Advertising

When I first joined Instagram in 2013 or 2014, the first thing that fascinated me about the platform was the quality of advertisements. At that point in time, all advertisements there looked really good, like the pictures that the platform was famous for helping sharing.

It wasn’t like the clunky ads I would see elsewhere on the internet, or even on Facebook – which mostly stuck out like a sore thumb in the middle of whatever content I was consuming at that point in time. Instagram advertisements looked so good that I actually paid them considerable attention (though I hardly clicked on them back then).

Over the years, as Facebook has gotten to know me better (I hardly use Facebook itself nowadays. But I use a lot of Instagram. For now I’ll believe Facebook’s claim that my WhatsApp information is all encrypted and Facebook doesn’t learn much about me through that), and the advertisements have gotten better and more relevant.

Over the last one year or so (mostly after I returned to India) I’ve even started clicking on some of the ads (yes they’ve become that relevant), giving Facebook even more information about myself, and setting off a positive feedback loop that makes the advertisements more relevant to me.

Over the years I’ve attended talks by privacy experts about the privacy challenges of this or that platform. “They’ll get all this information about you”, they say, “and then they can use that to send you targeted advertisements. How bad is that?”. If I think about all the problems with telling too much about myself to anonymous platforms or companies, receiving better targeted advertisements is the least of my worries.

As a consumer, better targeted ads means better information to me. Go back to the fundamentals of advertising – which is to communicate to the customer about the merits of a particular product. We think advertising can be annoying, but advertising is annoying only when the advertisements are not relevant to the target customer. 

When advertisements are well targeted, the customer gets valuable information about products that enables them to make better decisions, and spend their money in a better fashion. The more the information that the advertiser has about the end customer, the better the quality (defined in terms of relevance) the advertisements that can be shown.

This is the “flywheel” (can’t imagine I would actually use this word in a non-ironic sense) that Facebook and affiliated companies operate on – every interaction with Facebook or Instagram gives the company more information about you, and this information can be used to show you better targeted advertisements, which have a higher probability of clicking. Because you are more likely to click on the advertisements, the advertiser can be charged more for showing you the advertisement.

Some advertisers have told me that they elect to not use “too much information” about the customer while targeting their advertisements on Facebook, because this results in a much higher cost per click. However, if they look at it in terms of “cost per relevant click” or “cost per relevant impression”, I’m not sure they would think about it the same way.

Any advertisement shown to someone who is not part of the intended target audience represents wastage. This is true of all forms of advertising – TV, outdoor, print, digital, everything. It is no surprise that Facebook, by helping an advertiser advertise with better (along several axes) information about the customer, and Google, by showing advertisements after a customer’s intent has been established, have pretty much monopolised the online advertising industry in the last few years.

Finally, I was thinking about advertising in the time of adblockers. Thanks to extensive use of ad-blockers (Safari is my primary browser across devices, so ad blocking is effective), most of the digital advertisements I actually see is what I see on Instagram.

Today, some publication tried to block me from reading their article because I had my ad-blocker on. They made a sort of moral pitch that advertising is what supports them, and it’s not fair if I use an ad-blocker.

I think they should turn to banner ads. Yes. You read that right.

To the best of my knowledge, ad blockers work by filtering out links that come from the most popular ad exchanges. Banner ads, which are static and don’t go through any exchange, are impossible to block by ad-blockers. The problem, however, is that they are less targeted and so can have higher wastage.

But that is precisely how advertising in the offline versions of these newspapers works!

Something is better than nothing.

Alchemy

Over the last 4-5 days I kinda immersed myself in finishing Rory Sutherland’s excellent book Alchemy.

It all started with a podcast, with Sutherland being the guest on Russ Roberts’ EconTalk last week. I’d barely listened to half the podcast when I knew that I wanted more of Sutherland, and so immediately bought the book on Kindle. The same evening, I finished my previous book and started reading this.

Sometimes I get a bit concerned that I’m agreeing with an author too much. What made this book “interesting” is that Sutherland is an ad-man and a marketer, and keeps talking down on data and economics, and plays up intuition and “feeling”. In other words, at least as far as professional career and leanings go, he is possibly as far from me as it gets. Yet, I found myself silently nodding in agreement as I went through the book.

If I have to summarise the book in one line I would say, “most decisions are made intuitively or based on feeling. Data and logic are mainly used to rationalise decisions rather than making them”.

And if you think about it, it’s mostly true. For example, you don’t use physics to calculate how much to press down on your car accelerator while driving – you do it essentially by trial and error and using your intuition to gauge the feedback. Similarly, a ball player doesn’t need to know any kinematics or projectile motion to know how to throw or hit or catch a ball.

The other thing that Sutherland repeatedly alludes to is that we tend to try and optimise things that are easy to measure or optimise. Financials are a good example of that. This decade, with the “big data revolution” being followed by the rise of “data science”, the amount of data available to make decisions has been endless, meaning that more and more decisions are being made using data.

