ONLINE ADVERTISING AND CONTRIBUTION OF ARTIFICIAL INTELLIGENCE
Introduction:
Online advertising can be referred to as the promotion of goods and services over the internet to the target customers. In the year 2016 it was estimated that 3.5 Billion of the world’s population which roughly translates to 45% of the world’s population has access to the internet , with China leading the pack. With continuous development in the area of Machine learning, Artificial Intelligence (AI) and data science technologies online advertising continues to get sophisticated with time. This study was carried out to understand the procedure to carry out an online advertising and the impact of AI and in online advertising.
Objectives of the study:
To study important types of Online advertising
To understand the procedure and cost involved in online advertisement
Impact of AI in online advertisement with reference to NETFLIX
Chapter 1: Eight popular forms of online advertising:
Display Advertising
Display advertisement is a paid form of advertising. Frequently used forms of display ads are banners, landing pages (LP’s) and pop ups. Unlike other advertisements these advertisements do not show up under Display search results.
Most commonly found on websites and blogs their purpose is to redirect user’s attention to the company’s product. Working together with remarketing display advertisements are very successful. According to Digital information world, “website visitors who are re-targeted with display ads are 70% more likely to convert on your website.”
Search Engine Marketing & Optimization (SEM) & (SEO)
SEM and SEO promote content and increase visibility of the advertisement through searches.
SEM: In this type of advertising the payment for the advertisement is decided based upon the number of times an individual clicks the advertisement than for the actual advertisement. These advertisements appear on the search engine results page. The business usually pays the search engine in order to display the advertisement in their search engine result page (SERPs). The relevance of the ads displayed in the results page are based on the key words used in the search engine by the individuals alongside the results for the queries.
SEO: It is the combinations of techniques used to promote a web site to the top of the search engine results based on algorithms and other organic techniques like linking etc. Without involving payment to the search engine provider.
Native Advertising
Native advertising is a form of paid advertising, these ads blend into the media format in which they appear. They are often found in social media feeds or recommended content. The key feature of Native ads is that they are non-disruptive as they look as a part of the web page unlike banner ads or display ads which are easily recognized as advertisements by individuals.
Pay Per Click (PPC)
As the name suggests, the cost of these advertisements is based on the number of individuals who click on the ads and not based on the number of times the ads was seen or appeared to the individuals. Even if 100 individuals have seen the ad but only one person clicked it the cost revolves around the one click only. These ads generally carry an attractive tagline and an Image. It is worth noting that 64.6% of people click on Google ads when they are looking to make an online purchase.
Re-marketing
Re-marketing (or re-targeting) is a type of online advertising that brings the ad around the individuals multiple times. In this technology the site drops an anonymous browser cookie and literally follows the user around the internet and sends information to the re-marketing service provider on when the individual can be re-targeted. Statistics show that only 2% of web traffic brings positive results on the first visit, which means 98% of users leave without converting right away.
Affiliate Marketing
It is a form of advertising where the product of a company is promoted by affiliates targeting the same customer group. It works on a commission basis for every product sold by the marketing effort of affiliates of the seller. This form of advertisement is popular among bloggers and other individuals who have a significant number of followers who are looking forward to making a passive income.
Chapter 2 – Procedure and cost involved in online advertisement:
Advertising on Facebook – Fb ads manager:
Advertising on Facebook is managed through Facebook business. The ads can be created and managed through Facebook business which gives various details about the performance of the advertisement and cost incurred. Facebook business allows the user to classify the advertisement on the basis of categories as follows:
– Awareness
Brand Awareness – Increases awareness by reaching people who might be interested
Reach – Making sure the advertisement is seen by maximum number of people
-Consideration
Traffic – Maximum visit to the target website of page
Engagement – To get more people to engage with the ads through likes and shares
App installs
Video views
Lead generation – Drives sales through collection of e-mail ids of interested parties
Messages – Boosts conversation through messenger
-Conversion
Conversions – Drive valuable actions in websites and through messenger
Catalog sales – Ads based on the products in the add publishers product catalog
Store visits – Promotes people to visit the brick-and-Mortar stores
Budget and Bid:
Budget can be daily budget – Cost fixed on a daily basis and Lifetime budget which will be utilized for the entire lifetime of the campaign.
Bid: Every ad displayed in Facebook is a result of the ad winning an auction to win its spot. The advertisement is valuated on the basin of:
Cost – The cost paid for the ad
Relevance – The relevance of the ad to the target
Estimated action rate o the ad publisher
Facebook follows country based pricing and the average cost of an “cost per click (CPC)” ad is Rs 0.52 and Rs 2.30 and average cost per 1000 impressions is Rs 9.30 with a minimum budget of Rs 40 per day.
Advertising on YouTube:
There are four categories of ads in YouTube with an average cost of Rs 0.70 to Rs 17 per click or per view and it depends on the quality and popularity of the video in which the ad will be displayed or played.
In-search ads – Advertisement appears above the YouTube search results
In-slate ads – Advertisement appears in the suggested videos after your video ended
In-display ads –Advertisement appears on the suggested videos beside the video you are watching
In-stream ads – Advertisement plays before you can watch your video
Steps involved in YouTube advertising:
1. Google AdWords Account creation:
Primary step is to create a Google Adwords account which helps in creating and managing the advertisement campaign and the budget. Google Adwords is an online platform that users Pay to display various forms of advertisements within the Google ad network to the web users.
2. Link AdWords and YouTube
AdWords and YouTube accounts should be linked together. It can be accomplished from the navigation menu by clicking “Linked YouTube accounts” in Google Adwords page.
3. General Settings
In this step the desired budget per day is fixed. It is recommended to start small and scale up. No payment is made to Google unless the viewer watches the ads all the way through. There is also more customization that can be allotted for bidding for the advanced advertisers.
