Are you tired of constantly having to clean up your Salesforce data? Well, it turns out the problem might not be you. According to a blog post by Validity, the root of the issue could be the lack of a solid data-cleaning strategy put in place by the Salesforce administrator. The post highlights the importance of regularly cleaning up your data to ensure accuracy and prevent any negative impact on your marketing and sales efforts. The article provides several tips for putting a data cleaning strategy in place, including dedicating time and resources, regularly reviewing data quality metrics, and creating a plan for handling duplicates. So, if you’re tired of playing the blame game when it comes to your Salesforce data, it’s time to take a step back and see if the real problem lies with your data-cleaning strategy.
Excerpt from the main article:
Who’s responsible for an organization’s Salesforce data cleansing best practices? The answer isn’t as simple as you think. Luckily, with the right strategy and data cleansing tools, Salesforce data cleanup and maintenance are just a few steps away. Types of data that need cleansing Poor data quality destroys business value. In fact, Gartner research shows organizations believe “dirty data” is responsible for an average of $15 million per year in losses. In today’s business environment, dirty data is created by a variety of sources. It has the potential to cause any number of undesirable outcomes, from inconvenient disruptions in the normal flow of business activities to more disastrous impacts on a company’s revenue or reputation. Dirty data in Salesforce typically falls into one of these categories: Missing data: Empty fields that should contain data. An example would be if an automated billing process broke down because a customer’s billing address