Home Page
       Company Profile
       Why Data Quality?
       Support / FAQ's
       Social Responsibility
       Contact Details
Current Customers

Address Data Cleansing

Data quality issues, which include name and address and non-name and address data cleansing and validation, play a major role in some of the biggest issues affecting businesses, such as customer relationship management (CRM), corporate accountability and supply chain management strategies.

What is Address Data Cleansing?

This is the group of transformations performed on data containing individual and business names as well as domestic and foreign addresses for the purpose of improving the quality of data. Such transformations are usually referred to as parsing, standardization, correction and augmentation:

  • Address parsing is the breakdown of non-discrete input into discrete address components.
  • Address standardization is the modification of components to a standard version acceptable to a postal service or suitable for record matching.
  • Postal correction involves matching an input address with postal database entries to verify and/or correct an address.
  • Augmentation adds derived information to the data, such as gender based on name, or collection of census and geo-location data

Over half of all CRM projects are doomed to major problems because of data quality issues. Address Data Cleansing is a crucial component for any CRM implementation. This process for CRM dramatically reduces wasted effort and cost by eliminating redundant data. In addition it facilitates strategic business goals such as cross-selling and up-selling existing customers.

It is an important factor for projects that involve any type of name/address data such as vendors, suppliers, partners, employees and more. Address Data Cleansing will simplify processes, reduce costs and enable important business objectives such as strategic sourcing initiatives.

Its objective is to ensure that the mailing database conforms as much as possible to the Post Office standard, thereby attracting the maximum possible discounts, and reducing the amount of gone-away returns.

Accurate address data cleansing and post coding is paramount to the success of a direct mail campaign. If your records are out of date, the chances are that your mailings won't reach their intended target. If they do, it creates a negative impression about your organisation.

Your list of customers and prospects is potentially the most valuable asset your company owns. It is important to keep your list current and correct. Removing duplicates as well as fixing data problems saves wasted postage and material costs when mailing to your list.

An efficient list enhances your customer relationship and focuses your marketing efforts. Enhancements like Phone Number and Demographic Appends can make it easier to target the customers you need to find, and follow up with them after the fact.

Intimate Data is able to offer organisations a complete service. Intimate Data regularly assist our clients in maintaining accurate postal records for their customers. We are able to correct customer records that contain misspellings, and poorly formatted or incorrect address.

Intimate Data also specialise in correcting address data that other cleansing companies have failed to correct. For severely corrupted name & address data, this can involve manually rebuilding addresses and on occasion, customer contact to ensure the accuracy of such data. Many organisations offer automated address data cleansing which will achieve 80-90% accuracy or clean up. What about the remaining 10-20%? Often, the only way to successfully resolve these cases is to individually rebuild each address.

Maintaining accurate data on your customers is a prerequisite in today's legislative framework. We understand the importance of this and encourage our clients to maintain all customer address records in an accurate manner.

Poorly addressed items inevitably result in letters remaining undelivered, involving unnecessary postal and production costs. This service can help to solve this problem and enable to you claim additional postal discounts.

Indispensable for Customer Value: Address Data Cleansing

Despite many different negative examples, problem awareness concerning the data quality of customer and prospect addresses is still below average. That is surprising, since the possible negative effects are quite serious: avoidable high costs, severe impairment of customer relationships, missed opportunities.

What data warehousing, CRM and ERP projects have in common is the integral approach. With the aid of business intelligence and analytical applications, the aim is to create a much better foundation and support for making competent and well-founded decisions.

During data integration, short-comings in the data quality often become obvious. Inconsistencies and faulty, obsolete and incomplete data or redundancies are frequently discovered. These defects necessarily have an effect on all of the aggregated or derived data. This in turn impairs the integrity of the data analyses to a great extent or even makes them unusable.

One of the greatest challenges in constructing and utilizing data warehouse and CRM projects is the quality of the initial data and the data extraction from heterogeneous sources. Usually customer data from the most diverse applications and databases is exported in a uniform format. But by no means should one assume that the customer-relevant data from the diverse applications and areas of the company is in good condition. That is connected, among other things, with the fact that the address data and other customer data were originally recorded and used for other purposes. Particularly here the necessity of cleansing and maintaining the integrity of address data becomes obvious, in order to prevent faulty data representation and flawed data evaluation and analysis. Of course, the same applies to follow-up, quality-assurance measures in the ongoing contact with customers, whether it be per e-mail, telephone or via Internet (e-CRM).

Address Data Cleansing | Data Linking | Data Scrubbing | Direct Marketing | Mailing List | Data Cleansing
Data Quality | Deduplication | Merge Purge | PAMSS