4. Set the Locations for the Ad to Show Up
This deals with the selection of countries, cities, regions, IP addresses, etc, going as broad or as specific as the marketer would like. The more specific, the better qualified viewers will be targeted. To build brand awareness, being broader in selection might be helpful.
5. Upload Your Video
Next step involves the selection of the video that has to be showcased. The video to be showcased is uploaded to Google Adwords account from YouTube. Therefore, in order to showcase the advertisement the video has to be first uploaded to YouTube.
6. Advanced Settings
This steps allows the marketer to choose what days/time of the day the ads are to be shows and if there is a specific time to showcase the ads because a prospect is more likely to be compelled by the product, and the start and end date for your new ads.
7. Device Targeting
Through this option one can choose specific devices they want to target, whether it be mobile, desktop, laptop, tablets, etc. One should select the devices based on what the target viewers might use when searching for the product advertised.
8. Selection of demographics, topics & More
Here the marketer selects age, gender, and narrows down on what topics the ads should be shown. Better results can be expected on being more specific in these selections..
Being more specific with categories, words, websites, interests, and phrases the ads are to be shown, the audience will be better targeted.
9. Choosing Keywords
The Google Keyword Tool can be used to find relevant terms and specific keywords that the potential customers will use in searching for on YouTube. These keywords help in targeting the right individuals more efficiently and get as specific as possible. These terms are from Google’s search engine, not from YouTube. They can still be useful in cutting down on some of the keywords that could cause the ad to be viewed by the wrong person.
The longer the keyword, the more specific it is, and the more pertinent it will be to the business in capturing the right viewers.
Chapter 3: Impact of AI in online market with reference to NETFLIX:
Netflix began in the year 2007 offering video-streaming of its content to its subscribers. The company capitalized on the shift of viewers from regular cable television shows to media contests online. This move was accepted across the subscribers, technology enthusiasts and wall street analysts alike.
Netflix conducted a contest “Netflix grand prize” in 2009 and offered a reward of USD 1,000,000 for the best algorithm for predictive analysis of the viewers rating for a movie based on past ratings. During this stage there was a limitation on the level of data available about the viewers for the analysis. Apart from Cust ID, Movie ID, past ratings and the date and time the movie was watched there was no other data compiled.
With the launch of streaming as the primary mode of delivery there was scope for many other data points to generate date including but not limited to the time and date on which the movies were watched, time spent on selection of movies and the number of the times the playback was stopped and the causes for the pause and its effect on the viewers experience based on the ratings. Using these data Netflix has built models the differentiate their customers based on many scales and provides them with best offers and suggestions to customize their enterprise behavior to become more customer -centric in their approach.
Use of Big data and Analytic in Netflix:
Predictive viewing habits:
The core of the efforts made by Netflix is to provide its customers with the best set of movies they might enjoy streaming. Netflex has employed people called “taggers” who are requested to watch the upcoming content and flag them into various categories based on the elements in the movie. Based on this input from the taggers Netflix brings up the list of suggestions to watch other productions which were tagged similar to those which were enjoyed by the viewers in the past. Netflix have created around 80,000 new “micro-genres” of movies based on the viewing habits.
Netflix records the following data as well:
When the viewers pause, rewind or fast forward
The relationship between the day and the content screened
The date and time
Area from which the streaming takes place
Device used for screening
Pausing and non-resuming of content
Ratings of the content
Keywords used in search
Browsing and scrolling behavior and others
They use these data for predictive analysis of customer behavior and help in maintaining a healthy CRM relationship.
Moving from content distributor to content creator:
This shift of Netflix towards content creation was also based on the extensive data analytic. Netflix identified that the subscribers had a very strong preference towards the content directed by David Fincher and starring Kevin Spacey. Netflix bagged the rights for House of cards after outbidding HBO and ABC. They banked on this production to be the “Perfect TV show” based on their predictive model and they immediately launched two seasons of 26 episodes.
The scale on which Netflix would want to see their customers improve is the time spent by the consumers in streaming the content. This aspect of suggestion of content demonstrates the customer-centric approach followed by Netflix.
Quality of experience:
Netflix monitors the quality of experience of the viewers and its effect on the behavior of the user. The primary aim is to reduce the lag in streaming the consumer’s experience. From the physical location of the users Netflix measures how the viewing experience can be optimized through placement of data. Information on the causes of delay, whether it is due to buffering and/or bit rate. The use of Big data and analysis have helped Netflix to position themselves as the leader of the pack. Netflex follows the approach of various other distributors and production networks combined with innovation and efficient handling of data.
Defining future plan of action:
The CRM practices of Netflix is highly dependent on the insights collected from their customers coupled with innovative techniques and Analysis CRM to improve their business.
The other area in which Netflix outperforms is tn optimization of marketing campaigns. They target the customers based on the time spent by them across various electronic devices. It is done through the time spent streaming Netflix through various devices. Based on this information they perform ad campaigns that will return the highest ROI for Netflix. Netflix has a minimum of 80% success rate compared to 30% to 40% for other networks. These ads are set up using various data mining tools and building complicated algorithms to identify the behavior of the customer and the likelihood of them attracted to the content offered to increase the success rate.
Conclusion:
Online advertising is constantly growing in a steady phase and more so the technology involved in placing these ads in various online platforms and targeting the right set of audience remains the key factor to increase the success rate of any form of advertisement. In order to achieve optimization of ad placements development in technology especially in the area Machine learning and AI has been proved to be a tremendous advantage to the marketers. Hence, the marketers should constantly incorporate the best strategy based on their marketing objective to derive best results from their ad campaigns across various online platforms.
References:
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