Address-based householding¶

A household is a group of people who share a physical address and possibly other attributes. For example: a shared device or network, a shared last name, a shared phone number. Householding is a process that identifies a unique household in a dataset.

Address-based householding is a process that standardizes addresses, pairs them with a last name, and then assigns that pair a Household ID.

A Household ID is a universally unique identifier (UUID) that uniquely identifies the combination of a standardized address and a last name.

Note

Address-based householding is a starting point. An implementation of address-based householding can vary across brand use cases, depending on the

Type and number of data sources
Number of addresses
Types of direct mail campaigns that will be based on the results

How it works¶

Address-based householding is built upon the results of the Merged Customers table. This enables address-based householding the ability to use the results of individual identity resolution that is available from the Merged Customers table.

Apply the results of address-based householding to campaigns that rely on physical addresses, such as direct mail campaigns, to ensure that a single household gets a single piece of direct mail, even when multiple unique individuals reside within the same household.

Tip

Address-based householding can be improved when used alongside standardization provided by national change of address (NCOA) and coding accuracy support system (CASS).

National Change of Address (NCOA) is a secure dataset of about 160 million permanent change-of-address (COA) records. NCOA records consist of the names and addresses of individuals, families, and businesses who have filed a change-of-address with the United States Postal Service (USPS).

Coding accuracy support system (CASS) is an address standardization concept that helps clean address to make them more effective for direct mail campaigns.

The process for enabling address-based householding includes:

Reviewing the Merged Customers table to identify any tenant-specific behaviors within the table that may need to be considered when extending Amperity for address-based householding.
Reviewing the bad-values blocklist to identify any tenant-specific behaviors within the blocklist workflow and to identify the name of the domain table associated with the bad-values blocklist feed.
Adding a feed for the address-standardization.csv file
Adding a Merged Households table to the customer 360 database
Building segments that use the Household ID, which is a UUID that is available to segments from the Merged Households table.
Sending segment results to any downstream process.

Tip

Additional configuration options for address-based householding include:

Joining the Merged Households table to the Customer 360 table to add the household_id and household_size fields. This makes them available as profile attributes.
Using a common table expression (CTE) to flag a single individual that is associated with an address as the primary contact.
Adding a Household 360 table. This is similar to the Customer 360 table and can merge values down to a single row per Household ID. This enables the use of summary attributes, such as identifying household lifetime value.

Add the data asset¶

Address standardization starts as a feed that loads a CSV file that contains a list of address variations for state and street names.

Note

The address standardization data asset is available from Amperity Bridge, or, alternatively, from an Amazon S3 bucket named Amperity Data Assets. For most current use cases, Amperity Bridge is the preferred approach.

Configure Amperity Bridge. Choose the Reference data option, and then select the address_standardization_conversion table.
To use the Amazon S3 bucket as the source for address standardization, make a request to Amperity Support to enable file-based data assets, after which you can use the Amazon S3 data source to load the “address_standardization_conversion.csv” file from the “/householding” directory in that bucket.

To add the address standardization data asset

After adding the address standardization data asset, use all three fields–before, convert, and type–as the primary key.

Add a passthrough table to your customer 360 database named LookupTables AddressStandardization, and then run your customer 360 database to build the LookupTables AddressStandardization table.

Important

The LookupTables AddressStandardization table is used within the Merged Households SQL template in a series of LEFT JOIN operations that are used to standardize addresses. For example:

LEFT JOIN (
  SELECT
    UPPER(before) AS before
    ,UPPER(convert) AS converted
  FROM LookupTables_AddressStandardization
  WHERE type = 'STREET'
) AS a7clean ON (a7clean.before = core.a7)

You can name this table anything else, such as Address Standardization USA. If you use the Merged Households SQL template, you need to update the LEFT JOIN sections within that template to contain the updated table name.

Add Merged Households table¶

The Merged Households table applies address-based householding and address standardization to the output of the Merged Customers table and adds a column for household ID. Use the Merged Households table to improve campaigns that send offers to shared physical addresses, such as direct mail campaigns.

The Merged Households table starts as a SQL template that defines how address-based householding works in Amperity.

