By: Brad Koyak from Spectre Graphics
Before we talk about what big data is, we have to talk about data collection. Since the early nineties, companies have recognized the importance of knowing who is visiting their website. Early on in the life of the internet companies would parse through their server log measure their online traffic (Shiu, 2020). Today, companies use more advanced methods consisting of tracking pixels, cookies, and other methods.
Okay so What is Big Data?
Big data is a term used to describe a large quantity of information. A very large quantity of information. Pretend you have to survey 100 people. It’d be easy enough to write down each answer and note the most popular ones by hand. However, if you had to ask 1,000 or 10,00 or 10 million people then it would take the rest of your life to compile the answers. Dealing with big data has become a large part of advertising, sales, and digital marketing.
According to Gray (1996), there were only 623 websites at the close of 1993. Today there are roughly 286 million internet users in the US alone (Johnson, 2021). There’s no way even a small website can look at each person’s information individually. We’ve got to use software to help.
Parts of Big Data
Working with big data requires a solution to these three common problems (Big Data, 2021):
Volume referrers both to the amount of information but also the physical storage requirements of a large amount of information. According to Litman (2020), “The world is creating, capturing, and consuming about 40 Zettabytes of data.” This amount of information is simply impractical to keep on normal computers. Companies have to figure out where to store their big data.
Big data requires a system that can hold a lot of information. It also needs a system that can take in and store data quickly. If a system can work with 1 item a second that equates to 31.6 million records a year. A system that can work with 10 data points per second can parse 316 million records a year. It’s simple, the faster your solution can manage the data, the better.
The best system is one flexible enough to manage information of different types. Text, video, audio, email, financial transactions, etc are vastly different types of data. Whenever possible a good system should be able to manage disparate types of information.
How is Big Data Used in Marketing?
Big data is the biggest game-changing innovation for marketing since the invention of the phone or the Internet. For marketers, big data is the result of new techniques used in the digital landscape. Marketers are most interested in these categories.
Marketers have always worked with behavioral and transactional metrics. We collect information about customers from surveys, points of sale, advertising campaigns, websites, social media, online communities, and lots of other places. This information is the backbone of creating new products and improving customer satisfaction.
Retailers use big data to analyze buying trends. They also use customer purchases as suggestions for up sales or future purchases. The characteristics of the individual consumer are used to determine what he/she might be purchasing next. Then they send appropriate advertisements to influence their future shopping.
In addition to customer data, marketers are interested in metrics on the marketing process itself. Differentiating pricing strategies at the customer-product level and optimizing pricing using Big Data are becoming more and more achievable.
Finally, metrics related to finances are extremely important to marketers. Sales revenue, profits, and similar data points are crucial to determining the success or failure of marketing efforts.
How Big a Deal is Big Data?
Big Data is changing how companies establish greater customer insights and achieve greater customer responsiveness.
The marketing strategy in many companies is growing fast. Existing systems today have to evolve with the needs of customers, sales, services, and marketing channels. As a result, many marketing plans aren’t completely integrated at the data and process levels. To alleviate this problem, big data analytics is used for creating scalable systems of Insight. Supported by Big Data and its affiliated technologies, it is now possible to embed intelligence into contextual marketing (DeAngelis, 2017).
How are Companies Using Big Data?
Being able to collect information and identify trends can help to mitigate issues even before they occur. Big data can help a company prevent fraud, manage credit risks, or reduce customer and employee attrition. It can also help determine timelines for growth and expansion.
Customer analytics dominate big data use in sales and marketing departments. Companies can use demographics and behavior patterns and gain insight through some important metrics (Goodworklabs, 2017).
- Consumer acquisition costs
- Customer retention costs
- Lifetime value
- Customer satisfaction and happiness
- Average purchase amounts and behavior
Stores such as Amazon and Wish modify their website to individually fit each user. Items that are shown on the “recommended for you” pages change as the user navigates through the site. They use algorithms based on big data trends to personalize the products shown to the user. Some brands even use dynamic pricing to adjust the cost of products for individual users. You can read more on this in our article on targeted display advertising.
Netflix has been a dream for television programmers. They can collect information about who watches what show, how long they watch a show for, what time of day they watch, etc. Because of profiles, they are even able to determine how different age groups interact with the service. Netflix uses this information to create new shows to appeal to their customer base and to advertise shows as well. Netflix has also been planning artificial intelligence powered trailers where each user would get an ad created on the fly just for them. Check out more about programmatic video in our article.
Generating revenue, reducing costs, and reducing capital are three core areas where Big Data is delivering business value. An enterprises’ value drivers scale more efficiently when managed using advanced analytics and Big Data.
Big Data Take Away
Big Data doesn’t just give massive buying power to larger corporations. It can also be used to optimize the smaller budgets of Small to Medium Businesses. This means the mom and pops can use consumer information to target their budgets directly toward their target audience. If you have followed my digital marketing series, Big Data is at the heart of every digital marketing platform available.
However, as Uncle Ben always said, “With great power comes great responsibility.” As with any disruptive technology, the lines between ethical and overreach are blurred. In my next blog, we will take a direct look at Ethics in Big Data and how the United States Congress is addressing it.
Bibby, C., Gordon, J., Schuler, G., & Stein, E. (2021, March 24). The big reset: Data-driven marketing in the next normal. Retrieved April 05, 2021, from https://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/the-big-reset-data-driven-marketing-in-the-next-normal
Big data: What it is and why it matters. (2021). Retrieved from https://www.sas.com/en_us/insights/big-data/what-is-big-data.html
DeAngelis, S. (2017). Targeted marketing in the age of cognitive computing. Retrieved from https://www.linkedin.com/pulse/targeted-marketing-age-cognitive-computing-stephen-deangelis
Gray, M. (1996). Web growth summary. Retrieved from https://stuff.mit.edu/people/mkgray/net/web-growth-summary.html
GoodWorkLabs (2017). How Data Analytics Can Help Marketers Understand Consumer Behavior. Retrieved from https://www.goodworklabs.com/how-data-analytics-can-help-marketers-understand-consumer-behavior/
Johnson, J. (2021, January 27). U.S: Number of internet users. Retrieved from https://www.statista.com/statistics/325645/usa-number-of-internet-users/
Litman, D. (2020, February 27). The big data explosion (and why new storage solutions are Needed now!). Retrieved from https://galaxycapitalpartners.com/the-big-data-explosion-and-why-new-storage-solutions-are-needed-now/
Shiu, Alicia. (2020, October 07). The early days of web analytics. Retrieved from https://blog.amplitude.com/the-early-days-of-web-analytics
Sumits, A. (2015, September 01). The history and future of internet traffic. Retrieved from https://blogs.cisco.com/sp/the-history-and-future-of-internet-traffic
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