In this day and age, big data has not only come to dominate boardrooms by fueling business decisions, but now, decision-makers are leveraging predictive analytics based on big data to power business-critical marketing decisions.
This is done by analyzing customer information, be it existing customers or target audiences, at a granular level. The sheer volume of data generated when people interact with websites, smartphones, and apps, allows businesses to analyze a customer’s purchasing history, buying pattern, income, and interests. This, in turn, helps companies to create custom-made digital marketing campaigns for particular demography, resulting in a more targeted approach that ensures maximum impact.
Big data analytics allows marketers to analyze past data of their customers and predict their future behavior online. Although this raises many questions about customer privacy, the data collected and analyzed is mostly anonymous. This type of big data analytics helps brands engage and interact with their customers in a targeted manner.
According to recent studies, big data has three main benefits for driving digital marketing campaigns – a detailed understanding of customer insights, enhancing the 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 analyze data about customers. The data is collected from multiple resources and includes basic information like name, social media handles, email addresses, etc. However, the heart of digital marketing comes in the form of data collected about users’ online activities, which brand they follow on social media, their online activity, how often they purchase particular products, and so on.
In this day and age, the number of devices with which people are interacting is increasing. Gone are the days of simple smartphones, laptops, and tablets. IoT allows consumers to interact with appliances like AI-powered home assistants, connected microwaves, refrigerators, and temperature control systems. Carmakers are pushing to make people’s interaction with their cars completely digital. As the exchange points increase, so does the data collected by these interactions.
Some data sources being used to collect customer data are:
- Web Mining involves collecting unstructured data from websites, including activity logs.
- Social Media – Social Media data such as ‘likes,’ shares and check-in provide valuable insights into a consumer’s behavior.
- Search Data – Search data helps marketers chart their target audience’s web journeys and help plan digital campaigns.
- User Generated – This category includes data from surveys, online communities and forums, and the web in general.
- Transactional data – This type of data is generated when businesses interact with each other and their customers. This includes financial information, buying patterns, and purchase history of the targeted audience. When analyzed, this data gives the buying propensity of the TG and helps conceptualize targeted digital marketing campaigns.
Thinklayer offers Big Data Solutions to help organizations enhance their Business Intelligence and Analytics capabilities, enabling them to find a hidden pattern with data mining and fuel business growth.
