Before any company starts with analytics the most important thing to consider is the quality of the data. May companies face the problems of low response rates to campaigns and business activities and when a quick investigation of their data is done, the result is always a low data quality in the system. A large portion of the data they use it is out of date or badly formatted or erroneous.
With the fast growing competition and an increase of businesses relying on data, data quality is one of the most important factors in the success of every organization. Until and unless the data quality objectives are not met in an organization, the employees and management cannot gain full confidence on the strategies and decisions they develop based on information they have. Cleansing data and improving the quality of data in the organization is an ongoing process. It is not just a onetime affair. Data constantly gets imported into your database and also get updated and transformed. This increases the possibility to a higher state that the data you are using goes stale with time. Therefore the data management system should be such that it should constantly monitor and prevent the bad data coming into the system. Data enhancement, Data cleansing, Bad data prevention, and De-duplication are the tasks which have to be constantly managed by the data quality process.
Data Quality Objectives for Every Company
There are many data quality objectives for which every data oriented company tries to achieve. The first objective is that you are not just failing at the very first step. If you have devised your marketing campaigns for the customers who do not exist or you have incomplete records, your campaign is sure to be unsuccessful if the data is mostly bad. Good data is the first priority which every salesperson and marketer needs.
The second quality objective is the reducing of efforts and time spent on hunting for right information and data. If the phone numbers and email addresses are not formatted properly or missing, the people working with these data sets will spend more time in fixing the errors and collecting the right information. Nothing annoys you much if you see a data non working. The good solution for achieving this objective is to have a system which allows data in a particular format only which should be specific to the format of every country targeted.
No 1 Objective
The most important objective out of all data quality objectives is the money. Bad data means wastage of time and money and a big amount of it is wasted on poor campaigns. A big amount of money is wasted in fixing the errors in the data before starting the campaigns. If the data quality is already good there is no wastage of money in these activities. Good data leads to better conversion rates and therefore more business out of your campaigns.