Based on research done by Royal Mail Data Services, bad data reduces turnover by 6%. Having bad name data in your data base prevents you from effectively nurturing new leads into new client wins. Similarly having bad name data can prevent you from retaining new business after the initial contract.
When we work with clients on cleaning up their existing database, we will usually find a good collection of records with the name Mickey Mouse, James Bond and Lewis Hamilton. The challenge is to know which of these records are real and which are fake. It is unlikely that parents would name their child Mickey Mouse but James Bond, while unfortunate, is not outside the realm of possibility. When we searched for Lewis Hamilton in Linked-In, we found over 5,325 results. We also found two obvious fakes in the first ten rows.
We also find names which are much ruder in client databases but again, some of these may be legitimate records. Letter combinations that form rude words in English are not necessarily rude words. Take for example the Scunthorpe Problem. In 1996, AOL’s obscenity filters blocked the name of the town because of the rude substring, which prevented its residents’ access to the service.
Reclaiming even a portion of the 6% of turnover lost to bad data will have a huge impact on your business but people will enter nonsense into your forms. Regardless of whether this is intentional or accidental, we need to be able to identify the legitimate records while preventing the time wasters’ data from polluting your database.
LOLAMATIC makes this easy. We have been helping clients prevent nonsense name data from entering their systems for twenty years. Our proprietary rules know which names to block, which names to flag and which names to let through. There is no need for you to change your existing forms you just need to add the code that we provide, and we will do the rest. Working with our implementation specialists we can have the LOLAMATIC code up and running on your form in about ten minutes.
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