Customer Data Integration Effectively Implemented

Customer data integration is a difficult process without the right tools.

Integrating different customer data sources with different field types, address standards, naming conventions, etc is a monumental task. Especially when you consider how valuable the information is. The comments and history associated with these records are needed to insure a flawless customer experience.

 

Keys to effective implementation

1.  Find someone who has done it before. Data Ladder’s customer integration specialists have completed hundreds of customer data integrations.
2. The right tools make all of the difference. Every data integration is unique. Data Ladder’s DataMatch suite has; multiple customizable match definitions so you can identify duplicate and matching customers effectively (Same email, or same address, or same company name, etc.), the ability to merge data into a single golden record that combines duplicate/matching customer data with no data loss, and the ability to save your work for use in future customer data integrations.
3.  Get started quickly with an affordable solution. Why waste time waiting for large companies to return your phone calls? Why spend $100K on a solution that takes months to approve, and weeks to implement? Get started today and contact  us for a free customized WebEx demonstration on your data.

Why Data Quality and Data Cleansing Projects Fail

Data Quality and Cleansing initiatives are essential to improving overall operational and IT effectiveness. However many efforts do not get off the ground and get stalled before they really start. Read more

More Than One Way to Skin a Database

I have been a solution manager for Data Ladder for several years and have been fortunate enough to learn more and new ways to use DataMatch 2011 to solve numerous data problems that I never even knew existed. From working with Hospitals analyzing critical data and preventing future chronic illnesses` to your every day saving cash by eliminating duplicates in a post mail campaign, DataMatch 2011 provides a wide array of intergrated tools that allow you to do much more than you would expect.

DataMatch 2011 provides you options to find and eliminate hard to find duplicates but also gives our clients many other cures for common database problems. From getting rid of unwanted characters across thousands and thousands of records to taking a column of data and parsing it out based on specific needs and sending that data to new or existing fields. DataMatch 2011 packs an incredible punch and should be investigated carefully to get the most out of this powerful world class software.

I personally encourage every possible user to ask our sales reps any possible questions that may come to mind or any possible scenario the user may have when it come to specific needs. You may be surprised how many different solutions DataMatch 2011 can provide you.

http://www.DataLadder.com/download.php

Manuel Suarez
Sales Manager
866-557-8102
tsuarez@DataLadder.com

Data cleansing techniques

The amount of data we all deal with every day is expanding rapidly. With expanding data and the ongoing addition of data sets, keeping data clean is essential. There are several different simple data cleansing techniques that can avoid and correct data quality issues. All of the following are included in our DataMatch product that we can walk you through in a customized WebEx demonstration.

Data Cleansing Technique 1: Data Profiling

Know what you have in your data. A simple look at the min/max, top values, and data types in every column/field of your data can flag data quality issues or misunderstandings within the data set.

Data Cleansing Technique 2: Simple Data Cleaning

Sometimes there are simple changes that go a long way. Removing a space, changing all O’s to zeroes, making a copy of a field to manipulate later, etc. Additionally other simple functionality like recognizing that Jon is a nickname for Jonathan

Data Cleansing Technique 3: Standardization and Parsing

Sometimes data is entered in an uncontrolled manner resulting in pieces of data in the wrong place. The zip code in the city field, etc. DataMatch is equipped with advanced libraries and pattern recognition to find and parse out the most common standard address pieces. Additionally other simple functionality like recognizing that Jon is a nickname for Jonathan and is a Male gender name can be very helpful for cleaning your data and making it more useable.

For non standard information our Wordsmith and Regular Expression creator allows for an infinite number of customized parsing possibilities.

Data Cleansing Technique 4: Duplicates and Fuzzy Matching

Simple misspellings are very common, Somewhere Way and Somwhere Way both look the same to a person, but to a machine they are different. DataMatch’s fuzzy logic algorithm can detect these subtle differences quickly and combine the records, either to simply flag as a duplicates, help determine which record should be a master complete record, or just to transfer data between the records as you see fit.

Our standardization and parsing logic allows you to create matches on parsed out text, like street number, zip code, etc. Additionally you can create multiple definitions of what a match is. For instance you can say any records with the same email address are a match, and any records with similar street, person, and city names are also a match.

There are a lot of details to the above data cleansing techniques and we hope you will contact us so we can show you how DataMatch can meet your data cleansing needs with a demonstration on your own data and specific needs. Phone: 866-557-8102 Email: Sales@DataLadder.com

Remove Duplicate Records

Duplicate Records Impact on Sales and Operations

Quick post.

The major issues with duplicate records are often not felt by IT departments.

Typically the every day pain is felt within the heart and soul of a company, it’s sales force and operations. Sales sees firsthand the cost and embarrassment of duplicate customer contacts, mailings, and wasted time trying to decipher which customer number to use for the same customer when multiples exist in the system.

Operations sees the returns, customer complaints, and duplicated effort.

While good IT departments are right on top of the issue, sometimes a reminder is needed, or even the opportunity for sales and operations to take the matter into their own hands with a simple and easy to use software suite like DataMatch.

IT is especially important in realizing the issues that duplicate records have throughout a company. A duplicate customer master can impact the whole company, confusing auditors, new employees, and generally aggravating management from a mistake and reporting perspective.

Now is the time to fix the issue once and for all, give us a call at 866-557-8102 for a free consultation and walk through of our data quality solutions.

Every data cleaning situation is unique

A quick post today.

One often overlooked fact is that every data cleansing situation is very unique.

Take a simple customer deduplication (removal of duplicates) exercise. At first glance it is a very simple problem. Identify the duplicates, and remove them. However once you get into the details you realize there are several items worth considering.

1. How do you identify a duplicate? Is it the company name? Contact name? Address? Maybe you deal with 2 completely different offices that are the same customer (IBM in Australia and in the UK for instance)

2. Do you want to remove all information about a duplicate contact? There may be important contact information or customer notes associated with the record.

3. Have all affected stakeholders in your organization been made aware that the cleanup was occurring? There may be individuals and departments inside your own organization who should be notified to insure no unintended consequences occur.

4. Are there any new standards you’d like to apply? Capitalizing street suffixes, separating full name fields to a First and Last name field, etc.

Note that Data Ladder is here to walk you through these issues which is why we give free personalized WebEx demonstrations addressing your specific data cleansing activity.

Any other big questions that I missed? Feel free to comment below. We welcome and thank you for taking part in the conversation.

Why Email Cleaning is Crucial to Effective Correspondence

Email has grown from a mere messaging medium to something indispensable in the corporate arena. Especially, official communication in the corporate sector happens through an organization’s mailing system. Though everything, from important decision-making to strategy-planning, happen in a matter of clicking send/receive/forward from your desktop, maintaining an effective email system is not as easy as it sounds. Read more

Getting a Real Return from your Data Quality / Data Cleansing Initiative

Getting a Real Return from your Data Quality / Data Cleansing Initiative

Some important basic areas that we will cover:

ROI: Return on Investment is a simple measurement of the success of a project. You need to know two pieces

Investment: How much the project will cost and how to get the best deal

Return: How much the project will return and how to maximize return Read more