Data Appending Process - An overview

Business data append process can add wealth of business contact information to your existing customer file. The new information from data appending can be effectively used to extract move value from CRM application and improve customer communication.

During data append process, our automated data matching tool use data matching engines and complex algorithms to accurately locate similar data. Data Check Central undertakes data-matching & appending process to exponentially add relevant data to customer file.

DCC's DATA APPENDING PROCESS:

Step 1:

Customer identifies and uploads business data to our site through email or through FTP upload. We accept data in .csv, excel, access or in comon database format.

Step 2:

On receipt of data, our data evaluators examine the data on 25 point data measurement metrics. Then we proceed to match the data with our in-house master database of 18 million records. This automated process verifies the data fields, and marks matched data.

Step3:

After locating similar matches, we manually examine the validity of matches. Once verified, new data is appended to the external data.

Step 4:

On completing the append process, we also verify the accuracy of records through record validation. This is either done through telephone validation or through opt-in verification.

Step 5:

After we finish the data append process, our data evaluators will browse your data with our analytical software. This tool will sneak-peek into your database and build a generic profile of your database. This tool locates similar data pools and enable you to unearth hitherto unknown customer traits and demographic patterns.

To learn more on our business data appending service, please fill-in your details. Our representative will contact immediately to evaluate your requirement.

Why emails fail to reach in-box

Why emails fail to reach in-box

Marketer, we have a problem!
It's nothing new, but it's getting bad. Recently one of our partner's email was black listed by their ISP. We checked with ISP to know if it's a spam issue. Surprisingly the issue came from email bounces.

Before we go in detail, let's understand more about email bounces and the types of bounces.

Email bounce happens when your email can't get through the recipient's in-box. Reason for email bounces are notified to the sender thorugh an automatically generated message.

There are two types of bounce. Soft bounce and a hard bounce.

Soft bounces happen when your email cannot be delivered to an address due to a temporary error.

• Inactive Account
• Message too large
• Temporary Domain failure
• Out of Office
  
• Mailbox full

A hard bounce indicates the non-delivery of email due to a permanent error.

Most common reasons for hard bounce:

• Bad address syntax
• Address does not exist
• Unknown domain
• Invalid domain

Recent report show that major email clients like AOL are filtering email based on hard bounces. This shows the importance of list hygiene in email campaigns. Rise in email bounces is a hint about the rising number of junk data in your database.

If you're experencing email bounces beyong 5%, then it's time to give a thought about list-management. Steady list cleansing activity will keep dubious data from entering your system. Moreover, list managment efforts will bolster your relationship with ISP's and keep your goldmine intact for more golden deals.

Data Quality challenge - Q&A

What is the three question you should ask before you take up any any data management initiative?

Effective data management initiative should tackle the roles, responsibilities, procedures concerning the acquisition and maintenance of data. Organizations of all kinds should examine business trends and customer service levels before addressing a holistic plan on data management.

3 Key questions you need to address before you start Master Data Management (MDM) project:

• Do you trust the quality of the data?

• Does the data conform to the expected business rules?

• Will the existing data suffice the required functionality?

Effective data management initiative provides organizations with the ability to share data across all spheres of activity. This require the responsibility and co-ordinated effort of all the departments accessing the data (e.g., Sales, marketing, manufacturing). The teams concerned with the data have the responsibility to frame the common business rules and definitions for data.

DATA QUALITY MANAGEMENT CHALLENGES

Deploying data quality management program comes with many challenges. Here are the most common issues that crop while implementing data quality management.

• Responsibility delegation from the concerned departments
• Less cooperation between dept units
• Failure to recognize data management problems
• Low level of corporate discipline
• Less budget allocation
• Difficulty to quantify ROI

Data corruption: Causes and avoidance

Errors in b2b customer data can cause embarrassment to consumers and adversely affect your brand perception. Although errors in B2B data are unavoidable, it's best practice to maintain constant check on the burgeoning data.

Most common trait in b2b database is the prevalence of incomplete or inaccurate customer data. Erroneous data in your repository can result in lost sales opportunities and fudge the effectiveness of CRM initiatives.

Let's uncover the common errors in customer database.

Data Entry by Employees

Employees input errors to systems by mistake or intentionally to save time

• Misspellings
• Transposition of numbers/data
• Incorrect or missing codes
• Wrong data formats
• Data placed in the wrong fields
• Unrecognizable names
• Inconsistent use of nicknames
• Wrong use of abbreviations

Data Entry by Customers

Customers input details wrongly or in the wrong input column. Most often online users intentionally enter erroneous data to protect their privacy or add junk data.

