The Downfall of Programmatic Advertising?

So is programmatic advertising dying as some people say? In my opinion, no. Do I think there is a learning curve? Yes. A thousand times yes. Like most anything to do with digital these days, there is a steep learning curve, but does that degrade it? I don't think so.

Like most major companies are saying (i.e. Forbes, Digiday, CNBC, TTG Media, etc.) there are going to be bumps in the road, but advertisers and marketers need to learn from those hiccups and move forward, perfecting strategy, and implementing those strategies for their clients. If marketers are more thorough, and advertisers are more inquisitive, I think there will be a harmony found between them.

References: https://digiday.com/marketing/complexity-bad-ad-placements/
http://www.bbc.com/news/uk-politics-39301712
https://www.forbes.com/sites/forbesagencycouncil/2017/06/01/the-death-of-op-eds-declaring-programmatic-advertising-dead-hopefully/#3a7773b64e02
https://digiday.com/marketing/programmatic-101-marketers-turn-vendors-ad-tech-lessons/
http://www.cnbc.com/2017/05/18/programmatic-ad-buying-grossly-flawed-ana.html
https://www.ttgmedia.com/news/technology/how-can-brands-find-a-safe-place-to-advertise-online-10364
https://digiday.com/marketing/marketers-programmatic-summit/

What is Programmatic Advertising?

To answer the question to my previous post, "Why is my advertisement there?" The answer is: Programmatic Advertising? Heard of it? Probably. Understand it? I didn't. So I did a little digging.

Programmatic Advertising is an algorithm based automated auction platform that sells and buys advertisements and places them in the winning spaces online. Programmatic advertising isn't new, but it is growing every year. In a Forbes article, " Adweek recently reported that programmatic digital display ads now account for 80% of U.S. display spending — not bad for a platform we're constantly told is on the brink of extinction. "  Why is programmatic advertising going extinct? Surely you've heard about the YouTube crisis. Advertisements ending up next to terrorist enthusiasts, and YouTuber's like Pewdiepie, who most people are still on the fence about.

This kind of upheaval is not new, and is bound to happen with programmatic advertising growth. YouTube has been working on settling the nerves of its advertisers that have pulled from the platform, while others are just assuring clients that things are just fine, it's all part of the process. So why all of the "Call an end to Programmatic Buying!"? Well, as the old saying goes, "People fear what they don't understand." or something like that.

When a poll was taken to see how many marketers understood programmatic advertising, most people stared back blankly. The issue doesn't seem to be with the overall algorithm, but rather the people picking the data they are using to sell their advertisements via programmatic advertising.

According to an article in Digiday.com:

"The ongoing trend of brands taking more control over programmatic has driven the demand for such educational programs. Marketers don’t have enough ad tech expertise to train people themselves, so they are turning to tech vendors to fill the void with programmatic training. As a result, the likes of Adobe, Google and digital marketing company Quantcast are all increasingly investing in educational efforts to bring clients up to speed."

When a client doesn't understand what they are buying and marketers don't fully understand what they are selling, of course there are going to be discrepancies, and of course there are going to be mistakes in placement. Because of this, it is important to understand what you are selling if you are a marketer and important to know and understand what you are buying, if you are an advertiser.

References:
https://digiday.com/marketing/complexity-bad-ad-placements/
https://www.forbes.com/sites/forbesagencycouncil/2017/06/01/the-death-of-op-eds-declaring-programmatic-advertising-dead-hopefully/#3a7773b64e02
https://www.ttgmedia.com/news/technology/how-can-brands-find-a-safe-place-to-advertise-online-10364

Where Is My Advertisement? and Other Mishaps in Digital Marketing

"My advertisement is where?" you hear on the other end of your voicemail. Everything was going well, but now you're getting complaints. Of course, we've all seen the mishaps of traditional marketing:

http://www.express.co.uk/news/weird/576064/Ad-disaster-fails-39-funniest-marketing-mishaps (5 of 32)

This advertisement looks like it came out of an intro of Bob's Burgers (not a bad thing if that is what they were going for). 

http://www.express.co.uk/news/weird/576064/Ad-disaster-fails-39-funniest-marketing-mishaps (14 of 32)

Just like traditional advertisements, digital advertisements can also be placed in not so ideal spaces. Let's say you are looking at an obituary online and you see an advertisement for sliced deli meat (True Story). Not exactly appropriate. 

So how exactly does this happen? And what happens with the advertiser when it happens? Stay tuned for more!

The More You Know...

During this week, I have learned a lot about Netflix and analytics in general, and I hope that any readers also found value in the topic.

As a newbie to digital marketing, and because I am just now learning things about the analytics side of marketing, I was very thrown to find just how much of my dappling in psychology and science were involved in the process of analytics. Even more shocking, and unfortunate (just kidding "math lovers"), was to discover that math played such a huge role in putting together the experiments that Netflix was executing, and to interpret that data.

