Data Cleaning
Accuracy and up-to-date data are critical for effective CRM

Being in the data business since 1983, we care about data quality a great deal because its business impact is HUGE!

For instance,

Duplicates not only mean wastage, but they also tarnish your brand image when your customers receive multiple copies of your promotion material all the time

Incomplete / inaccurate address leads to deadmail, i.e. wastage in postage, printed material, etc. and more importantly potential loss of sales due to inability to maintain communication with customers)

Our data cleaning (Data Quality Management, DQM) solution addresses 4 main points that our clients care very much about:

1. Deduplication

Over years, we have accumulated hundreds of deduplication rules applicable to different data quality patterns. Our engine identifies the duplicate records and assigns different confidence levels for our clients to decide what to keep versus what to purge.

As customers may not have filled in complete information and / or there could be illegible typos, data quality inevitably varies from record to record.

In an attempt to strike a balance between data quality and data cleaning cost, we have designed our data cleaning engine to score the records into different quality gradings. The primary purpose is to allow us to prioritize our resources in cleaning the data that require the most attention. And in doing so, we are able to better manage the data cleaning cost for our clients.  

3. Error Correction

Based on service level chosen by the client, we will correct data errors based on a combination of technology and human judgment from our experienced data quality specialists accordingly.

4. Data Validation and Recovery

Based on service level chosen by the client, we will validate “suspect” data and recover incomplete customer information.

User Interface of Data Cleaning Module