From the Customer 360 tab, under All Databases, select the menu for the customer 360 database, and then click Edit.
Click Add Table. Name the table “Merged_Households”.
Set Build Mode to “SQL”, and then define a SQL query.

Important

Amperity uses a single table in the customer 360 database to collect rows from the Unified Coalesced table, and then collapses them into a single row per Amperity ID.

This is referred to as the Merged Customers table. Prior to August 1, 2020 the name of this table was Unified Merged. Verify the name of this table as it is used for your tenant, and then update the template to match the name of the table in your tenant.
The section titled “Basic address standardization” is a common table expression (CTE) that performs address standardization.
What is address standardization?

Address standardization is a process that
- Removes non-alphanumeric characters
- Trims for leading, trailing, and repeating whitespace
- Converts characters to uppercase
- Converts all valid names of states in the United States to their two-character representation
- Converts all postal codes to five digits
- Converts common representations of street addresses into standardized variants
Physical street addresses, as identified by the address field, are standardized by splitting on spaces. Each of the second, third, fourth, etc. elements of an address are compared to a lookup table. When matches are found, they are replaced with standardized values.
The section titled “Build the Household ID” builds a universally unique identifier (UUID) from unique combinations of the address and surname fields.
The section titled “Get count of Amperity ID per Household ID” associates a count of Amperity IDs to each Household ID.

Tip

Additional SQL may be added to handle custom statistics on a per-household basis and to support other tenant-specific use cases. The default behavior only associates the Amperity ID to the Household ID, but can be tailored to support most use cases.

For example, you could add support for checking the number of Amperity IDs associated with a household, and if that exceeds a threshold, that address could be flagged as a business address or some other non-household entity.
The section titled “Create flag for addresses in bad-values blocklist” identifies if addresses have been added to the bad-values blocklist.

If you are using the bad-values blocklist, uncomment the following sections.

The blv_address block (lines 209 - 220):
```
blv_addresses AS (
  SELECT
    amperity_id,
    CASE
      WHEN (blv.value IS NOT NULL)
      THEN TRUE
      ELSE FALSE
    END AS blv_address
  FROM clean_addresses AS AD
  LEFT JOIN Blocklist_Values AS BLV
    ON AD.address = UPPER(BLV.value)
)
```
where Blocklist_Values must be updated to be identical to the name of the domain table that is created by the bad-values blocklist feed.

Tip

The blv_addresses block may cause duplicate rows. Use SELECT DISTINCT if you run into issues with duplicate rows.

Caution

When uncommenting the blv_addresses block, be sure to add a comma after the closing parentheses (“)”) in the household_stats block or you will get a validation error.

The blv_address line in the last SELECT statement (line 230):
```
,BL.blv_address
```
The LEFT JOIN for blv_addresses (lines 248-249):
```
LEFT JOIN blv_addresses AS BL
  ON CONCAT_WS(' ',AD.address,AD.address2) = UPPER(BLV.value)
```
The section titled “Build Merged_Households table” combines everything into the Merged Households table.

Tip

Extend to support additional use cases, such as for specific household-level statistics or to add filter criteria that checks for BL.amperity_id IS NULL or for ST.amperity_id IS NULL.
Click Validate to verify that the SQL query runs correctly.
Make the table available to the visual Segment Editor by checking the box in the Show in VSE? column.

Note

The Merged Households table contains the Amperity ID and should be made available to the Visual Segment Editor.
Click Activate to update the customer 360 database with your changes, and then run the customer 360 database to update the Merged Households table.

Build queries and segments¶

The default Merged Households table makes available two new columns for segmentation: household_id (the address-based Household ID) and household_size (the number of unique individuals who share the same physical address).

As a SELECT statement, the Merged Household table is similar to:

SELECT
  amperity_id AS "amperity_id"
  ,household_id AS "household_id"
  ,household_size AS "household_size"
  ,full_address AS "full_address"
  ,given_name AS "given_name"
  ,surname AS "surname"
  ,address AS "address"
  ,address2 AS "address2"
  ,city AS "city"
  ,state AS "state"
  ,postal AS "postal"
FROM Merged_Households