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Advertising is essentially communication.

Have you ever wondered why and how a ‘DailyHunt’ Ad is unveiled to you when your previous Google search was ‘how to stay updated on news.. pls help’?

Does it boggle your mind when you receive a notification on your phone reminding you of a half-way purchase on Amazon that you made on your laptop?

Are you astounded to know that the global advertisement spent in the year 2019 alone ~$550 B?

If yes, pls proceed. If no, I hope you’re now. :) Let’s define the structure of the series first so you know what you’re in for.

This is a series of advertisement tech blog posts focusing on providing structured and exhaustive knowledge on the sector. It delves into the explanation of industry concepts and the products along with the business highlights and metrics. A number of Data Science related action items will also be described in the series. It is broken down into a succession of 5 stories covering the following topics in…


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This post details a model that has been prevalent since the 70s, developed by Fischer Black, Robert Merton, and Myron Scholes and is still widely used today. It is regarded as one of the best ways of determining fair prices of options. The underlying hypothesis is: By placing a certain set of assumptions on the market, the future price of the Options stock can be determined by modeling the movement of stock prices at different time intervals.

The Black–Scholes model is a mathematical model for pricing a derivative contract by simulating the dynamics of a financial market containing derivative financial instruments. The key property of the model is that it shows that an option has a unique price regardless of the risk of the underlying security and its expected return. …


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This is going to be a series of posts or a network/graph of stories, if I may, on Machine Learning in Finance and economy. I believe a profound understanding of the sector where AI is being used is equally important as the models themselves. Therefore, each post would either delve into the finance sector fundamentals or machine learning models.

This is also to consolidate my learnings and understandings of the FinTech sector. Although I’ve always been immensely interested in this field, I never ended up taking a structured course on the same. …


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Is the Ad industry needed at all?

Doing business without advertising is like winking at a girl in the dark. You know what you’re doing but nobody else does. ~Stuart H. Britt

To a lot of us, the advertisements seem more infuriating than any good. Even I’ve on many occasions found myself hovering over the ‘Skip Ad’ button while watching a video.

Why is the industry still thriving then? Let’s back up our hypothesis with some stats. The chart below indicates the global spendings in the whole of the advertising industry. …


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Artificial Intelligence in Adtech

Machine Learning plays an important role in the Adtech sector for efficiency and sophistication it can bring about in the system. The goal of machine learning is to develop methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data or other outcomes. It also gives birth to innovative products that we’ll discuss shortly.

The narrative around data is changing. If big data was once the goal, today the focus is on making data actionable. “Data science is the discipline of making data useful.”

I. Predictive analysis:

Making an analysis of users’ historical transactional data, browsing behavior, etc. to predict the future trend of users. This information places you in a better position to take action in terms of advertising. If you’re dealing with potential customers, for instance, predictive analytics can help you identify customers who most likely intend to transact by using data from existing customers (referred to as “lookalikes”) so you’re not wasting resources on poor prospects. …


AdTech products serve a variety of purposes right from providing technology and the framework for seamless advertisement placement to laying out software solution blankets to carry out the whole operation efficiently and effectively. It also diversifies into creatives of producing marketing content and strategic ads placements. With user privacy taking the pedestal, all the above should also conform to mutating regulations.

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Let’s dig into the details of each product one by one. Let’s borrow Carl, a fictional character from the previous post for the user reference. Say Hello to Carl.

1. Data Onboarding:

Data onboarding is the process of transferring offline data to an online environment for marketing needs. Data onboarding is mainly used to connect offline customer records with online users by matching Personally Identifiable Information (PII) gathered from offline datasets to find the same customers online. …


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Cogs(components) in the wheel (Adtech ecosystem)

There are many cogs in the wheel in the Adtech ecosystem with their indispensable functionalities as depicted in the diagram below. The terms may seem intimidating at first, but you’ll get hang of it slowly. I have also pasted a video link towards the end that’ll put things in perspective.

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*Adtech Ecosystem*. Don’t worry, it’ll make sense as you proceed through the post.

Let’s start with the most basic components, the advertisers, and the publishers. Advertisers can be brands like Starbucks, who want your desperate attention so that you spend your hard-earned money on purchasing their well-thought-of product. …

About

Shreya Jain

Machine Learning | Neural Networks | Probabilistic modelling

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