What Are the Limitations of Big Data for Marketers?

Julia Sellman
Marketing in the Age of Digital
3 min readApr 16, 2021


Based on my research, there are a variety of limitations to “Big Data” for marketers. According to Ciklum.com, Big Data analytics is “the process of drawing from large sets of data.” This set of data being referred to is a ginormous sea of data that needs to be sifted through and sorted constantly. There are many revelations that can come from that huge data pile, or the data may mean nothing at all to a marketer. It all depends on the depth of your analysis and on what you’re looking for in your research. Some of the many limitations are as follows….

1. Finding Meaningful Correlations in Data
The pool of data that you work with as a marketer is so large, it is sometimes difficult to sift through. There can be many correlations you may make between different variables in your data. However, making these correlations, doesn’t always mean anything significant. It is possible that the relationships between variables are insignificant. This process can be a waste of time and effort, or can be very worthy. The important part of this process is figuring out where in your correlations there is actually causation and where there isn’t.

2. Figuring out Which Questions to be Asking
The data you’re working with can lead to a slew of assumptions and “answers,” but it is imperative to make sure you’re asking the right questions and answering them with your findings. Even though you might be finding “answers,” you need to make sure they answer questions consistent with your business goal. You might discover important data, but it may not be helpful in answering the question you’re looking for that will help you achieve your goals.

3. Security of Data
“Big data analytics is prone to data breach” (Ciklum). Information and inferences you come up with and pass along to others could easily get leaked to customers and competitors. This creates additional limitations because data needs to have additional layers of security, which leads to the next point of transferability of data.

4. Transferability of Data
Usually only people with specialized skills and knowledge can efficiently reach Big Data and use it, because it needs to be secured with firewalls or private clouds. Therefore, it may be difficult to transfer and use data between multiple teams and consistently keep up with analysis. For example, if you’re working on a huge initiative that involves a lot of time allotment and you find a huge discovery, it might be difficult to track data that confirms your discovery. There is such a tremendous amount of data and it may be difficult to get to it, so consistent research endeavors are often a difficult task.

5. Discrepancies in Data Collection
Tools used to collect big data might not be 100% effective. There is so much data and so many different ways to collect it, collection could get complicated. In addition, many data collection programs used in present day tend to change the results of their searches day to day, which can skew results and ultimately even change them. Therefore, correlations and analysis of data could change frequently due to changing data patterns.

A Final Limitation in the Data
In addition to these limitations in the physical data itself, there are also limitations to the use of computers and machines to analyze the data. The reality is that computers are becoming increasingly capable of performing human-like activities and analysis. However, no matter how advanced computers get, they’ll never actually be humans. Their insights will likely never be able to incorporate experience into their assumptions. Marketers need experiences of life like “strik[ing] our in little league, hav[ing] their heart broken, see[ing] their children born or know[ing] many of the joys and sorrow that make life worth living” to find a passion point and create a phenomenal campaign (Forbes). Marketers need to be a part of the process to connect to people and continue to reach them in a meaningful way.