No, this is not a blog post about how to handle customers that unjustly complaints about everything.
This is a blog post about how to maintain high quality data in customer databases.
When doing that, there are some types of party entities that are more difficult to handle than others. In general B2B (business) entities are more complex than B2C (consumer/citizen) entities. Some of the B2B types I have spent more time with than others are the following:
Restaurants are some of the more demanding guests in our databases:
- They do change owner more often than most other business entities making them a new legal entity each time which is important for some business contexts like credit risk.
- On the other hand it’s the same address despite a new owner, which makes it being the same entity in the eyes of other business contexts like logistics.
- In many cases you may have a name (trade style) of the restaurant and another official name of the business – a variant of this is when the restaurant is franchised.
Public sector bodies can’t be sliced the same way as private entities:
- Often it is hard to state if a business partner belongs to a narrow defined or a broader defined unit within a governmental or local authority.
- Public sector bodies tend to have long names that may be used with different inclusion of words, sequence of words and abbreviations of words.
Global enterprises may be seen as one or as thousands of customers:
- The need for hierarchy management is obvious when it comes to handle data about business partners that belongs to a global enterprise – risk management, 1-1 marketing, sales force automation and so on will use the same data in many different ways.
- Company family trees are useful but treacherous. A mother and a daughter may be very close connected with lots of shared services or it may be a strictly matter of ownership with no operational ties at all.
These are some of the facts of life that make it fun and not trivial when you are conducting data matching and other activities in order to achieve and maintain high quality of customer master data.