Data science and big data are essential in today’s world of marketing. You’ve probably already seen multiple instances of both being used for advertising and sales purposes, but you may not realize just how useful they are. If you own a business, you need to know how to use data for your own marketing programs.

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What is Big Data?

Big data refers to huge quantities of data that come in from a range of sources. It often comes in multiple formats, and you may need to transform it before you can use it. Companies use big data to help them plan their business and marketing strategies, using insights gleaned from the information collected.

For example, these insights may help you keep track of shopper habits so you can personalize the shopping experience, map roads live with self-driving cars, or refine media streaming. If you drive a Tesla or use a Fitbit, you’re contributing to big data. All the information collected helps companies target their ideal customer with an even more narrow focus while offering customers exactly what they need.

What is Data Science?

Data science is not the data itself, but the tools you can use to find patterns in the data. Data scientists use machine learning, algorithms, and other tools to analyze the information given, and then they use the results to create new processes. Essentially, data science makes big data usable.

Once information is gathered, scientists or machines can sort through it to find hidden patterns and discover what shoppers really want, when buyers are online, and who is ready to make a purchase. While big data comprises this information, data scientists make sense of it all.

Analyzing Data with Data Analytics

Finally, we have data analytics, which differs slightly from data science. It involves actually examining the raw data, coming to conclusions, and then using those conclusions to make decisions. Data analysts inspect, clean, transform and model the data they receive.

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Where Does Big Data Come From?

Big data comes from many places, including social media, scientific reports, real-time data sensors, and customer databases, among others.

How Data Science Helps with Marketing

Data scientists usually work with machine learning or AI. They learn from big data and continue to adjust operations depending on the information they receive. While you might think of data science as being a fairly narrow area of study, it actually touches nearly every aspect of business. Ultimately, data science affects and improves most industries.

Marketers prioritize the use of data and machine learning to craft their ad campaigns. You can track and analyze how your target market behaves so you understand what your clients need. In fact, that’s one of the main reasons companies put up oddly specific ads on social media and search engines.

You can use the information you gather using data science and big data in a variety of ways, including:

Segmenting Customers

You can’t market to everyone and expect to be successful. This is where customer segmentation comes in. You can use the statistics you pull from big data. It’s easy to group customers by specific characteristics so you can target them exclusively with your campaigns. You can group customers by their purchase patterns, touchpoint engagement, or any other relevant factor.

Real-Time Analytics

Thanks to social media and the ability to create real-time algorithms, it’s now possible to look at both customer data and operational data to create a more complete picture. Customer data shows what the customer wants or needs, while operational data illustrates how efficient or cost-effective your marketing campaigns are. Since you're using up-to-date data, you can adjust your campaign as needed based on the current information.

Predictive Analytics

Big data is available to nearly all companies, so it’s easier to determine what the future may hold for your business. This is where AI comes in handy, as it can create a predictive forecast based on the statistics already gathered. The more information available, the more likely the prediction will be accurate.

Conclusion 

The sheer amount of data available in the world is enough to make big data analytics and science of major interest to most businesses. After all, Amazon didn't get to where it is today without analyzing information that came through its customer service database. E-commerce is where it is thanks to digital marketing and the datasets that make it possible to process large amounts of information and metrics. 

And we can only expect to see these methodologies improve in the future. Predictive analytics are getting better, and predictive models for trending business intelligence give us better ideas of how to use them in decision-making. From data mining to artificial intelligence, data science is big business. It’s also changing how we manage our businesses and market our products.

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