The trouble, of course, is availability bias, or what I call as the “keys-under-lamppost bias”. We tend to optimise and make decisions on things that are easily measurable (this set of course is now much larger than it was a decade ago), and now that we know we are making use of more objective stuff, we have irrational confidence in our decisions.

Sutherland talks about barbell strategies, ergodicity, why big data leads to bullshit, why it is important to look for solutions beyond the scope of the immediate domain and the Dunning-Kruger effect. He makes statements such as “I would rather run a business with no mathematicians than with second-rate mathematicians“, which exactly mirrors my opinion of the “data science industry”.

There is absolutely no doubt why I liked the book.

Thinking again, while I said that professionally Sutherland seems as far from me as possible, it’s possibly not so true. While I do use a fair bit of data and economic analysis as part of my consulting work, I find that I make most of my decisions finally on intuition. Data is there to guide me, but the decision-making is always an intuitive process.

In late 2017, when I briefly worked in an ill-fated job in “data science”, I’d made a document about the benefits of combining data analysis with human insight. And if I think about my work, my least favourite work is where I’ve done work with data to help clients make “logical decision” (as Sutherland puts it).

The work I’ve enjoyed the most has been where I’ve used the data and presented it in ways in which my clients and I have noticed patterns, rationalised them and then taken a (intuitive) leap of faith into what the right course of action may be.

And this also means that over time I’ve been moving away from work that involves building models (the output is too “precise” to interest me), and take on more “strategic” stuff where there is a fair amount of intuition riding on top of the data.

Back to the book, I’m so impressed with it that in case I was still living in London, I would have pestered Sutherland to meet me, and then tried to convince him to let me work for him. Even if at the top level it seems like his work and mine are diametrically opposite..

I leave you with my highlights and notes from the book, and this tweet.

Here’s my book, in case you are interested.

 

Instagram targeting

Instagram is really good at what I call “one dimensional psychographic targeting”.

Essentially, based on the photos and videos (more likely hashtags) that you see, spend time on, like and comment, the platform figures out some of your interests and targets at you advertisements of products that serve these interests. And instagram manages to combine this with demographic information (where you live, etc.) to target advertisements better at you.

For example, of late I’ve been looking at a lot of weightlifting stuff on Instagram – I follow most of the coaches at my gym, and a few other handles that post fitness stuff. I’ve even posted a video of myself deadlifting.

As a result, Instagram has been following me with advertisements related to fitness, and the combination with demographics means I’m being served stuff I can get in Bangalore. For example, last two days I’ve been seeing ads of my own gym (!!). There are ads for whey proteins and healthy foods of all kinds as well.

This targeting is not perfect – for the last few months, ever since I returned to India, I’ve been bombarded on Instagram with advertisements asking me to emigrate to Canada (I don’t know what makes it think I want to move abroad again given I’ve just moved back home). The seemingly un-targeted mattress advertisements are everywhere. The shirt advertisements as well (though recently I uploaded a picture of my wardrobe on Instagram).

Nevertheless, this is a massive step up from what marketers were able to do a generation ago, where they could at best target based on a demographic. Marketers might have created elaborate psychographic or behavioural profiles of their target audiences, but when it came to advertising, the media available (newspaper, television and outdoors) meant that they had to collapse it into a demographic profile.

Instagram is not perfect, though. To the best of my knowledge, it can only target me on one “psychographic dimension” (“interested in weight lifting”, “interested in coloured chinos”, “likes Bangalore”) along with a multitude of demographic dimensions (I’m sure it’s figured out my gender, age group and maybe even caste, even if it exists in some vector somewhere and no human knows these classifications).

However, when you have created elaborate psychographic profiles, collapsing them into one dimension is still a simplification process. And so you get a reasonable degree of error in targeting. So I’m wondering what can be done that can enable advertisers to target me with more specific products that I might be interested in.

Finally, really how much are the likes of Charles Tyrwhitt, and some mattress brand whose name I don’t recall, willing to pay for their campaigns, given that their untargeted campaigns have beaten the highly targeted campaigns of the fitness guys and coffee companies to reach my eyeballs?

Mass marketing and objective journalism

This is a fascinating essay by Antonio García Martinez on the history and future of journalism (possibly paywalled). The money paragraph is this:

The bigger switch happened as a national market for consumer goods opened after the Civil War, when purveyors like department stores wanted to reach large urban audiences. Newspapers responded by increasing the number of ads relative to content, and switched to models that went light on the political partisanship in the interest of expanding circulation. This move was driven not exclusively by lofty ideals but also by mercenary greed. And it worked. Newspapers used to make lots of money. Mountains of money.

