Because not every data available in your business are customers, there may be prospects, leads, spill data etc.,
Who should read this?
Executive managers, including chief executive officers, chief operating officers, chief strategy officers, or any other executive who needs comprehensive
customer information in order to provide business insight.
Directors who needs to see total sale in a specific department.
Privacy professionals, including chief privacy officers, who have a mandate to individualize constituents on behalf of their companies.
Marketing executives, including marketing vice presidents, directors, product managers, and anyone else who needs to target the right customers and
prospects for meaningful interactions.
Program managers who are responsible for customer-focused initiatives like CRM, target marketing, voice-of-the-customer projects, market research, and
customer surveys. Most of these initiatives require customer detail that can be delivered through CDI.
Sales managers and field salespeople, for whom customer relationships can mean the difference between a good year and a bad year. These professionals
need to understand customers as individuals.
Financial analysts who need to understand not only company performance, but the contribution of customers to their company’s bottom line.
Customer support managers and representatives. Simply put, they need to know who they’re talking to. Data integration helps to see their entire picture of
their customer while they talking with them.
You need to be truly analytical before you integrate a data into your system. Once you are done with integration then it would be easy to do
Master Data Management.
Real Facts
Enormous Data. Enormous Users. Enormous Platforms. Millions of business questions. No wonder companies can't get their arms around the information!
Most of the executives believe that their business would grow from 1 to 20 percent if they could gain access to comprehensive data.
Case Study Scenario I
You work for an HMO and are challenged with the issue of patient compliance. HMOs and other health care providers often struggle convincing patients
to fill their medication prescriptions. Providers have found that patient compliance is directly correlated to lower costs and better outcomes, so you want
to make sure your patients follow doctors’ orders. However, it’s imperative that the pharmacist understand the patient’s other medications to prevent
unpleasant side effects of incompatible drugs being taken together. Looking at the wrong patient record at the wrong time could literally mean life or death.
This newfound knowledge leads to the now-common refrain from executives for a “single version of truth” about their customers. They want to know
how customers are interacting with their companies, be it by telephone, Internet, or in the brick-and-mortar store. They want to understand what
customers are buying, and what they’re paying. They want to distinguish between “good” customers and “valuable” ones. They want to map relationships
between corporate customers and partners. They want to read and hear customer feedback. And, above all, they want to understand what accounts for
the company’s profits, and what can improve them.
If you don't have an integrated data about a customer then you can't:
1.Map an individual customer back to a point of service
2.Determine which consumers shop across channels
3.Optimize partner and reseller referral plans
4.Determine their highest-value customers
5.Personalize communications with customers
6.Individualize customer conversations during real-time interactions
7.Understand hierarchies between and across business-to-business (B2B) relationships
8.Make sense of encoded or abbreviated information
9.Perform effective propensity-to-buy or propensity-to-churn analysis
10.Determine “hot” prospects
11.Refer customer prospects to the salespeople most likely to sell to them
12.Incorporate knowledge of customer history or behaviors into the customer conversation
Making Data Integration Work
Data integration involves an often complex combination of processing and technology. The obvious justification of DI at most companies is to provide
a consistent way of accessing customer details. Via DI, these details are complete, integrated, and clean, thus freeing the applications to focus on their
core functions. Of course, the information technology (IT) infrastructure around DI will vary depending on the specific business needs, the functional
requirements, and the actual technologies used.
Data Integration Architecture using data warehouse:
What is Data Integration:
Responsibilities of a DI Architecture
Because DI is so new, it’s important to understand the functionality associated with retrieving, transporting, transforming, and delivering data between systems.
So we’ll start with a simple logical architecture, evolving it to introduce the different types of features associated with DI. Once we’ve completed our logical architecture,
we can turn to the various alternatives for physical implementation.
The goal of any architecture should be to:
1.Provide a framework for addressing functions in a simplified and efficient manner
2.Create an environment in which economies of scale and development reuse is the norm, not the exception
3.Build an infrastructure that reflects overall system requirements, not just specialized application needs
The benefit of DI hub technology is that it alleviates application systems from having to deal with complex data integration processing, particularly when the
data integration requirements are highly specialized or apply to multiple constituents. Since the rules governing details such as household definition,
customer identity recognition, or even address standardization can be complicated, it makes sense to address that processing in a single location.
This should improve efficiency, improve accuracy, reduce overall costs, and decrease processing