location Risk Score ([Foot traffic * Density of Points of Interest (POI)]) is based on real-time mobile and business data and provides present, historical and forward-looking insights to enhance commercial real estate financial models. Data includes walkability and transit scores, foot traffic, dwell time, statistically normalized occupancy by building polygons.

For more information, please see the Habidatum data dictionary and sample data.

Data Kits

Introducing Data Kits for SFR

What are Data Kits?

Cherre Data Kits are collections of filtered and derived data and dashboards to serve specific use cases. Our Cherre Foundation layer and connected data provides a broad and flexible platform to apply in your business. Data Kits take specific groups of data, and filters, combines, connects, and transforms them in relevant ways to allow clients to answer specific questions, build specific models, or operationalize specific data even faster.

First American Table and Market Tables

Current market tables using publicly available tax assessor and recorder have a few blind spots, specifically non-disclosure states. Public records can also be enhanced by listing records to triangulate information on the characteristics of a property. Also, features like days on market, failed listings and price relative to list, are critical features in modeling market performance. All these features have been added to the Data Kit.

Listings Master:

Max/Min list and sale price
Changes in listing
Lot and home features
Agent features
Zoning

MSA, Zip, and School Boundary submarket tables:

Period type and period
Number of listings sold
Number of listing failed
Mean and Median days on market (both sold and sold + failed)
Mean and Median sold price and price/sq foot
Fraction of properties sold above and below list

New Seasonally Adjusted Home Values

Seasonally adjusted and smoothed values will now be available in MSA Market and Zip tables. Seasonal adjustments have been applied to the medians and means in the market tables using an autoregressive algorithm similar to that used in X-13ARIMA-SEATS by the U.S. Census Bureau's published software package. Smoothed data is also available which is represented as a rolling average.

Coming Soon - SFR Portfolio Details Dashboard:

This dashboard enables clients to search for portfolio owners by their public record names OR by our owner unmasking. It shows distributions by size, age, and bed/bath, the average pricing, and markets.

Coming Soon - Expanded Oxford Data:

For Oxford subscribers, expanded data will be available to build and run forecast models with our market tables.

SFR Data Kit Page:

We have launched our SFR Data Kit alpha page. This page explains the kit and what's in it, including data dictionaries, sample data, fill rates, and row counts.

Please feel free to check it out at https://cherre.com/coreconnect/sfr-data-kit/

Cherre API

Upgrade to Hasura v2

We have released a major upgrade to the GraphQl engine that powers Cherre’s API (Hasura.io). In addition to the added stability and security features that it brings to the platform, there are a few exciting new features for end users as well.

New Filtering Functionality

More robust filtering when joining from cherre_address to other objects:

Prior to this upgrade, when joins were made from cherre_address to other objects (see line 5 of the sample below), you could not apply filtering criteria to the joined object.

Now you can.

Ex: I want all alternative addresses for a given building, but only if the alternative address is associated with a tax record:

query demoExpandedFilteringOnCherreAddress {
  usa_building_footprint(
    where: { building_footprint_id: { _eq: 360610040763 } }
  ) {
    cherre_address__building_footprint (
      where: {
        tax_assessor__property_address: { tax_assessor_id: { _is_null: false } }
      }
    ) {
      display_address
      tax_assessor__property_address {
        tax_assessor_id
      }
    }
  }
}

Regular expressions:

_regex, _nregex, _iregex, _niregex operators can now be used for pattern matching on string/text fields.

Ex: I want all alternative addresses for a given building that do not contain Suite, Apartment, Unit, Floor numbers, etc.

query demoRegexFiltering {
  usa_building_footprint(
    where: { building_footprint_id: { _eq: 360610040764 } }
  ) {
    cherre_address__building_footprint(
      where: {
        display_address: {
          _nregex: "(STE|#|APT|FL|FLOOR|UNIT|PH|RM|LBBY|FRNT|BSMT)[, ]"
        }
      }
    ) {
      display_address
    }
  }

Change in Functionality

Semantics of explicit "null" values in "where" filters have changed

Prior to this upgrade, if you used an explicit null value in a comparison, the expression would evaluate to True.

Example where $tax_assissor_id is ‘null’

query demoNullBehavior {
  tax_assessor(where: { tax_assessor_id: { _eq: $tax_assessor_id } }){
    tax_assessor_id
  }
}

V1 results

Returns ALL tax_assessor records

Following this upgrade, the same expression will be treated as an error and yield an error message.

V2 results

{
  "error": {
    "errors": [
      {
        "extensions": {
          "path": "$.selectionSet.tax_assessor.args.where.tax_assessor_id._eq",
          "code": "validation-failed"
        },
        "message": "unexpected null value for type \"numeric\""
      }
    ]
  }
}

Parcel Boundary Connections

Finally, there are objects that are connected geospatially that use a slightly different convention and connect through an intersecting join. If you are looking to see different forms of an address, you can connect from cherre_address to parcel_boundary and then back to cherre_address to see all the other forms of the address that are connected to that parcel.

cherre_address(
    where: {display_address: {_eq: "185 GREENWICH STREET, NEW YORK, NY 10007"}}
  ) {
    display_address
    parcel_boundary__address_point {
      cherre_address__parcel_boundary(order_by: {display_address: desc}) {
        display_address
      }
    }
  }
}

Geocoding Addresses

Cherre geocoded an additional 48,622,513 addresses. This will improve geospatial match rates.

Coming Up Next

Power Query

Connecting Excel with Cherre GraphQL API

Wondering if you could connect and consume Cherre data in Excel? The answer is absolutely yes! We will be sharing a detailed guide in our next release and you will be able to connect directly to Cherre GraphQL API through Microsoft Power Query.

International Expansion

Connect data in UK and Canada

Cherre has released the ability to connect data in the UK and Canada as a new alpha product. Cherre will continue to expand its support internationally by adding more countries. If you are interested in connecting your UK and Canadian data today, please contact us.