Advertisement Tech — Introduction
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 detail:
I. Adtech. Evolution. Hype.
II. Adtech legacy ecosystem. Components and concepts.
I. Adtech. Evolution. Hype.
Adtech? What’s the hype?
Advertising Technology (AdTech) is defined as a range of software and tools that brands and agencies use to strategize, set up, and manage their digital advertising activities.
From a technical standpoint, these are the major steps:
Handling Big Data on a large scale.Targeting ads based on user relevance and insights obtained from the data.Performance measurement and analytics on the ad campaigns to assess market feedback.Ad deliveries across various channels to advertise on multiple platforms including websites, apps, etc
The hype around this industry:
Let’s discuss them one by one:
The Adtech industry deals with data on a colossal scale right from unstructured search logs of users to highly sophisticated transaction data. Because no data is bad data. Big infrastructures have been set around ingestion, cleaning, and maintaining sanity around this data. With global standards, GDPR, and CCPA guidelines coming into play, more emphasis has been given to user privacy, which requires logical segregation of data. The entire process consumes tremendous space and computational resources to keep up with the guidelines. Many companies have spun out and are earning profits by just maintaining this gigantic scale of data securely.
This industry affects more than 60% of the current world population just in the form of audiences. Not to take into account the people working in this sector, ranging from brands that want to advertise, technology upkeep, and the websites that show up advertisements.
The complex operating procedure right from picking fitting users for a specific use-case to actually displaying advertisements to them in real-time requires high availability of systems. The effectiveness of targeting relevant users in the run-time is made possible with the existence of high bandwidth network servers. The systems need to be made available both from the demand-side, i.e., the readiness of online users from the advertisers’ side, and also from the inventory supply side, where the ads are published.
In order to choose relevant audiences for targeting advertisements, many Machine Learning models and heuristics are applied. Even the bid amount to be paid for every ad space has models running in the background in real-time. Another useful application can be the detection of fraudulent customer data. We’ll see more applications of Machine learning in one of the upcoming sections.
The majority of the revenues for big giants like Google, Facebook is obtained through advertisements directly or indirectly. This revenue generation stream is so widespread and easy to operate that an individual content writer or a YouTuber can also easily get onto the bandwagon. Apart from revenue generation, the existence of this industry in place has helped the globalization of brands digitally and effectively. Many blogposts with extremely informational pieces are able to continue sharing their learnings because of this industry.
Evolution of the sector:
The digital advertising industry has been around since the 90s. Below is the pictorial representation of the significant changes that helped shape the industry as we see it now. It consolidates the major events in the Adtech sector from the 90s until the late 2000s.
The existence of cookies to track user behavior as a proxy has been around since 1994 and is still used for trailing user history for better advertisement targeting. This has also prompted various agencies to focus on users’ privacy and impose global regulations to safeguard the same. With every passing year, we hear about more stringent policies being put in place, like GDPR, CCPA, etc. to name a few, to protect privacy infringement.
The need for efficiency and relevance of advertisements in this industry started cropping up in the early 2000s when publishers’ websites got bombarded with pop-up advertisements.
To uplift more relevant advertisements, Google Adwords came into existence in the year 2001, where advertisers with the higher scores made it to the top on the Google search webpage. The scores are a mixture of a bunch of things, one of which is the relevance of keywords(from the ad) with the search query a user has typed.
For the publishers out there, who have their websites, Google found a way to display its ads onto the empty website space through AdSense. Google AdSense is a program run by Google through which website publishers in the Google Network serve text, images, video, or interactive media advertisements for the online audience.
With both the demand(advertisers) and the supply side (website owners, publishers) growing at tremendous rates, there arose a need to pipeline this ecosystem through a channel where fair bidding and relevant advertising can materialize in real-time. To put an end to these liquidity issues, a technology platform called an ad exchange was invented in the year 2005 that facilitated and still does, the buying and selling of media advertising inventory from multiple ad networks. The underlying idea is similar to that of a stock exchange, where stocks are traded at even higher unimaginable rates between the buyers and the sellers.
