Cleanlist Announces New Age-Enrichment Service for Canadian Databases
For Immediate Release on April 16, 2024
London, Ontario. Cleanlist today announced the release of a new, first-of-its-kind data service to append estimated age to Canadian consumer database records. In performance testing against benchmark geo-demographic age-enrichment solutions, the new Cleanlist service outperforms by a margin of at least 25% on typical consumer databases.
“We’re excited to announce this innovative age-enrichment solution that will help our clients gain further audience insight and improve database segmentation accuracy. Although appending a person’s age is a common capability in the United States and some other less-privacy-regulated markets, it’s a huge challenge in Canada.
Credit bureaus have age data but accessing it requires consumer consent. Until now, the only alternative has been to use geo-demographic data where the average age in a postal code is appended to all its occupants. This is obviously not very precise. Cleanlist’s new solution represents a major advancement for researchers and marketers who are interested in the age of their audience.”, says Jeff Bisset, Cleanlist’s founder.
About Cleanlist’s Age-Enrichment Service
Cleanlist’s Age Append service was AI-trained against massive datasets containing millions of records with a known name, address, and date-of-birth. The resulting model determined that first-name, in addition to location address, provided a significantly better estimate of a person’s age, versus considering location alone.
The AI-model found a distinct correlation between a given name and the year of birth. For example, Brittany, Dylan, and Taylor were very popular baby names in the 1990’s. Whereas Francine, Jerry, and Lorraine were popular in the 1950’s. Cleanlist’s model found thousands of similar examples.
The model found spelling mattered too. Names like Joan were common in the 1950s and earlier, but Joanna and Joanie are likely to be younger. Common names like Jason have always been popular, but Jayson was most likely born in the 1980s.
Some names like Michael, Elizabeth, and David don’t correlate to a birth year. These names have been given to babies for decades and don’t provide much insight. In these cases, the Cleanlist Age Append service defaults to using the traditional, geo-demographic approach.
The new Cleanlist Age Append service succeeds in appending an estimated age to over 95% of a database that contains full names and location addresses.
Key Features of Cleanlist’s Age Append Service:
1. Uses name and location address data to estimate the age of an individual.
2. Test results indicate an accuracy rate that’s at least 25% better than traditional geo-demographic age estimating approaches.
3. An estimated age can be appended to over 95% of a typical consumer database.
4. The service can be acquired stand-alone, or in combination with data hygiene, cleansing, and other data enrichment services.
5. The service is offered via batch-processing or can be called through a REST-API for individual record enrichment.
For more information or to receive a quotation for age enrichment, contact Cleanlist directly at sales@cleanlist.ca. Or, call Cleanlist at 1-800-454-0223.
About Cleanlist
We’re Canada’s largest customer data company. We clean, enrich, and validate business and consumer data. We’re also experts in data-driven document composition and Canada’s largest data provider for digital and offline marketing. To learn more, visit us at Cleanlist.ca