Basically, the move to objective journalism came in the late 1800s when advertisers such as Macy’s wanted to take out full page ads, and wanted to do so in newspapers that served the largest sections of the market. And when a newspaper had to reach a large section of the market, it inevitably had to tone down the partisanship, and become more objective.

Over the last decade, we have been witnessing (across the world) the decline of objective media. All media is “#paidmedia” based on which side of the political spectrum you stand on. There aren’t that many truly objective papers around, and social media is bombarded left and right by extremely politicised reporting that goes as “news”.

It is perhaps no coincidence that this period has coincided with a time when print circulation has been dropping steadily (in the developed world at least), and where online advertising can be highly targeted.

In theory, mass marketing is inefficient. When you pay to put up a hoarding somewhere, you’re possibly paying a small amount for each person who sees the hoarding, but not all of them might find it interesting. Consequently, this reflects in a depressed per-person price of the hoarding implying the owner of that real estate can’t make as much as she could if the hoarding were to be more “targeted”.

When you can target your advertisements more precisely, everybody wins. You as the marketer know that your advertisement is only being shown to your intended audience. The owner of the real estate where you put your advertisement can thus charge you more for your advertisement. Even the customer will be less pained by the advertisement if it is highly relevant to her.

Another way of seeing it is – an advertisement shown to a customer who doesn’t want to see it is wasted. The monetary cost of this waste are borne by the owner of the real estate and the advertiser, and the non-monetary cost is borne by the customer (being forced to see something she didn’t want to see). And so one of the biggest technological problems of today is on how we can target advertisements better so that we can minimise such costs – and in the last decade and half, we’ve made significant progress on that front.

The problem with greater efficiency, however, is that it comes with the side-effect of biased media. When Nike knows that it can precisely target an advertisement at American leftwingers, it makes an ad with Colin Kaepernick and shows them to American leftwingers to sell them more shoes.

This doesn’t however, mean that Nike only sells to left-wingers. The same company can make another advertisement targeted precisely at right-wingers and use it to sell shoes to them!

So now that you can make left-wing and right-wing ads, and you have the ability to target them, you want to cut the waste and place the ads so that you can target as best as possible. In other words, you want to place your left-wing ads in places that only left-wingers want to see, and right-wing ads only in places that right-wingers will see. And so you prefer to advertise in CNN and Fox rather than in a hypothetical “broad market” media outlet.

And the reason you created the politically charged ads in the first place was because there were some outlets (Facebook, for example) where you could precisely target people based on their political orientation. And so you see the vicious cycle – that you can target in some places means you want other places where you can target and that creates demand for more polarised media.

It was the opposite cycle that took effect in the late 1800s and early 1900s. There was no way brands could target (also, when you make physical advertisements, with 1900s technology, each advertisement is costly and you don’t want to make one per segment) too effectively, and so they went mass market in their communication.

And this meant advertising in the outlets that could get them the maximum number of eyeballs. When you can’t discriminate between a “right” and a “wrong” eyeball, you pay based on the number of eyeballs. And the way for media organisations to grow then was to cater to everyone. Which meant less less bias and more objectivity and more “features”.

Sadly that cycle is now behind us.

The finiteness of the global advertising market

In this excellent post on social media companies, Aswath Damodaran articulates something I’ve long wondered – about the finiteness of the global advertising market. Given the number of companies that come up with new mechanisms to match advertisers with consumers, one can be forgiven for believing that the market for advertising is infinite. That the more avenues you create for serving advertisements to people, the more the advertising that will flow, and there won’t be a let up anywhere.

This picture here is from Damodaran’s blog (which I recommend you subscribe to, since every single post is worth reading). Based on the numbers that Damodaran presents here, the overall growth of the worldwide advertising market seems rather low.

Source: Aswath Damodaran (http://aswathdamodaran.blogspot.in/2014/11/twitters-bar-mitzvah-is-social-media.html). All numbers in billions of dollars

The number to take away for me from this calculation is the shrinking pie of non-digital advertising. Based on these numbers, the total non-digital advertising market in 2008 was $468 billion. In 2014, going by the same numbers this is down to $400 billion. This de-growth is significant and holds important lessons for other sectors that are dependent on advertising.

So far, the flow of advertising capital has been taken for granted and the number of business plans made (in both old and new economies) with an assumption on advertising growth is endless. If you want your local bus utility to make more money, you rent out advertising space on buses. If a low-cost airline wants to make more money, they put advertisements on the back of seats (a very good idea since it gets undivided attention for the duration of the flight). It is a surprise that insides of toilet stall doors (which again get undivided attention) haven’t fallen prey to advertisements yet.

The point here is that while it is all well and good to plan businesses based on advertising income, what we need to keep in mind is that the advertising pie in the long term grows at the same rate as the global economy. Sooner or later the waters will recede to the natural level, and then we will know who is swimming naked!