A recent blog post on DataMentors discussed about house holding – a process of grouping related customer records. House holding is one of the most prominent aspects of selling by many industries today.
What house holding information allows is the ability to find out the aggregated relationship of a family as a whole with the organization. For example, a retailer may want to group customers from the same family unit to reduce cost of marketing and also cater to the preferences of the household versus individual customer preferences.
Talking from an MDM perspective, capturing household information in the system adds ample value to your solution. Since this data is crucial to marketing, managing this information in MDM, which is already a core system for trusted customer data, makes for a great selling point.
House-holding process comes with a unique set of challenges. Here are some of the key opportunities I have witnessed in many MDM implementations –
Deriving House Holding Data
A core challenge with house holding is to find ways in which this information is derived. Several aspects can be considered which include incubation of name parsing and address matching. Some times customers may actually be providing this knowledge. But as I have seen, this information is not very explicit. The other clue, which is helpful, is derived from customer’s account information such as joint accounts owned by two customers who share common last name and address. Phone numbers can also be used as criteria to increase the confidence level of grouping.
When we aggregate all these above techniques, we can have a wealth of knowledge linking parties in our master data management repository.
Regrouping of House Holding Data
House holding information, just like any other master data, is mutable. Some of the factors, which cause the change are – marriage, divorce, birth and death of a family member. So, if we are keeping all the distinct parties in a system like MDM, we need to periodically regroup them depending on the changes which might have happened. This can either happen in real time as the data gets added and updated, or can be done on a scheduled basis using a batch job depending on the criticality of the data requirements.
Distinguishing Customers and Individuals
When you group parties into households, we have to ensure there is a clear indication to show customers versus individuals. Here, individual is a person in the household who do not yet have a contract with the organization. This clear indication helps during cross-sell and up-sell opportunities to create proper messaging.
Grouping of customers seems like a simple process but in reality is one of complex exertion. If done correctly, this information can be of a great value-add to your MDM system and can help your marketing thrive by targeting right customers and prospects.
What are your thoughts? Do you have experience working with house holding data in a MDM system (or otherwise)? Do share.
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