Why Data Quality Is Crucial For Your Day-to-Day Marketing
You can’t do business if you don’t know your customers well enough. It’s no secret, we all know it. So learning about what your customers really want, need and are willing to spend their money on is...
You can’t do business if you don’t know your customers well enough. It’s no secret, we all know it. So learning about what your customers really want, need and are willing to spend their money on is somewhat of a main priority.
To get the best insights, you need to invest time and resources, especially when it comes to collecting and analyzing the right bits of information. As a marketer, you are likely swamped with tons of data already that, to the best of your knowledge, may be accurate, relevant and insightful. But what if it isn’t - at least not entirely?
Can you really trust all those numbers? How can you be sure that there is no missing or incoherent data? Or what if there are blind spots and you don’t even know where to start looking for them? To be able to fully rely on your data, you need to make sure that you don’t compromise on its quality. After all, you generate and collect data to have a fact-based decision-making process, so you better make sure you have one!
What makes for good quality data?
The thing with marketing data is that, while two pieces of information may look similar or almost identical to the human eye, to a data analytics tool, they may be completely different. Even when they signify one and the same thing.
The most common confusion stems from having various time and date formats, as well as inconsistencies in the spelling of users’ names and addresses. High-quality data makes sure there are no such inconsistencies - and that the insights are accurate, timely and as complete as possible. In other words:
Quality data is consistent. This means that data is stripped of its various formats, cleaned and harmonized and made ready for analysis in a unified form. So, while a date may be originally formatted in three different ways like: 21-Aug-2017, 21-08-2017 and 21/8/2017, an ETL (extract, transform and load) tool can format it down to only one date format to achieve consistency.
Quality data is accurate. Marketing data needs to be collected as close to its original source as possible to avoid it being processed multiple times along the way. The more detailed and specific the data, the more accurate it ends up being.
Quality data is up-to-date. Timeliness is one of the most important characteristics of marketing data nowadays, mainly because of the speed information moves with. Collecting and analyzing data in near-real time is what helps companies respond to their customers’ wants and needs quickly, and what eventually sets them apart from their competition.
Quality data is complete. Or at least as complete as possible. Collecting and analyzing data in its entirety is key to the success of your marketing activities. Any missing information, in turn, would only get you to make decisions based on educated guesses instead of facts.
No missing or incoherent data. When you have the numbers, they need to be correct - or at least you should be notified if there was an error in the loading or transformation process. Making important decisions based on the wrong numbers can hurt, so you should also make sure to not only get but also pay close attention to the error reports.
Achieving good data quality
Making the right business decisions and building strong relationships with your customers is something quality data contributes greatly to. But how do you get to the point where your data is in the necessary quality?
Without a doubt, you’re dealing with more data than ever before. And it’s growing further and further in size. Investing in a sophisticated data analytics tool is, thus, not just a need anymore. It’s a must.
If you are to analyze your data in near-real time, you need to be able to collect it, clean it and analyze it as it is being generated. A next-generation marketing analytics tool, especially one that operates in the cloud, can help you work with increasing amounts of data, stripping it of its various formats, harmonizing it, and making it ready for your analysis.
It is also crucial that the technology you choose can automatically detect possible discrepancies in your data and provide you with an integrated overview of it at any time. Imagine clean, ready-to-use data, with no blanks for you to fill in. As soon as you have that, you can focus on your business’ main objective - to identify and satisfy the exact wants and needs of your customers. After all, isn’t that what marketing is all about?
What tools do you use to ensure the high quality of your marketing data? Feel free to share your thoughts with us in the comments