The ultimate beginner’s guide to big data marketing
- April 15, 2021
- By Casey Schmidt
As anyone who has worked within a marketing team will tell you, analysis of data has become a staple in maximizing important factors of customer experience. When it comes to big data, the impact is even more crucial.
What is big data marketing?
When it comes to marketing, big data helps organizations by offering valuable insight into their customers and future customers. It also helps businesses understand how to streamline their important workflow processes. Big data helps marketing teams evolve their use of analytics.
Big data impact on marketing
The ability to thoroughly analyze big data is the main difference between companies who are efficient and companies who fail. Big data is in fact recognized as a staple for organizations, especially when it comes to marketing.
When big data is effectively utilized, marketing teams are able to optimize their campaigns, accelerate workflows and boost customer loyalty. Here are some of the biggest ways big data impacts marketing:
- Improved performance through superior understanding. Understanding can apply to many things, but in this instance it is referencing the understanding a marketing team has on its tools, budget and content. With big data analysis, marketers can better assess how successful certain campaigns are and evaluate how to better approach these projects in the future.
- Steadier flow of new customers and clients. Big data offers insights into what types of things are effective in bringing in more customers. This often involves data brought in from technology such as email and website interactions.
- Superior understanding of target market. Lastly, big data provides some of the most innovative, dynamic understandings of their target market. The overall analysis of specific data directly translates to things like enhanced customer experiences.
Different big data types
All data is different, and this holds true for big data as well. Understanding which type is what helps users understand how to extract, analyze and apply different pieces of information. Here are the three different big data types.
Structured, as the name implies, is data that is grouped based on information that is most likely numerical in form. This generally includes addresses, age and payment information. Structured data fits nicely into data maps and outlines that show interconnected information.
Unstructured data is all stored information which is without any organizational form. It’s a large part of the makeup of modern data. The natural state and result of a user’s actions on a computer end up in unstructured form.
Semi-structured data is a hybrid between structured and unstructured data. It’s often data that is mostly unorganized but that has key identifiers and labels alongside it that help keep it recognizable and understandable.
Now that you’re aware of the different types of big data, let’s dive into some real world examples to show big data’s impact on marketing.
5 big data marketing examples
One of the most helpful aspects of big data is it is already being embraced by marketers and successful companies. Because of this, it’s easy to find real life examples of companies using big data.
These types of real world applications give us insight into how successful companies use big data in their marketing processes. Here are five to consider.
We’ll start with Netflix, who is prolific in their attempts to use big data in order to improve crucial factors of their services. Where this is most prevalent, at least to the public eye, is in their data-driven recommendation platform.
This has not only increased the company’s connection with customers, but also saved money and influenced what types of content hits the servers. Look to Netflix when searching for examples of marketing efforts driven by big data that worked.
Similar to Netflix, Amazon uses big data to drive personalization and customer satisfaction. However, Amazon takes a much more comprehensive approach. They have a much wider customer base and different services which require different processes.
As it turns out, quite predictably, Amazon is benefiting greatly from its big data usage, as it is driving a large portion of its sales. Their machine learning also synchronizes with data to maximize the efficacy of things like ratings and reviews for customers.
Kroger uses big data to personalize direct mail coupons to customers. In order to do this correctly, they need data to determine which customers should get which coupons and on which days/times.
One of the most telling results that big data is effective comes from Kruger’s coupon return rate. It’s consistently been outpacing the industry average by over 60%.
4. The Economist
One of the most important things to The Economist is making the best connections possible with their customers. This means that big data is at the top of their priorities, since they needed a deeper understanding into what their customers wanted.
The Economist supplemented their big data management with a customer data platform, finding the most precise marketing offers to serve to customers at the critical moments. This boosted subscription rates drastically.
Airbnb is one of the best success stories when it comes to big data, as they’re a company that structured so much of their processes around gathering key insights from data. The data science they then used increased their marketing efficiency immensely.
Airbnb used big data to understand where the best and worst performances were geographically, and made insightful conclusions based on this data to make helpful adjustments.
Marketers who commit to utilizing big data are bound to see more success in all their different projects and campaigns. The possibilities are truly endless, and the analysis that comes with big data can change the entire outlook of a marketing team.