Data Science in Marketing: Big Data’s Impact on Business – DookyWeb

Data Science in Marketing: Big Data’s Impact on Business

If you take the foundational elements of mathematics, business, and computer science, you enter the world of data science. If you already acknowledge that millions of users provide personal data to Instagram, Facebook, and other social media platforms, you can understand how powerful the data can become.

That’s why it’s important you take advantage of how data science can be coupled with the tools our customer’s use daily. From this data, you can garner both past and real-time information to predict future events. You can even uncover the psychographics, demographics, and behaviors of your users. Master how to use this powerful discipline to boost your marketing strategies.

Whenever a digital product is used, data is created. In fact, the total amount of data created has exceeded 20 zettabytes. This number might have little significance to you, but trust us, it’s a big number.  

What marketers use this data for?

  • Analysis of customer journeys through targeted advertising: have you ever searched for something on the Internet, then find advertisements popping up for products similar to what you searched for? Or recently talked about the product being advertised?
  • Sentiment analysis: this moves beyond simply monitoring the comments of a post, clever marketers can track key insights from conversations straight from the market.
  • Smart segmentation: data science helps group certain movements on cohorts as distinct categories.

For example, Taco Bell used data science to identify the millions of people expressing positive feedback about them on social media. The company used this data to break the audience down into micro-segments. With their findings, they went through what people loved, wanted, craved, and needed from Taco Bell.

Thanks to the help of data science, Taco Bell was able to launch micro-targeted social media ads. Their analysis of behavioral and emotional data brought them:

  • 2.5X higher retweet rate than other Twitter audiences
  • An extended reach of 4X
  • 3.7 million downloads shortly after the launch campaign

Aside from this example. Marketers can use data science to help out with:

  • Dynamic pricing to optimize changing prices
  • Demand forecasting to build predictive models that match demand
  • Churn forecasting to gain insight for what drives users to churn and find out more about the pain points they come across

Study what goes on behind the scenes for how marketers use data science. Master these referenced tips in the infographic below from Clevertap to find out how you can use data science to your advantage.