Customer-Centric Information Architecture For Efficient Customer Insight

Traditionally, many large service businesses, haveCustomer holistic view, cannot be optimised. For
focused narrowly on direct operational needs likeexample a CTP handling sales inquiries and orders,
order handling & invoicing, when designingcannot perform efficient cross & up selling
their information architecture. This way they havewithout the Customer holistic view, which allows
developed account-centric data structures. A realthe call agent to assess the profile of the
Customer could have more than one accounts,Customer and handle the case accordingly.
the records of which were unlinked in theBusinesses active in highly competitive
customer database. In this case, more than oneenvironments cannot afford not to develop
Customer records, would exist for the same realCustomer insight. CRM systems have been
Customer. This data model would not reflectdeveloped in order to efficiently manage the
accurately the relationship of the Customer to theCustomer interface and capture & exploit
Business. Moreover this information architectureCustomer contact history. However CRM
would often involve loosely coupled or isolatedsystems integrate with other operational systems
databases, thus developing departmentalin order to support end-to-end processes. These
'information silos'. For example the faults calloperational systems have to align to a
center database, would not integrate to the orderCustomer-centric information architecture, in order
handling database. Therefore the Customerto achieve the Customer holistic view. Having
interaction history would be fragmented in variousrealized the paramount need to develop
isolated systems, serving specific Customer touchCustomer insight, Businesses have started
points (CTPs). The information architecturereorganizing their information architecture and
described above, does not support the Customergradually developing their Customer-centric
holistic view, which is needed in order to provideinformation assets.
quality Customer service or analyze efficiently theThe process is gradual because legacy data
Customer behavior.structures and account-centric data, inherit their
Any analysis on Customer data which are storedproperties to the new systems, during migration
in an account-centric structure is problematic. Forprojects. In order to avoid the inheritance of the
example, one might want to calculate a simpleundesirable properties, records of the same
Customer value ranking based on the last quarterCustomer should be identified, if possible, and
invoiced amounts. However, this would rather bemerged in order to realize the new
an account value ranking, than a Customer valuecustomer-centric structure. The resulting
ranking, since the analysis would probably not'Customer tree' is a structure which incorporates
aggregate all accounts related to a specificall accounts and products, related to the same
Customer. Business wise, it is erroneous to carryreal Customer. This business need has been
out Customer analysis on the account level, sinceidentified by vendors active in the data quality
this analysis may give an incomplete picture aboutniche market. They started offering record
a Customer. Furthermore, one might want to'matching & merging' functionality, in order to
perform a recency analysis based on Customerdevelop and maintain customer-centric information
interaction history. This analysis won't beassets (such products are Trillium, Firstlogic,
effective, if the Customer interaction historyAscential). Being able to view 'one face of the
cannot be consolidated in a single database. AnyCustomer' is of paramount importance to
CRM interaction which is not based on theoperational as well as analytical CRM.