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How Big Data is Driving Digital Marketing?

In this day and age, big data has not only come to dominate board rooms, by fueling business decisions, but now, decision makers are leveraging predictive analytics based on big data to power business-critical marketing decisions.

This is being done by analysing customer information, be it existing customers or target audience, at a granular level. The sheer volume of data generated when people interact with websites, smartphones and app, allows businesses to analyse a customer’s purchasing history, buying pattern, income and interests. This in turn helps businesses to create custom-made digital marketing campaigns for a particular demography, resulting in a more targeted approach that ensures maximum impact.

Big data analytics allows marketers to analysepast data of their customers and predict their future behavior online. Although this raises many questions around customer privacy, but the data collected and analysed is anonymous in most cases. This type of big data analytics helps brands engage and interact with their customers in a manner targeted manner.

According to recent studies, there are three main benefits of using big data for driving digital marketing campaigns – a detailed understanding of customer insights, enhancing supply chain and fuelling business promotion and campaigns.

 

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How Big Data is being used for targeting customers online

Brands are leveraging data-as-a-service providers to collate and analyse data about customers. The data is collected from multiple resources and includes some basic information like name, social media handles, email addresses and the likes. However, the heart of digital marketing comes in the form data collected pertaining to online activities of users, which brand they follow on social media, what is their online activity, how often do they purchase particular products, and so on.

In this day and age, number of devices with which people are interacting is increasing. Gone are the days of simple smartphone, laptops and tablets. IoT is allowing consumers to interact with range of devices like AI powered home assistants, connected microwaves, refrigerators, and temperature control systems. Car makers are pushing to make people’s interaction with their cars completely digital. As interaction points increase, so does data collected by these interactions.

Some data sources being used to collect customer data are:

  1. Web Mining – This involves collected unstructured data from websites including activity logs.
  2. Social Media – Social Media data such as ‘likes’, shares and check-in provide a valuable insights into the behavior of a consumer.
  3. Search Data – Search data helps marketers chart out web journeys of their target audience and help plan digital campaigns.
  4. User Generated – This category include data from surveys, online communities and forums, and the web in general.
  5. Transactional data – This type of data is generated when businesses interact with each and with their customers. This includes financial information, buying patterns, purchase history of the targeted audience. This data when analysed gives buying propensity of the TG and helps conceptualize targeted digital marketing campaigns.

Thinklayer offers Big Data Solutions that are helping organizations to enhance their Business Intelligence and Analytics capabilities, enabling them to find hidden pattern with data mining and fuel business growth.

About author

I work for WideInfo and I love writing on my blog every day with huge new information to help my readers. Fashion is my hobby and eating food is my life. Social Media is my blood to connect my family and friends.
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