GIF: pandawhale.com

And while I swore back in high school that I was done with math, I dappled in it again in my undergraduate ventures in statistics, which I enjoyed, but shhh.... don't tell anyone. I have pushed this slightly unsettling dilemma into the back of my mind, so I could pursue the clichéd version of the English major, but now that I have been out in the world, I'm embracing the fact that I may be geeking out a little over the statistics aspect of marketing, the tables, the graphs, the numbers (breathes heavily). All of it.

Not only that, digital marketing also includes something I am passionate about: psychology. It is very comforting to find that my knack for reading people and always wanting to know "why" "why is this person saying/reacting/thinking the way that they are?" is a useful trait.

I guess what I'm saying is, I am starting to enjoy this.

PHOTO: Know Your Meme

The One With A/B Testing

In my last post, I introduced a little bit of what Netflix does with their data, but this data is mostly just surface data, not big picture data. In reality, Netflix uses a lot of different types of testing and algorithms to determine what new features they should launch for their audiences, what new shows, and how Netflix is presented in general.

Netflix has a large membership, over 81.5M members (techblog.netflix.com), so when they receive data and try to sort through it, it can be a little nerve-wracking. How do you figure out what the users want? How do you get them to stay with a certain show? How do you track whether or not what you are doing is working? The answer seems to be A/B testing. 

"In marketing and business intelligence, A/B testing is a term for a randomized experiment with two variants, A and B, which are the control and variation in the controlled experiment.^[1] A/B testing is a form of statistical hypothesis testing with two variants leading to the technical term, two-sample hypothesis testing, used in the field of statistics." - Wikipedia.com (A/B Testing).

So how does this work with Netflix?

Netflix uses A/B testing to determine when and how to proceed with new features or setups on Netflix. For example, on Netflix's techblog, "www.techblog.netflix.com" they discuss the data they received by changing the covers of titles they have on the search lists. By changing the fonts and background images for the title an releasing those versions to some viewers, but keeping the titles the same for others, they discovered something interesting.

Photo: http://techblog.netflix.com/search/label/algorithms

Viewers were more inclined to watch and stay on the titles that had more expressive facial expressions in the title rather than just body motions or poses.

Coming to this conclusion took more than just one experiment process, however, it took at least three versions of this experiment to get to this conclusion.
1) Experiment 1 - Single Title Test with Multiple Test Cells:  This was the beginning of their journey to finding more successful artwork. They tested out different versions of one title, and kept a control group. There was a huge positive response to the change in title covers.
2) Experiment 2 - Multi-Cell Explore Exploit Test: They started mixing blockbuster titles and small industry titles to see if they had the same effect as the first experiment. There were also more rules and criteria for this project.
3) Experiment 3 - Single Cell Title Explore Test

Netflix launches over 200 tests per year (business.financialpost.com) to keep updating and improving their business. One of their newest projects is updating their rating system from a 5 star rating to a thumbs up/thumbs down rating. The reason? Their results showed it was skewed to mostly a positive outcome for their titles, with no ratings or very minimal ratings for shows they were not impressed with.

While what Netflix is doing could probably have an entire blog dedicated to their news, for the purposes of this blog, this will do for now. Keep on doing you Netflix, and we will be there for you.

Sources:
https://www.infoq.com/news/2017/03/netflix-big-data-analytics
http://business.financialpost.com/fp-tech-desk/personal-tech/data-is-mothers-milk-to-netflix-as-it-tweaks-algorithms-to-find-that-perfect-content-just-like-a-dating-app
http://techblog.netflix.com/search/label/algorithms

Netflix: Who is Watching Whom?

Ah, Netflix. The haven of series binge-watching, the holy grail of shows and movies galore! Netflix has given and yet we want more shows. And you know what? Netflix does too; want data on those shows.
So how does Netflix access all of this data and apply it to their business and ultimately our streaming devices?

In the blog, "The World in Digital Eye" there are a couple of articles that also delve into that question.

"Instead of choosing 8 TV shows and streaming them to the Internet for free, Ted  [Ted Sarandos] and his team used the data to analyze the viewers, subscribers, ratings or the watching record and so on. Ted and his team then use the data to reveal discover all these small things that belong to the public, like what is the kind of shows the subscribers are looking for, how are the producers or the actors the subscribers are interested in." - "Data Analysis in TV Series"

Ted Sarandos is the executive manager of content at Netflix, and he uses the basic algorithms that Netflix has set up to decipher what viewers are wanting to see, how often they see the content, and how they choose content.

While it seems like Netflix just gains insight and data from how audiences view content, other experts at Netflix explain that it is much more complex than that. Tom Gianos, a senior software engineer at Netflix, and Dan Weeks, an engineering manager for Big Data Compute at Netflix explain this during QCon San Francisco 2016.

In the next few posts, I will delve deeper into the algorithm and analytic side of Netflix, and just how they decide how you view your favorite shows.... and binge away!

Movement to Digital for Local News

We've talked about how publishing needs to be going digital and the benefits, but has anyone successfully done this yet? In the book publishing industry, the news on movement is very dry, but in the aspect of local newspapers, it is not so stagnant.

