Top Three Use Cases of Big Data in Marketing

Over the past few years, big data has proven itself to be much more than a fad. With each passing day, huge amounts data is being gathered in different areas of life, right from improving healthcare outcomes to helping to manage traffic levels in metropolitan areas and, of course, creating marketing campaigns that are far more powerful. In the following post, I would simply like to shed some light on what is the significance of big data in the field of marketing.

In the current scenario, marketers have increased the use of artificial intelligence and machine learning to parse huge amounts of data and to draw conclusions. Moreover, predictive analysis is also used to figure out what customers and prospects are likely to do in the future and to adapt their communication materials as a result of it. Similarly, Netflix has started making use of such data of end users to create more personalized recommendations to its users. After all, big data offers marketers a great opportunity to gain a greater understanding of what people are actually doing on their websites. Due to which companies are able to make personalization easier than ever before. I am sure being a marketer you must be knowing the true importance of personalization especially when you are planning to build genuine connections with your potential customers.

Big data in Marketing

Why every company is inclined towards adopting big data?

Reasons Big Data benefits
Timely Gain instant insights from diverse data sources
Better analytics Improvement of business performance through real-time analytics
Vast amount of data Big data technologies manage huge amounts of data
Insights Can provide better insights with the help of unstructured and semi-structured data
Decision-making Helps mitigate risk and make smart decision by proper risk analysis

According to Gartner, Big data comprises of 3 V’s, i.e. high velocity, high volume and high variety data. Right from public sector services to healthcare, education, insurance, industrialized and natural resources, transportation services, banking sector and fraud detection are some of the industries propelled by big data analytics.

Main use cases for big data in marketing

More targeted advertising

As publishers gather more and more data about their visitors, it will enable them to serve up more and more relevant advertising. Similarly, Google and Facebook have already offered detailed targeting options and third-party vendors will offer the same array of choice. Can you imagine being able to target people based on the articles that they’ve read or based on a lookalike audience of your ideal reader?

Have you ever observed the weather channel? If yes, then you must have understood that it has already given a glimpse of the future of advertising by analyzing the behavior patterns of its digital and mobile users in over three million locations across the globe. Combining the given information with the climate data to give advertisers the opportunity to send super-targeted advertisements. For example, I am sure you will come across many shampoo brands who end up targeting people in humid climates with anti-frizz products.

Semantic Search

For those who have no idea regarding the term, semantic search is a process of searching in natural language terms instead of in the short burst of keywords that we’re more used to. Big data and machine learning make things way easier for search engines to fully understand what a user is searching for, and smart marketers are beginning to incorporate this into their site search functionality to improve the user experience for their visitors.

Walmart can be considered as a famous example, it makes effective use of text analysis, machine learning, and synonym mining to improve the accuracy of their site search. They believe, adding semantic search to their website has increased the conversion rate by 10-15%.

More Relevant Content

Another example of Netflix, it can serve up personalized recommendations. Here publishers are able to offer more relevant kind of content to their visitors by simply tapping into their wealth of data and determining the content which people are most likely to enjoy. In such scenario, even if content marketers are able to get the job, chances are their digital marketers will need to learn to stop thinking of their blog especially in terms of a static site. Now I am sure you must have got different results when you Google the same phrase in different locations? I mean your blog automatically seems to be different depending on who’s looking at it.

This poses a technical challenge. Well, there is nothing new as the field of digital marketing comprises of an array of challenges and it moves at such a pace that those who don’t rise to the challenge will quickly be left behind. So the choice left is consumer will make a decision on your behalf by deciding where to click and what to purchase. And the companies catering such consumers by providing more and more relevant content are the ones that come out on top.

Conclusion

Day by day AI and machine learning are becoming better and better with more and more processing power and more and more data available for them to learn from, it can only get more and more important over time. Meanwhile, there is a plenty of potentials for marketers to take advantage of big data in and nearby future. It’ll be an owned asset that sets one company apart from another.

Nishta Sing

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