Looking for Salesforce data management best practices? The truth is developing a great strategy for managing your data starts with understanding what not to do. Keeping data clean and organized is difficult but with the right knowledge, you can avoid pitfalls and put plans in place to make data management simple. Ready to master Salesforce data management? Keep reading to learn about 7 Salesforce data management mistakes you should avoid.
No quality standards
All Salesforce admins know that there’s good data and bad data. However, to keep the bad data out of your organization you need to make sure that everyone knows what bad data means to you. This doesn’t look the same for every business.
To achieve this, you can apply rules to your database to automatically fix this issue in some cases. However, the concern doesn’t stop here. Once you’ve defined what good and bad data is for you, share that information and make it clear to everyone on your team. When this isn’t a point of confusion, it’s much easier to enforce a Salesforce data management strategy.
Not utilizing accessible data
It’s easy to fall into the trap of focusing on collecting data, instead of using the data that you already have. However, to manage data well, you have to think about how you can put data to good use and how you can maximize your efforts.
Salesforce recommends the following:
“Start small and don’t underestimate the data you can use today. There’s always room to grow with data in Contact Builder. For example, if you regularly collect a customer’s mailing address, you can use the ZIP code to target customers by location. Behavioral data is another rich source of data you can use to target your customers. This information includes how customers browse on your website, open your emails, or purchase products.” Bottom line: Use the data you have before you think about growth.
Nothing will make data management more difficult than holding on to a bunch of data you don’t need. To avoid this, think about what information is really critical to your organization. Then only keep that data and ditch the rest. Less is more in this case. Keeping too much data only makes it more difficult to manage information effectively. So, determine what data you need and then develop a process that makes it easy to collect only that information.
Confusing naming conventions
Many people believe that naming conventions are developers’ responsibilities. However, in many cases, this isn’t true. Often administrators will have to determine naming conventions for field reports, custom objects and more. Things can quickly become confusing without guidelines in place.
To help your team understand your naming conventions, you should keep everything predictable. This isn’t the time to get creative and make people guess what the name of a field actually means. You want to leave little room for error here. You also want to make sure to always include descriptions for each field. This way, even if your naming conventions are clear and consistent, there’s always extra information available to eliminate possible confusion.
Your Salesforce data management strategy won’t get you far if you’re the only one who understands it. It’s important to communicate with your team about your strategy and make sure that there’s proper documentation to educate them and train them on these practices. It’s best if you keep this documentation in a place where you can update it in real-time. Then, as things in your organization change you can be sure that everyone on your team has access to up-to-date processes.
No Salesforce backup strategy
The time you put into creating a great Salesforce data management strategy can quickly go to waste in the event of data loss. To avoid this, it’s important to also have a backup and recovery strategy to protect all your Salesforce data.
The truth is that the weekly backups that can be done with Salesforce aren’t enough for most organizations. Even worse, the recovery fee comes with a huge price tag. The good news? Using a third-party solution, backing up and recovering data can happen in just a few clicks. You can be confident that your data is secure and that your organization won’t feel the impact of catastrophic data loss.
Not cleaning data regularly
Even the best teams will need to take a closer look at their data every once in a while. As we mentioned in a previous post, dirty data is a serious problem that can wreak havoc on your organization. If you aren’t auditing and cleaning your data regularly you may not catch issues that could cause serious headaches down the line. Much like defining your process for only keeping critical data, you should define a process for cleaning data too.
There are several things that you can implement to make keeping data clean a breeze. Third-party tools can help you identify and merge duplicate records so that you don’t have to dig them up manually. There are also tools that can help you analyze your data health and data quality. This can help you uncover data that isn’t useful to you and help you evolve your data collection process to avoid more “dirty data” in the future.
Have you made any of these Salesforce data management mistakes? If so, we hope that this post has helped you identify best practices that you can start using in your organization today. Managing data can be tricky, but understanding how to keep your data clean and secure before the problem grows is key. Creating a data management process takes work but it’s well worth it. Once you have these rules and systems in place, Salesforce data management becomes a lot easier for your entire organization.