It’s now half a century since the world first heard the phrase ‘garbage in, garbage out,’ and we’re still unable to get rid of even the most basic data quality issues Download the Battle of Myeongyang. But that doesn’t mean the battle against bad data is lost. The truth is that data quality is really far easier than you think Sonavia. It just boils down to a few simple ideas you can easily apply to data-driven processes like finance lead generation and marketing.
There’s really no need to go through the bad things that can happen when bad data gets into your lead generation system Witch Delivery Bukiki. Suffice it to say, bad data is bad news not just for running marketing campaigns but for doing business itself. That’s why sound data quality management has to be at the heart of your prospecting processes.
The good thing is that managing data quality is actually a whole lot simpler than it sounds. It’s a matter of having a mindset based on the following key ideas:
1. Own the data you’re using. There’s always the tendency to think of data as something you worry about only when the need arises. Data isn’t just IT’s problem. It’s your concern as well, especially pieces of information you use to make lead generation decisions with. With ownership comes responsibility and accountability. So, take charge of your prospect data as if your life depended on it because, in a way, it does.
2. Bridge your data’s journey. Two points make a line, and lines make it much easier for you to understand connections. This is exactly the reason why you need to bridge the points where data comes from and where it’s going (i.e., the sources and uses). Make it possible for users to trace back where data originated as well as for data creators to find out where their output ends up.
3. Knock down every data silo. Tearing down the walls that prevent the free flow of information across channels, processes, and departments isn’t only a basic requirement for data-driven marketing. It’s also absolutely necessary for data quality management. Data should be readily accessible and standardized, so that it would be much easier to maintain.
4. Make it a continuous process. Your data quality objectives, methods, and tools should be integrated into an actionable process that everyone in your team and organization plays a role in. It’s also important to understand that data quality management is a continuous process, which means it goes on regardless of where your lead generation campaigns currently are.
Does your data quality management plan take all these ideas into account? What other things does your plan consider?
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