Data Analytics - The Future of Marketing Analytics

Introduction

The phrase, " Way to a man's heart is through his stomach," if twisted moderately, could be true for a marketer. "Way to a marketer's heart is by providing him a vast amount of data." With a lack of data on consumers, marketing decades ago was done through the spray-and-pray method. Since technological advancements have no boundaries, there's data galore on the customer's buying pattern and their behavior. This helps the marketers target the right set of people for their products which bring in more business.

Perhaps, the catchphrase, "Data is the new oil," sheds light on the importance of mere behavioral data and the browsing pattern of a consumer on the internet. Although the metaphor is inaccurate, it holds that data plays a prominent role in shaping the marketing industry and businesses alike. No business will grow if the targeted audience isn't reached through the archaic methods of advertising. To prevent a business from coming to a standstill, businesses often consider paying for data or the footprints of people on the internet.

What Is The Data That is Analyzed For Marketing Purpose?

To have a reach about a product amongst the general masses, proper research must be done before advertising the same. Through the surveying methods, only a handful of people are willing to provide their insight on the products they are willing to try and the products they use. More often, people presume that the data provided by them could be used against them or for fraudulent transactions. With the fear of being confronted by law enforcement, people tend to lie on a survey.

To get honest opinions from people, the easiest option is to track one's browsing pattern and interests. These are sometimes collected through illegal methods and also through legal methods. The industry giants serving in the IT Sector or the e-commerce websites track their customers and users' browsing patterns and purchase history. The patterns aren't visible to an average joe, and to determine these patterns, the industry giants incorporate an algorithm. These are, namely, Artificial Intelligence and Machine Learning. These algorithms are complex programs that analyze the data collected through the websites and give an insight into the patterns of a consumer. This helps not only the business but also consumers.

One may ask how analyzing the footprints of a consumer helps the consumer. The answer is quite simple, understanding the patterns of a consumer, ads of their interest are displayed on the forefront, and the products that were previously unknown to the consumer yet useful could be purchased by him/her. This doesn’t only help grow a business but also proves beneficial to the consumers.

Artificial Intelligence is the core of analyzing a million gigabytes of data per hour in real-time. The term Artificial Intelligence came into existence in the early 1950s by a group of researchers that included Allen Newell and Herbert A. Simon. They believed that human-like processes could be achieved in a few years. Since then, the AI industry has seen development by leaps and bounds.

Future Of Data Analysis Is Now

Oddly, the future of data analysis does not lie in the future but in the present. With data galore, one can easily analyze it in mere seconds and come to a conclusion as to what could be the right choice for a person. The interests and dislikes are all tracked and fed to the AI algorithms, which spraypaint the best possible interests and alternatives. From the advent of these algorithms, the tech giants have grown exponentially.

In the marketing sector, data analytics plays a crucial role in evaluating and transfiguring raw data into valuable data and drawing conclusions for the business model. For a decade, the data analytics business has spiked the ranks among marketers and proved itself an ultimate tool to develop the best possible marketing strategy.

A throng of people using social media and paving their way through e-commerce websites has pledged an enormous impact on the marketing industry. Advertising through pamphlets and radio bites is done and dusted. Advertising in the new age is done individually by curating a set of products of interest for each individual based on their likes and dislikes. With the help of social media, an individual's browsing history is collected and shared with the partnering businesses to maintain a blockchain of data. The suitable products are advertised individually to the consumers.

With an increase in music streaming services, a person's taste in music can be decoded based on the genre of the songs they listen to most, and suggestions based on the same are displayed. Apart from suggestions, ads to buy products or merchandise related to the artist can also be displayed. For free users, the products are advertised as audio bites in between the songs.

On the contrary, the suggestions displayed on the famous content sharing and viewing websites are based on the videos a person consumes over time. By analyzing the type of content one consumes, suggestions are appropriately generated and displayed on the front page or the suggestions column. An employee's workload is relaxed with the help of previously mentioned algorithms, Artificial Intelligence and Machine Learning.

How Data Analysis Works And Helps A Business Grow

To gain valuable insights into the consumer's purchasing capabilities, the data is collected and analyzed. This data could be the interactions of the consumer with the promotional mail, time spent on a web page that is recorded and contextualized into factual data, and the interactions with the content on a web page. All such data is recorded and collected by big data companies with the help of cloud storage and computing and geo-location tracking technology.

The collected data, when analyzed, doesn't just give an insight into the consumer's purchasing capabilities and the buying patterns, but it also gives an insight into the market trends and shifts. The data can also determine the consumer's buying pattern daily, monthly, or even yearly. Seagate UK estimates 175 zettabytes of data will be created by the year 2025 in the global datasphere. While the World Economic Forum estimated 44 zettabytes of data would be created at the dawn of 2020. The amount of data that is already present in the datasphere is enough to facilitate space for the data analytics market and the marketing industry. Campaigns in coordination with the marketing agencies and businesses yield great profits based on the valuable insights obtained from this data.

The trends in the marketplace can be determined in real-time with ease using the techniques of regular data analytics, which further complements the business to understand the customer's interests and the experiences and the troubles that the businesses could provide support for. For more impactful Business-Business (B2B) or Business-Consumer (B2C) transactions, analyzing the data and interpreting it thereafter provides a deeper comprehension of the type of product most feasible for businesses.

While browsing through the internet, the data is tracked and recorded using cookies. These are third-party cookies that provide the data to the data collecting and analyzing companies which are then processed, streamlined, and shared with various other businesses. This model is profitable for all businesses, such as marketing agencies, analytic data companies as well as businesses that make use of these data for advertising purposes. To let oneself be tracked on the website is voluntary. A pop-up appears where it is asked whether the person wants to accept the cookies or not. If one feels he must not be tracked, he can easily tap the decline button, and no tracking or collection of the data is done.

In the US, industry giants such as Google and internet service providers plan to phase out the third-party cookie system, stripping off the marketers of the wealth of fine-grained data and information. The statement was released by Neil Hoyne, who is a Chief Measurement Strategist at Google.

Companies may begin to collect data using the first-party cookie model and analyze the data themselves. This is obtained by programming complex algorithms, mainly Artificial Intelligence. It is of utmost priority that Artificial Intelligence is regularly reprogrammed and kept a watch on since it can learn to bias between two factors on the opposite spectrum. Amazon scrapped recruiting software that was gender-biased while Twitter shut down Microsoft's chatbox that had learned to post racist tweets on their platform.