Unified data: What is it and why is it important?
Our customers tell us a lot of stories – what problems they solve for customers, how they overcome business challenges, and what they do to better understand their customers. While most senior leaders are quite good at discussing their businesses, they frequently struggle to make their data tell them the stories they need to succeed.
For example, one of our customers is a large, digitally growing enterprise. Their goal was to get a handle on their data, reduce the cost of new customer acquisition, and gain new customers more efficiently. They invested a great deal of time and money innovating in the data space. However, they could not figure out how to make their data work for them, rather than them working for their data.
Their problem wasn’t a lack of information. Quite the opposite; they were, and are, faced with a tsunami of over 250 disparate data sources crashing toward them on a daily basis. Since each of the data sources was in a different format and was not verified, they struggled to make sense of it all, much less make it actionable.
Initially, they did what most companies do: they spent tons of money and time hiring data engineers who spent all day cleaning, validating, and helping the company to understand and utilize their data. As one might imagine, this was very expensive, and they weren’t confident that the data was accurate. So, even though they spent lots of money and resources, they still weren’t sure if they were making smart decisions.
Realizing that this was not sustainable, and since they didn’t want to keep making the same expensive mistakes, they looked for an ETL solution (ETL stands for Extract, Transform, and Load, and will discuss this more thoroughly in our next blog post.) Although they found one, it still didn’t solve their problem, because the data was not unified or normalized, so would show up with errors and challenges.
The solution for them was data unification. Once they unified their data, everything changed. Suddenly, they could make better, more confident data-driven decisions, knowing the data was not just in one format, but accurate and consistent.
This was no easy feat.
They had to normalize and unify – and validate – over 250 marketing channels into a single format.
However, once they got their hands around the data with unification, they were able to optimize their user acquisition strategies, make business-level decisions more easily, and reduce the cost in customer acquisition. Furthermore, they could re-deploy expensive data engineers to engage in more interesting – and profitable – work, well-beyond messing with spreadsheets.
They also gained unique domain expertise of data sets, and can now use their data in every department beyond customer acquisition, including finance, HR, RevOps, and more.
In other words, thanks to data unification, their data is no longer an endless tsunami of chaos or an expensive, time-consuming burden in terms of engineering resources. Instead, it’s a strategic asset that benefits the entire enterprise. It enables them to make smarter, more profitable business decisions at a reduced cost.
So, if you want your data to be an asset rather than a liability, we would suggest starting with data unification. Data unification can produce amazing results for just about any industry, from manufacturing to media to retail and e-commerce, and everything in between.
Unifying your data is the key to making your data work for you, rather than you working for your data.
Be Data Strong!
Read more from our blog HERE
Learn more about ETL here: ETL: The Ultimate Guide.
Learn why an industry-leading digital media platform said, “We had previously invested over eight months of engineering to overcome a data challenge that took Switchboard one month to solve.” Email us to learn more: email@example.com