Factual continually ingests fresh data and real world signals to improve the quality of our Global Places™ dataset. We pride ourselves on the accuracy and comprehensiveness of our data and strive towards expanding our data offering.
Earlier this year, we announced the addition of two new countries (Saudi Arabia and the UAE) to increase our global coverage, plus ten new categories to our taxonomy to more accurately categorize the places in our dataset.
Along those lines, we’re pleased to share another improvement to our Global Places data: the expansion of our Global Chain IDs. Our Chain ID feature exists within Global Places to enable easy filtered access to all instances of a popular chain business.
For example, if you were to perform a plain text search of Factual’s data for “Starbucks” in an attempt to view all Starbucks coffee shops, you would have the misfortune of getting this Starbucks Roasting Plant back in your results, which does not have a coffee shop to buy and drink beverages. Performing an exact string match on the “Name” attribute is not necessarily sufficient either; consider the “Marriott Hotels & Resorts” case, where records like the New York Marriott Marquis and the Seattle Marriott Waterfront both belong to the same chain, but don’t share the same name.
To streamline this process for our partners, we have expanded our Chain ID and Chain Name fields, where all instances of a particular chain are assigned the same unique identifiers on which you can search. Instead of searching the “Name” attribute for “Starbucks”, you can search “Chain Name” for “Starbucks” and have only the actual coffee shops returned.
This is not only helpful for search and mapping use cases, but also useful for setting more specific targeting parameters within our Geopulse product suite. Marketers who want to send a contextually relevant ad to people at Target retail stores most likely don’t want to include people at the Minnesota Twins game at Target Field, and can benefit from using Chain ID and Chain Names in our Geopulse Designers.
The filtering options make it easy to specifically target users who frequent certain chains, but also allow for interesting and complex targeting parameters. For example, you can easily target users who frequent mom-and-pop coffee shops by specifying places with a category of “Coffee and Tea Houses” while also excluding all places with a Chain Name of “Starbucks”, “Peet’s Coffee and Tea”, and others.
With this expansion of our Chain ID coverage, we have increased the number of unique chain identifiers from roughly 300 to over 1,500 across 52 countries. We are pleased with the improved user experience this expansion provides our clients, and we will continue to improve the quality and coverage of Global Chains through 2017 and beyond.