6 Tips to Improve Your Business Data
Who has customers has data, and who has data can better meet the needs of the customers. Everyone agrees with the first statement. As for the second, most marketers may agree, but one might conclude that it is true only when companies pay attention to the quality of their data. Unfortunately, it still seems that they are still losing a lot of money (and customers) because of the poor quality of their data. What can you do to maintain or improve your business data quality?
Data quality – garbage in, garbage out
When the data is incorrect, it can impact the entire business process and the relationship with the customer. For example, the e-mails do not arrive, the unsubscriptions are not correctly processed, the invoices are sent to the wrong addresses and the employee of the service department does not know if the person on the phone is already a customer (for a long time). And the number of frustrated clients is increasing, as are the number of claims. The bad data therefore cause a domino effect. They cost money and loyalty. Because the “garbage in” becomes the “garbage out”.
A study proves it
A recent study on data quality found that the incorrect data directly affected earnings in 88% of companies surveyed. A company loses on average 12% of its revenues in marketing expenses, and that also means staff hours wasted. The same study found that only 38% of participating companies use software to monitor data at the time of entry. So there is bread on the board, because who does not have his data in order loses money because:
- missed sales opportunities because sales signals are unclear;
- e-mails sent to bad addresses (high bounce rate);
- printed materials sent to wrong addresses;
- of the shipping costs, because many unnecessary stamps are pasted on invoices or mailings;
- of the call center, because more (dissatisfied) customers are calling or efficiency is decreasing due to bad phone numbers or contact persons;
- of the reputation of the brand, because you send the wrong message to the wrong customer.
Factors Affecting Data Quality
The quality of the data depends on internal and external factors. The sensitivity to errors is furthermore a function, in particular, of:
- responsibility (who are the people to monitor the quality of the data?);
- how to enter the data (manual input is more error-sensitive than the automated method);
- the number of different systems (the more databases , the more often the data is duplicated and the more frequent the errors);
- the pace of data change (do customers often move or are new products frequently in the assortment?);
- the control mechanism (are errors quickly identified?);
- the data processes (are there rules for introducing, cleaning and maintaining data? Are master data indicated?).
Tips for improving the quality of your data
To use the data successfully, it is important to prevent duplicates, gaps and errors. What you can do in different ways. The good news is that some of these measures are easy to implement and are therefore quick win, which you will immediately get the fruits.
- Connect your systems to external sources – You can have your data checked by external parties, periodically, but also permanently. Your customer addresses can thus be easily checked and edited, and duplicate data can immediately be duplicated.
- Automate processes and interfaces – When you connect your data systems, you can save your customer data to a central location. When other systems perform updates on the central file, you are certain that introductory errors are avoided and that everyone works with the same data.
- Integrate controls – Configure automatic reports and e-mails, with which an employee can check at fixed intervals whether the data has been entered. Give the person the authority to correct the mistakes of colleagues and to inform them.
- Improve your business process management and simplify data entry – For example, ask users to follow a logical step-by-step plan for importing the data, and make sure the application to the couple’s background and saves the data itself the right way.
- Work with required fields – Ensure that users cannot go further in the registration process when critical data is not, or not correctly, completed. Block the possibility of recording errors, for example, by programming telephone numbers as (00) 123 45 67, which are not accepted.
- Give incentives – Everyone does not like to enter data. Vendors are, for example, reputed to have difficulties in correctly recording the data. They want to be on the road, and not sitting in front of a computer. Yet, the seller can accurately collect valuable data during his contacts with the customer. By combining incentives or bonuses with the quality of your data, you can encourage your employees to take the time (correctly) to input the data.
Data quality and data governance
Data quality and data governance are similar, and sometimes confused. Data governance concerns the quality of data, but it goes further: it also covers other aspects such as compliance, risks and privacy. You can apply lessons learned from your data quality programs to your entire data governance, which will reduce the risk and time it takes to implement data governance.
