Unless you have someone managing your database full-time, it’s likely that your database has been touched by dozens if not hundreds of employees over time, which in turn means it’s likely a bit of a mess.
This is especially true in the title industry, where data is critical to a transaction and many different staffers may be touching the database on a regular basis.
Let’s take a quick look at why it is important to have a clean database and what it means to “clean” a database.
Why clean up the database?
Cleaning up a database is arduous. The “why” is easy.
Data, if properly managed and effectively used for decision-making, can save time and increase revenue.
For example, at the end of the year when you are putting together your business plan for the next year, being able to pull a quick analysis about who, what, when, where and how orders were generated in the previous year, can help you make a more accurate assessment about where your particular market is trending and where you might most effectively deploy resources in the coming months.
Then, of course, there is the marketing side of the equation.
A clean database allows you to segment your marketing so that your messaging is appropriate to each of your verticals. Correct addresses ensure your expensive marketing materials arrive on your client’s desk. And finally, it’s a lot less embarrassing if the marketing piece arrives with the name spelled correctly. Less egg on your face!
And finally, a clean database means your staff can actually find what they need easily or quickly access a snapshot of a customer’s interactions, saving you both time and money in the long run.
What it means to clean data
In cleaning your database, you are striving for accuracy, completeness, and consistency. Here are the two most important goals in cleaning your database:
Normalization
Ensure you are entering data in the same way each time. For instance, be consistent in how you are going to classify your clients. Instead of variously entering RE, agent, realtor or real estate agent, normalize all entries to real estate agent. If a staff person inadvertently enters RE, cleaning up the database means normalizing the entry back to your preferred classification. Normalization of data entry makes it easier to export data effectively when you need it.
This applies to how you enter the name of a company, or how you enter addresses, for instance do you use Rd or Road, Ave or Avenue. Establishing rules helps in data entry and data cleanup.
Complete entries
When life gets busy, your staff may find themselves slamming information into a database, just to get the customer’s name in without taking the time to fill in all of the details that will be needed later for analysis or marketing purposes. Cleaning up data involves following up on the entry to ensure important data is included or training your staff on the importance of keeping data current.
If you are struggling with managing your database effectively, contact us at Premier Data Services. Database management is just one of the many services we offer at PDS, and we would be happy to consult with you to determine the best path forward for maintenance, administration and optimization of your database.