Do I Need a Data Lake? Are You Data-Driven and Data-Science Driven? Then, Yes.
Reaching marketing nirvana has long been described as the ability to tie together every interaction with a consumer back to the individual and ensure perfectly curated content across every channel and touch point. Sounds easy, right? Well, the reality is that this is not really possible nor necessary. There are regulations to protect consumer privacy and differences in channels and data, never mind the fact that not every brand interaction is trackable to a household or individual—traditional out-of-home, I’m looking at you.
Just because marketing nirvana is unachievable doesn’t mean you shouldn’t invest in the tools needed to help you tie together as many disparate consumer touch points as possible. Enter the data lake. Just as with a DMP (data management platform), brands are constantly asking me, ”do I need a data lake?” And, similar to my answer to the DMP question, it depends.
What is a Data Lake?
Before jumping into whether a brand needs one or not, let’s define what a data lake is. A data lake is an analytic and big-data environment that allows you to bring together multiple facets of data—known, anonymous, structured and unstructured—with the goal of driving richer, more predictive analytics and ultimately a better understanding of the consumer. Eckerson Group did a survey in 2018, in partnership with Alliance Data, and found that nearly three-quarters (72 percent) of respondents felt the data lake they use “fosters better decisions and actions by business users.” It’s a tool that provides insights to drive marketing, product and offering development, customer satisfaction, in-store optimization, and website engagement, to name a few.
Should I Invest in a Data Lake?
Having an analytic capability like this available can be very powerful, and it almost seems like a no-brainer that brands want to invest in a data lake. But realistically, it takes the right people beyond marketing (in IT and data science) to be able to build, use, and extract value from a data lake. It also takes expertise to sort through necessary privacy and data ethics considerations. Without the right people resources, you’re making large-scale technology investments without the internal structure to make it worthwhile.
This comes with a rather large caveat. Data lakes run the risk of becoming a data dumping ground. Forrester estimates that 60–73% of all enterprise data goes unused for analytics. In a rush to pull together data, data lakes have become swamps of undefined data from a variety of sources.
At the end of the day, it always comes back to what you are trying to solve for as a marketer. Data lakes can be powerful tools that provide insights to drive growth within your brand beyond marketing. Determine how you will tie business outcomes to a data lake investment. They can also sit unused or underutilized. The choice is yours.
In my next blog post, I will provide a list of questions that will help marketers evaluate the need for a data lake, so they can take the time to truly assess organizational needs and goals before making the investment. Make sure you’re leveraging the power of your data to achieve your marketing goals. Know your Mar Tech acronyms to better determine what best fits your needs.