Considerations for Accurate Data Cleansing Process
January 4th, 2019 | Hitesh Mistry
Accurate data is the prime necessity for every company planning to derive branding, advertising or marketing strategies. Data, starting from customer’s contact information to time spent on the website, list of social media interactions and past buying experiences; every single details has to be collected and managed appropriately. However, the quality of these data points is equally important as much as the quantity.
Marketers and data analysts are endowed with the responsibility to keep the data clean. Data entry errors such as typo and mistypes word or name, nonexistent email IDs and all the information which is collected from customers is likely to be full of mistakes and hence time consuming when it comes to be utilized. However, in a situation where no data points are perfect, there are chances that marketers and data scientists can create and adhere to data cleansing process which ensures the accuracy of required insights for strategic planning and decision making.
Enlisted are some of the considerations to be made to execute accurate data cleansing process.
1. Adhere to data entry best practices
Regulating the data entry process, before initiating the data cleansing process, is more important. It works as an early error detection strategy, where all the customer information or data is entered with utmost care; and a quality check of that data is done in on regular basis. Defining the type of errors likely to happen and also the kind of impact it can have on your business processes, really helps. Also check out if your data entry teams are watching out for errors that occur due to incorrect keystroke, field or application interpretation errors. Setup a schedule to conduct the rechecking of such information.
2. Accuracy of data entry
Training data entry professionals to collect and enter perfect data is the first step towards producing accurate data. Also, if they know how important is the data which they enter, and its accuracy of course, and how it will impact the overall business function – will give them that feeling of responsibility to put in more efforts to strive to enter accurate data. Motivate them to collect and check the third party data for correctness.
Setup mutually agreed data accuracy goals, and then start tracking the progress in that direction. Primary data checks will help you find out how much data is entered, how much is correct and how much needs to be re-entered or corrected due to data entry errors. Because you have set accuracy goals, checking out on how the data entry teams are faring and whether they are improving or not is convenient. Adhering to this process would also highlight the areas of improvement, in the overall data entry process, to ensure non repetition of such errors in future.
3. Touch the high priority data first
So now that you are set to start cleansing the business data, take the first step to identify high priority data that matters the most to your business and what do you think of doing with that data. Check out if the job titles are significant, and are the last names appropriate as you would want for your email marketing strategies. Implementing the data cleansing process for the most critical data is advised as in case you are required to withhold the activity – you are sure that you have cleaned the most important datasets which will help you continue operating your business till a time you come back and address the remaining data pieces.
4. Standardized data points
Ensuring all the data entered is same as entered at other locations is equally important. In postal addresses, spelling out “Road” and “Rd” may sound to be a small mistake but it is not. Postal codes, area codes and state codes – are they entered accurately, are they correct? Some of the contacts or customers do not have a title – so is purposeful or a data entry error? Colleges or universities updating student’s academic status should look out for automating the update of corresponding state. Auto populating matching postal codes with the state is also a possibility which should be checked. Ensuring all the information and data points are in a standardized format – will help you efforts of solidifying data accuracy.
5. Check for data gaps
Now is the time to see what data elements are missing and whether the information is correct or not. Checking whether the information which is missing is due to the reason that it was unavailable at the time of data entry – is not available or not. It is called data validation and helps big time in filling up data gaps. If you encounter instances where a lot of campaign emails bounce back or social media tags are incorrect or outdated it is time you start checking for data gaps and fixing them by validating the data.
Data gaps should be checked for customer information including phone numbers, last names, emails, or other essential personal data. Validating the data gaps requires hands on experience and expertise in web research, which is a time taking process. However, it cannot be avoided as it ensures that the business data keeps your company in touch with the customer. Take help of reliable third party data experts to review that data. While you can fall back on data entry best practices to check the authenticity you can also prepare data gaps assessment guidelines for future purpose.
Every data cleansing activity does not end with data accuracy. What about the automation? Yes, automating the repetitive tasks for easy to collect information and a futuristic strategy.
Remember, your marketing efforts and strategies are only as good as your data. Data cleansing process is the prime necessity for successful branding, advertising or marketing strategies. Accurate data by adhering to data entry best practices should be the motto.