How Big Data Is Revolutionizing Marketing [4 Major Impacts]

Marketing has seen a recent revolution, led by robots. Fed big data, an algorithm can distill a massive amount of data into an actionable plan. Put another way, it can use customer data-driven insight to form the basis of a tailor-made ad campaign.

A marketing department can then implement the campaign, taking much of the guessing out of the equation. Big data, when used correctly, can be a major boon to a marketing department.

1. Data-Based Prediction

Data collection in the past regarding shopping habits was laborious and time-consuming.

“In the past, companies wishing to track existing customers’ spending habits had to generate that data in-house. Marketing or inventory departments would then use the data to argue for new products, better ad campaigns, or adjustments in production,” writes Maryville University. Now, however, a computer can analyze and generate the data.

Big data, or a large collection of data meant for use in predictive analysis, is currently being used for a number of applications, from developing new products based on what a market is currently using, to granular aspects of marketing, such as figuring out the best way to market to a specific audience.

The data collected, for example, might be online customer behavior analysis. This could include products that capture the customer’s attention, what they are saying about certain products, bounce rate, and demographics.

Wal-Mart, for example, collected data from its website users to better discern user intent. This data was used to upgrade the site’s predictive searching function, which in turn led to a 10-15 percent increase in completed purchases in 2012.

First Tennessee Bank used predictive analysis in a different way: hyper-personalized advertising. It saw a more than 600 percent ROI when they used predictive analytics to target their customers with specific offers.

It’s easy to stay within your marketing budget when you have a massive amount of data backing up your marketing strategy, as you no longer have to make guesses that could turn out incorrect, resulting in a campaign that flops. This provides for maximum ROI.

It’s important to note that the computer is not making decisions, but simply offering up analysis. It parses a given set of data, usually a set that would be daunting for a human, and creates conclusions. It still takes a human to decide how to use the conclusions.

However, that’s not to say that AI in the future might not propose a campaign based on its data, rather than having humans figure out what to do with the data. Now, it gives a starting point, but it could, in theory, develop an entire campaign. It could also provide multiple options for humans to review and choose.

2. Beacons and On-Site Marketing

Beacons are small, location-based electronic transmitters that use Bluetooth to connect mobile devices. For retailers, beacons, combined with big data, provide a massive amount of marketing potential.

The beacons collect tracking data, such as the customer’s footprint in the store, what they are buying, and how frequently they visit an area of the store.

This is a marketing goldmine, as the data can be used to send the customer a coupon for a product they often purchase, a new, similar product that matches their interests, or simply something the algorithm analyzing the data predicts the customer could enjoy.

It’s not all just coupons. Upon entering the store, the beacon can send the customer a personalized greeting or email. If the store has an app, the beacon can push messages through it.

Personalized emails have a click-through rate 14 percent higher than non-personalized emails, increase conversions by 10 percent, and increase eventual transaction rates by six times.

3. Content Marketing

Content, the internet is ready and willing to tell you, is king. The problem comes with providing subpar content that readers do not want and that will not help your marketing campaign.

Instead, the goal is to create important, shareable content that readers will want to interact with. This increases brand awareness and gets people talking about a company.

Content marketing, then, can be tricky to get right, but it’s still extremely important to both a company’s blog and social media presence.

Big data comes into play by analyzing what your customers are reading and interacting with. What else in your niche interests them that your writers could create top-quality content about? Is there a well-known writer that customers tend to read who might make a good guest blogger?

Spying on the competition is also possible by seeing what others in your niche are writing about. An algorithm can analyze topics, figuring out a topic ripe for creating something better than the competition, rather than something complementary.

4. Bigger Does Not Mean Better

Not just any data will do, and the proper data must be provided to produce a conclusion that makes sense.

An article in Computational Biology, a scientific journal, laid out 10 rules for using big data in Research. Part of rule six states: “Being mindful of the data’s context provides the foundation for clarifying when your data and analysis are working and when they are not.

While it is tempting to interpret findings based on big data as a clear outcome, a key step within scientific research is clearly articulating what data or an indicator represent and what they do not.” In short, make sure the conclusion is sensible, and not just confirmation bias.

The writers go on to pose a question that can help you determine if the outcome is what should be expected: “Are your findings as clear-cut if your interpretation of a social media posting switches from a recording of fact to the performance of social identity?

Given the messy, almost organic nature of many datasets derived from social actions, it is fundamental that researchers be sensitive to the potential multiple meanings of data.”

Big data can be used to give marketers a leg up, determining what customers want, what they want to read, or even what type of marketing campaign might work best for the audience.

It vastly improves ROI, making the most of a budget, and provides a large set of data to back up conclusions. However, it must be quality data to achieve a quality result.

A quality result, however, will make your marketing department more efficient and, with a little bit of added luck, increase revenue.

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