External Data/ Data errors during data migration

Third party data often contain inconsistencies and errors. This can degrade the value of your in-house data and undermine the database values. Another entry point of wrong data is during data migration data error is when you're merging

How Data Check Central Can Help

With our proprietary data cleansing process, we can clean and matched your data with our large b2b database. We drill down our attention to each individual record and ensure that all fields contain consistent data. Our sophisticated match & cleanse technology use automated data cleansing process with manual check to ensure complete data cleaning. Apart from appending quality data, we also validate data to ensure 100% accuracy of appended records.

Strengthen your front-line data with Data Check Central's data matching services.

For more information call us or visit our site. For immediate call back, please give details in the online form given below.

How to Control Expenses through Data Cleansing

Most companies in U.S is feeling the pinch of the recession and almost all are adopting some form of cost-cutting. Companies In drive to cut corners, one aspect is left out - Cost of maintaining relevant customer data.

To cut cost, businesses must adopt effective data management process. This involves avoiding corrupt data, removing inaccurate data, and reducing the number of duplicates in your database. To achieve this feat, all the biz must create a holistic plan at all customer-touch points to reduce the of

Data Quality

Data quality involves in ensuring accuracy, timeliness, completeness, consistency and relevancy of customer data. Good quality data allow businesses to use it for effective decision, prediction and for extracting value from CRM tools.

How to get the complete process

One way to use data to connect with users is through data profiling. It helps to improve the effectiveness of Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), or data warehouse application project. Data profiling is done through statistical analysis of data quality with in a data set. It uncovers the relationship that exist between different values within and across the database.

How to conduct Data profiling

The main purpose of data profiling is to consolidate the data to form a single-master resource. Before you start with data profiling, it's essential to:

1. Discover the common entity points in the database

2. Understand the attributes that carry similar information

3. Extract the common parameters form the data

4. Transform the data into standardized form

5. Benchmark with similar records

About Data Check Central:

DCC provides enterprise solution for data profiling, data cleansing, data augmenting and data standardization to create reliable information for your business. With Data Check Central's data solution, you can add business intelligent data into your existing file. Our services are best fit for small and medium sized business, and can dramatically improve the returns.

Email List Management - Calendar

Data Check Central enables optimal use of your permission-based (opt-in) email marketing through email list management and data deployment services. We use secure data management solution to ensure full-worth of your CRM data used in email marketing.

Key features of our email management services:

Manage Database Imports

We remove duplicates and clean imported data. This involves automatic removal of bad/bounced emails after each campaign.

Response Reporting

After each email campaigns, we can monitor email deliveries, bounces, and unique click-throughs.

Un-subscribe Management

We manage and maintain a comprehensive list of un-subscribes. This help you to find the using an automatic removal function in the footer of every email delivered.

Message Personalization

We can personalize your email by obtaining personlization elements to your customer record.

Database Exports

After cleaning your email database, we can send it across in excel or any other desired database format.

Data Check Central has the capability to transform your data into most vibrant marketing asset. Our data managers can extract, transform, and re-model the data as per your business specification.

Here are some typical data-cleansing functions:

Standardize data & Normalize values

We can normalize all business phone numbers, standardize transform addresses to a common format.

Replace missing data values

We use our master database to find and insert missing information( phone #s, mobile #s, zip codes, SIC code, correct physical address, fax #, etc.

DCC's data service facilitates the in-depth identification of individual records and make our digital asset the most added information in your repository.

For more information call us or complete the online form.

What's Your Business Resolution?

At the start of every year, I set few personal & biz goals -- call them New Year's resolutions. This year is no different about my resolve, but I've made a twist to the plan. Instead of compiling a long list of wannabe goals, I'm focusing my efforts on the most important aspect in personal and business life.

I've read in an interesting blog post about how important is to have fixated on "ONE" vital item to achieve your goal. So, here I'm going to make it a ritual in my daily life.

In my conversation with my clients, they ask what they need to focus in 2010. I didn't take much time to answer. I retorted on the need of the hour - "CUSTOMERS", & customer “DATA”.

In other words, start focusing on customer data and you'll have steady return by nurturing relationships.

Good quality data will help you to separate the wheat from the chaff - ie find the best customers.

So there's my business resolution for 2010 and my suggestion to you. I'm keen on collecting your responses, and willing to learn from your biz experiences. Shoot me your comments, and I'll be all ears.