The ad ecosystem gradually was taking a definite shape with each component having a specific and important role to play. We shall discuss more on these components in the next blogpost. Each of these pieces has immense revenue generation opportunities, the potential of which was soon realized by big companies like Google, Facebook, Yahoo which started throwing money in this sector and building their business models around this source of revenue. The functions range from providing the platforms for advertising, being a facilitator in the ecosystem to providing the relevant users for targeted advertising.
What has happened in the last decade?
The underlying advertising legacy still remains the same as mentioned above. The more recent changes have either made the systems more efficient and effective. The points below highlight the areas where the Advertisement industry has seen newer trends in the last decade.
- Programmatic Ad buying: Programmatic pertains to the use of technology and data to automate and streamline online media’s transaction process. With the introduction of programmatic buying, publishers, and advertisers don’t have to sit across the table to discuss and negotiate the contract. Ad buying is done through algorithms.
a) Programmatic Direct: Programmatic direct is a method of programmatic media buying. Programmatic direct is a digital replication of the traditional media buying process where advertisers strike a one-to-one deal with publishers to display their ads.
b) Real-time bidding: RTB involves advertisers bidding on ad inventory in real-time through an ad exchange by means of newer, faster and more efficient algorithms. It’s a feasible method for publishers as they can now sell unsold inventory without actively getting involved in the process. Although publishers may not get premium value from RTB, they still get a fair deal as the bids are determined based on demand for the ad inventory.
- Don’t worry if it doesn’t make as much sense now. It’ll be taken up in another post in detail.
2. Type of display ads: More types of advertisements based on context have begun to surface, leading the way for types like expandable banners, 360 degrees display ads.
3. Consolidation of niche offerings: Giant corporations are acquiring promising independent companies in their respective niches to strengthen and scale their offerings. For instance, recent acquisition of Looker, a data exploration and discovery business intelligence platform by Google.
4. More transparency: GDPR enforces the privacy and transparency aspect on end-users’ part by making it mandatory for publishers to disclose how their data is used and reinstates the power in the hands of users through the eight rights for individuals.
Advertisers are tracking the placement of their ads and how each ad is contributing toward revenue generation. Similarly, publishers are keen to understand how users navigate through their websites, interact with ads, and how much revenue the website is generating for advertisers.
5. New Ad Channels: Smart TVs and over-the-top OTT platforms such as Netflix, Hulu, Amazon Prime, HBO Now, and Roku have amassed an enormous user base. While OTT video service is just one of the new channels, advertisers are also evaluating the potential of direct-to-customer (DTC) brands and digital out-of-home (DOOH) to expand their advertising efforts.
Technologies to look forward to in the upcoming years for Digital Marketing and Advertising:
- Blockchain for advertising — blockchain provides opportunities to deal with fraud, lack of transparency, privacy, and barriers to open competition within the advertising supply chain.
- Artificial intelligence for marketing — Although it’s already deeply intertwined in the sector, impacting multiple facets in the industry, a lot more magic needs to be witnessed on the lines of analysis of human behavior.
- Real-time marketing — Acting on users’ online activities in real-time to monetize on short-lived intents by streamlining the buyer journey and get them to purchase quickly.
- Customer Data Platform — CDP is a marketing system that unifies an organization’s customer data from marketing and other channels to enable customer modeling and optimize the timing and targeting of messages and offers.
The article beautifully highlights future trends and expectations in detail.
The next post is about the Adtech legacy ecosystem. Describing components and concepts in detail. The indispensable functionalities that they provide in the Adtech ecosystem.
References:
- https://www.discovery.org/v/evolution-bacteria-to-beethoven/
- https://www.gartner.com/en/marketing/insights/articles/6-technologies-on-gartner-hype-cycle-for-digital-marketing-and-advertising-2019
- https://www.slideshare.net/clearcode/the-history-of-advertising-technology
- https://east.vc/east-ventures/advertising-tech-indonesia/
