Points of Interest (POI) are being applied to address so many problems it's hard to keep track of them all. I feel like I learn a new one every time I meet clients – surprising things we've never thought about. While site selection (where to put my store or other facility) is one of the stalwart applications, a client recently showed me a very sophisticated version of this using points of interest data that included public transit locations, and Spectrum's Enterprise Routing Module to measure distances between Medicare clinics and public transportation stops. The sophistication lies in how the distances are calculated and the result allowed this firm to improve utilization of their services by offering additional transportation options only where required. This not only assured that they complied with legislation but did it in a cost-effective way.
Choosing a business location is important as well. Many years ago I worked for a company based in Bradford, UK. Our highest profile client came to visit. They parked in the car park and made their way the 20 metres to the front entrance. This moment turned out to coincide with the moment the Police decided to carry out a raid on the flats opposite, and our client was caught in the middle of a lot of police and police cars. At this point my CEO turned to me and said "Andy we need to find a better location". We moved to a shiny office in Leeds.
Can you relate to these examples? The below list summarises how different industries use Points of Interest (POI) data. Are you doing something similar or different, or have you ever wondered if there was a way to improve your results by adding additional reference data to it? What would you want to achieve?
Financial Services firms use POI data to:
Retail firms use POI data to:
Insurance firms use POI data to:
Adtech firms (those who specialize in marketing to mobile consumers) use POI data to:
Telco/Wireless carriers firms use POI to data to:
Real Estate firms use POI data to:
Public Sector organizations use POI data to:
World Points of Interest is a best of breed data package, providing the best of many datasets conflated together.
These datasets have their own USPs and we thrive to ingest the same and provide our clients with best of both (or more) worlds.
But there is more to it than meets the eye, when it comes to conflating 2 or more datasets from different vendors. Each vendor has a unique naming convention of various brands/businesses.
For example, here are just a few ways how the famous retail chain 7 ELEVEN is represented by our major vendors like Dun & Bradstreet and TomTom:-
It would be paranormal for us to expect our end-customer to filter out all required POIs of 7-ELEVEN, taking all the above occurrences into consideration. No matter which DBMS is being used, one would have to manipulate his SQL query with the usage of wild cards and the keywords in all possible forms.
Wouldn't it be easier if there is just a single standardized occurrence of 7-ELEVEN, and to fetch the same, one would simply query out the brandname as it exists, without any wild card characters at all.
Standardized data is one of the biggest feats to achieve, and the business-trade-name, being the most important identifier of a POI, needs to be standardized.
The World POI team took this humongous task as a challenge and created an all new system with the help of latest technologies like Natural Language Processing, String-Matching Algorithms like Cosine & Levenshtein, pySpark, Jupiter notebook, etc.
As a result, a new attribute was introduced in the Points Of Interest dataset, namely BRANDNAME, which introduces one of the biggest data features craved by data specialists around the globe - standardized business-trade-name for a POI.
With successful application of Brandname Standardization in 24 major Countries and 3000 distinct Brandnames, the process is ever expanding and under continuous improvement.