A local newspaper in Norway, Amedia, has managed to create a successful business model that moves to digital only products for its members. The Norwegian publisher launched in 2014 and has created a three step model to turn print subscribers into digital only subscribers.

http://www.niemanlab.org/2017/05/heres-how-this-norwegian-publisher-built-a-successful-digital-subscription-model-for-local-news/

http://www.niemanlab.org/2017/05/heres-how-this-norwegian-publisher-built-a-successful-digital-subscription-model-for-local-news/

http://www.niemanlab.org/2017/05/heres-how-this-norwegian-publisher-built-a-successful-digital-subscription-model-for-local-news/

With this model Amedia has gained over 130,000 subscribers and it is still growing. Compare this to Gannet (a UK and U.S. newspaper) that just hit 250,000 subscribers recently. 

Maybe this could be something that other local papers could look into to broaden their audience and eventually create revenue? 

Publishing, Big Data, and What That All Means

Publishers, amongst other print companies, have all been running into the same issue over the past few years; decline in readership and loyalty to their brand. As everyone knows, the world of marketing is becoming more and more digital every day. Despite this, there has been a significant push against a complete overtaking of digital aspects in the publishing industry.

However, publishing is finally beginning to change. With the growing popularity of e-books, author presence on social media, and potential consumers mostly gathering their information and advertising online, the Publishing Industry is starting to move towards the digital era.

Ayesha Salim addresses this in her article, "Brands vs publishers: Who's winning with data?"

"But publishers are facing their own battles. With print advertising on the decline, publishers are taking drastic steps to revamp their digital strategy to attract readers."

Publishers are ready to make the move, because traditional marketing is starting to fail them to attract the reader base they desperately need. How are they going to do this? By focusing on big data and using the advice of marketing analytics resources. And while most brands do not know how to use the data they are given, or don't put much stock in that data (Brands vs Publishers), Publishers are showing that slow and steady can indeed win the race. While others are delving into big data, head first, but with no clear direction, publishers are being more strategic with their process, and in the long run, I think it will benefit the industry.

"A study by publishing solutions provider Ixxus found that publishers are immensely feeling the pressure of digitalisation in terms of revamping their business models and are focusing on targeted content and predictive analytics. But while they struggle to monetize their content, according to Parse.ly’s findings, when it comes to data, 52% of publishers feel more confident using it compared to 45% of brands." - Ayesha Salim

 Despite understanding the use of the data that they are finding, publishers are still struggling to make a profit for their content. This could be that they are not interpreting the data in an efficient way or maybe are not planning their marketing strategies based off that data in a bold enough way. One brand, however, seems to have the right idea:

Speaking on The Telegraph’s data strategy, Carr says: “The Telegraph does something really interesting. They tag all their premium content so that their editors and reporters can understand how a subscribed audience is reading content versus the non-subscribed audience. Then they can make decisions based off not just what's popular, but what are their most loyal readers doing.” - Ayesha Salim

This type of strategy seems like a better strategy than most newspaper/magazines are doing, which is making readers pay for content that they can get for free in most industries, or are focusing too much on getting subscriptions for their content. To do this, they are relying more on traditional advertising, and in this current market, it is just not cutting it.

When it comes to data, one thing that some publishers are working towards is Reader Insights Data. Anders Breinholst discusses this in his article "Big Data is Coming to the Publishing Industry":

"So what kind of RID could prove valuable to publishers? Even the most basic data points can be surprisingly helpful. These include finishing rate, reading time and reader demographics, as well as other books readers are consuming. This data will not only help publishers make better suggestions for improvements to their authors, but more importantly, it will help publishers successfully sell book rights in new markets."

 So what does this all mean for the future of publishing and marketing? Publishing is realizing that it needs to adapt faster to the ever changing environment of digital marketing and analytics, so hopefully there will be a significant change in the way the publishing industry gathers and markets its data for customer retention. Hopefully delving more into the digital aspect of marketing will improve readership and will make a better strategy for the publishing and for books.

http://www.digitalbookworld.com/2016/big-data-coming-publishing-industry/
http://www.thedrum.com/news/2017/04/03/brands-versus-publishers-who-s-winning-with-data

Introduction

Now that I have your attention. I believe introductions are in order.

My name is Kyla, which, as an after-effect I should have probably picked a pseudonym for this particular project, but it seems a little late for that now... 

The purpose of this blog is to help others, as well as myself, become more informed of Marketing Analytics, of which I currently know nothing about. Some of the major focuses for the next 10 weeks will be: Status and Future of of Big Data in Publishing, Data Analytics Tools, and Data Visualization and Reporting. 

One area that I am particularly interested in is Publishing. I will use this blog to delve deeper into the publishing industry and to see if and how they are using Big Data, and for what marketing purposes.

To get up to date on current trends in Marketing Analytics, I did what any wise person would do; I Googled. However, I didn't just willy nilly Google just anything in Marketing Analytics, I Googled the leaders of Marketing Analytics, and am currently following these pioneers in analytics on Twitter. 

Updated list to come.