House Holding in MDM System

Blog

House Holding in MDM System

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.

Image courtesy of Stuart Miles/FreeDigitalPhotos.net

COMMENTS

16 Thoughts on House Holding in MDM System
    Henrik Liliendahl Sørensen
    18 Sep 2014
     11:38am

    Good stuff Prash. May I bring my favorite subject, being external reference data, into play? I have had good experience with using property data for this purpose. You are more certain about that it is a household if you know the address as a single-family house or you have an existing unit in a multi-occupancy building. Further, if the address is a nursing home or a university campus you should not try to group occupants into a household.

    0
    0
    Tony Ellis
    18 Sep 2014
     6:15pm

    Great points Prash. I’d simply add that from a public sector perspective that household view is often critical. Whether it’s income generation ensuring the right level of taxes are paid, reducing fraud/error, local democracy ensuring everyone has the vote or the protection of the vulnerable that household composition is vital. Always a good moment when customers realise that the proverbial single view is more than just the citizen.

    0
    0
    Gary Allemann
    19 Sep 2014
     9:41am

    Hi Prash

    Another pet topic of mine.

    In South Africa individuals have a unique Identity number – many MDM projects rely on this number ofr matching (similar to a US Social Security number it should be unique to an individual). Not withstanding that poor data quality means that ID number is frequently not unique (or accurate) this cannot be used for householding.

    So other shared attributes must be used for householding – address, etc.

    from a census perspective the Statistics South Africa describe a household as a group of individuals who spend at least 4 noghts a week under the same roof – quite a challenge to model that 🙂

    have a good weekend
    Gary

    0
    0
    Raja Krishnamoorthy
    20 Sep 2014
     4:22pm

    Nice article Prashant. One telecomm client had an interesting case – households could be different – e.g., Service department is interested in Service Location; Billing department is interested in Billing Location – they called it economic household – e.g., you may be paying for your parents internet,tv and phone and you and your parents would be in the same economic household.

    Really interesting stuff and if you add geocoding to this the use cases are endless.

    Raja

    0
    0
    Dennis Moore
    20 Sep 2014
     11:32pm

    Prash –

    Great stuff. BTW, there are multiple forms of households, and an individual can be part of multiple households. For example, sometimes you are interested in people sharing an address, but sometimes you are interested in people who have financially dependent relationships or familial relationships. You may also find people who have multiple addresses, including children shared between divorced parents or folks who move between two addresses (e.g., college students, “snowbirds”). In a sense, household relationships are just like any other kind of relationship. Thanks for another great blog.

    – Dennis

    0
    0
    Flemming Vestergaard
    21 Sep 2014
     12:11pm

    Household control of customers is a cool data setup for data-driven CRM in dialogue marketing. Purchasing patterns tell more about the household when adding up the individuals. Individuals are kept on own records and only intelligently viewed and utilized as statistical data about households. When individuals separate, decease, etc. the households are automatically updated. Here in Denmark, I mainly use the KVHX address key which is strong data match along with cleansing validation of the individuals. Works great. I understand other countries have more challenges. Great to learn how you match in other countries.

    0
    0
    Vishu Rastogi
    21 Sep 2014
     1:30pm

    Hi Prashant,

    Householding is an interesting topic indeed. Many of the customers still struggle to use to this useful concept in their MDM implementation lacking data quality. Many of the folks have presented some really interesting use cases indeed. I think integrating with external references such as census data or data from other public departments (viz.. IRS) etc periodically is a sure shot way to re-enforcing integrity of your house holding data periodically.

    One another piece that I find fascinating is how with the explosion of social media, the concept of house holding has taken a “glamorous” turn. By analyzing the social media interactions within the house hold of family, friends and relatives one can try to “personalize” the results house hold experience. The integration of these two, which i believe is definitely happening somewhere in the retail industry represents a really amazing integration of concepts and technology.

    -Vishu

    0
    0

Leave A Comment

RECENT POSTS

Businex-Blog

Composable Applications Explained: What They Are and Why They Matter

Composable applications are customized solutions created using modular services as the building blocks. Like how...

Businex-Blog

Is ChatGPT a Preview to the Future of Astounding AI Innovations?

By now, you’ve probably heard about ChatGPT. If you haven’t kept up all the latest...

Businex-Blog

How MDM Can Help Find Jobs, Provide Better Care, and Deliver Unique Shopping Experiences

Industrial data is doubling roughly every two years. In 2021, industries created, captured, copied, and...