High sales data quality is essential for successful customer relationship management and for acquiring new customers. The more accurate and consistent your sales data quality is in the CRM, the easier it is to retain your customers. Just take a look at the following tips and tricks to help you influence the quality of your data and data integrity.
Taking Preventative Action
If you want to improve both the reliability and the quality of your CRM-data, preventative action is the key to success. When introducing the CRM system, make sure that only correct data is entered into the system and that no important details are overlooked. This will significantly reduce the risk of problems occurring later due to incorrect data. Instead of spending a lot of time cleaning up incorrect data, you should simply use accurate and well-defined data from the outset to achieve high sales data quality. The following tips will help you to be successful:
- Provide data access on a need to know basis. Only giving a select group of users access to a specific set of data might help you in avoiding bad data in the long run.
- Your CRM should come with a duplicate detection feature. Definitely put this feature to good use in order to prevent duplicate data entry. Of course, you can define the specific rules that are going to govern duplicate data detection.
- Before any data becomes part of the database, specific CRM data validation rules apply. Make sure that you define the type of data that is required for each field. While some fields might require a numeric value, a date might be required for other fields, for example.
- You can also set up a method for forcing a specific piece of data to be entered before the new information can become part of the database. This should help with the overall integrity of the record that is being entered into the system.
While these preventative measures are extremely important for maintaining the integrity of your data, certain rules apply to the processing of existing data in order to ensure a high level of sales data quality on an ongoing basis. This step is also known as CRM-data management.
CRM data management for high sales data quality
When new information is entered into the CRM system, you have the option of changing or editing the existing data. However, you should bear in mind that the quality of sales data can also deteriorate as a result of such editing. To ensure that you do not have to clean up the subsequently changed data again at a later date, you should define appropriate rules for this process. These rules specify who may edit the existing data, under what circumstances and at what time. It is advisable to keep an eye on the following guidelines for CRM data management:
- Only grant data editing permission to those users with a need for updated data in a particular area. By restricting the level of access and putting strict rules for data editing in place, you can help avoid errors.
- Data auditing at the field level can be useful for some organizations. If you are making use of the auditing feature, this means that you can change data that has been incorrectly edited back to the original data. Nevertheless, auditing should only be used sparingly. Take all of the required preventative steps in order to minimize the amount of auditing that is required.
- Moreover, you should define the rules that apply to the altering of data. This is important to ensure data integrity. You might consider putting an approval process in place, for example.
As you can see, data change management plays a key role in maintaining data integrity. If you pay attention to these guidelines, you might be able to identity and avoid poor sources of data early on. Once bad data has been identified, you should take the required corrective action in order to address this problem. Of course, we also provide you with some best practices for how to go about repairing bad data.
Repairing Bad Data
Data maintenance is required when incorrect data has been discovered. However, you should not only replace the erroneous data with accurate data, but also take all preventative measures necessary to ensure that such erroneous data does not find its way into the system in the first place. Learning from your mistakes is the key to avoiding erroneous data altogether in the future. Perhaps you will take the following recommendations to heart during this process in order to increase your sales data quality:
- Thanks to the duplicate detection feature, you can merge records that contain duplicate data. The end user entering the new set of data will thus be faced with the decision of either continuing with the creation of a new record or abandoning his record in favor of the already existing record. This is important so that duplicate record creation can be avoided at all costs.
- You should perform a data cleanup process on a regular basis. Even if you have all of the right checks in place, this step is important in order to maintain data integrity.
- Periodic backups are key. This will ensure that you are safe even if major problems come up. Make sure that your backup makes a complete recall of data possible.
As you can see, all of these processes go hand in hand in order to ensure a high level of overall data integrity from start to finish. Make sure that you regularly schedule each of these steps in order to make the best possible use of your data.
Learn more about how to ensure sales data quality and how you can use your data for customer retention, customer acquisition and even in-depth analysis. Just take a look at which functions Microsoft has to offer in these application areas.