External membership of unions

The ostensible reason for the violent crackdown on protesting students at Alighar Muslim University and Jamia Millia Islamia last month was the involvement of “outsiders” in these protests. In both cases, campus authorities claimed that student protestors had been joined by “outsiders” who had gone violent, which forced them to call in the cops.

And then the cops did what cops do – making the protest more violent and increasing the damage all round, both physically and otherwise.

I’m reminded of this case from a few years ago from some automobile company – possibly Maruti. The company had refused to recognise an employee’s union at a new plant they were starting, because of an argument on the membership of non-employees in the unions.

The unions’ argument in that case was that external (non-employee) membership was necessary to provide the organisational and union skills to the union. If I remember correctly, they wanted one third of the union to consist of members who were not employees of the firm. The firm contended that they wouldn’t want to negotiate with outsiders, and so they wouldn’t recognise the union with external members.

I don’t remember how that story played out but this issue of external membership of unions, whether student or employees, is pertinent.

At the fundamental level, unions need to exist because of the balance of power – the dominance in favour of an institution over an individual employee or student is too great to always produce rational outcomes in the short term (in the long term it evens out, but you know what Keynes is supposed to have said). The formation of unions corrects this imbalance since the collection of employees or students can have significant bargaining power vis-a-vis the institution, and negotiations can result in more rational decisions in the short term.

The problem I have is with external membership of unions. The problem there is that external members (who usually provide leadership and “organisation” to the unions) lack skin in the game, and the union’s incentives need not always be aligned with the incentives of the employees or students.

Consider, for example, the protests in the universities last month which became violent. The incentive of the protests would have been to peacefully protest (to register their dissatisfaction with a recent law), and then get back to their business of being students. The students themselves have no incentive to be violent and damage stuff in their own institution, since that will negatively impact their own futures and studies at the institution.

External members of the unions don’t share this incentive – their incentive is in making the union activities (the protest in this case) more impactful. And if the protest creates damage, that can make it more impactful. The external members don’t particularly care about damage to the institution (physical and otherwise), as long as the union’s show of strength is successful.

It is similar in organisations. It is in the interest of both the employees and the management that the company does well, since that means a larger pie that can be split among them. The reason employees organise themselves, and sometimes go on limited strikes, is to ensure that they get what they think is a fair share of the pie.

The problem, of course, is that negotiations aren’t that simple, and they frequently break down. The question is about what to do when that inevitably happens. Each employee has his own threshold in terms of how long to strike, and at what point it makes sense to back down and accept the deal on the table.

In an employee-only union, the average view of the employees (effectively) guides when the strike gets called off and the negotiations end. External members of the union lack skin in the game, and they have a really long threshold on when to back down from the strike. And this makes strikes longer than employees want them to be, which can make the strikes counterproductive for the employees.

One infamous example is of the textile mills in Mumbai in the late 70s, and early 80s. There was massive union action there in those times, with strikes going on for months together. Ultimately the mills packed up and relocated to Gujarat and other places. The employees were the ultimate losers there, either losing their jobs or having to move to another city. If the employees themselves had controlled the union it is likely that they might have come to a settlement sooner or later, and managed to keep their jobs.

In the automobile case I mentioned earlier, if I remember correctly, the union demanded that up to 33% of the membership of the union be comprised of outsiders – a demand the company flatly refused to entertain. Now think about it – if external members control a third of the union, all it takes is one fourth of the employees, acting in concert with the union, for something to happen. And there is a real agency problem there!

Big Data and Fast Frugal Trees

In his excellent podcast episode with EconTalk’s Russ Roberts, psychologist Gerd Gigerenzer introduces the concept of “fast and frugal trees“. When someone needs to make decisions quickly, Gigerenzer says, they don’t take into account a large number of factors, but instead rely on a small set of thumb rules.

The podcast itself is based on Gigerenzer’s 2009 book Gut Feelings. Based on how awesome the podcast was, I read the book, but found that it didn’t offer too much more than what the podcast itself had to offer.

Coming back to fast and frugal trees..

In recent times, ever since “big data” became a “thing” in the early 2010s, it is popular for companies to tout the complexity of their decision algorithms, and machine learning systems. An easy way for companies to display this complexity is to talk about the number of variables they take into account while making a decision.

For example, you can have “fin-tech” lenders who claim to use “thousands of data points” on their prospective customers’ histories to determine whether to give out a loan. A similar number of data points is used to evaluate resumes and determine if a candidate should be called for an interview.

With cheap data storage and compute power, it has become rather fashionable to “use all the data available” and build complex machine learning models (which aren’t that complex to build) for decisions that were earlier made by humans. The problem with this is that this can sometimes result in over-fitting (system learning something that it shouldn’t be learning) which can lead to disastrous predictive power.

In his podcast, Gigerenzer talks about fast and frugal trees, and says that humans in general don’t use too many data points to make their decisions. Instead, for each decision, they build a quick “fast and frugal tree” and make their decision based on their gut feelings about a small number of data points. What data points to use is determined primarily based on their experience (not cow-like experience), and can vary by person and situation.

The advantage of fast and frugal trees is that the model is simple, and so has little scope for overfitting. Moreover, as the name describes, the decision process is rather “fast”, and you don’t have to collect all possible data points before you make a decision. The problem with productionising the fast and frugal tree, however, is that each user’s decision making process is different, and about how we can learn that decision making process to make the most optimal decisions at a personalised level.

How you can learn someone’s decision-making process (when you’ve assumed it’s a fast and frugal tree) is not trivial, but if you can figure it out, then you can build significantly superior recommender systems.

If you’re Netflix, for example, you might figure that someone makes their movie choices based only on age of movie and its IMDB score. So their screen is customised to show just these two parameters. Someone else might be making their decisions based on who the lead actors are, and they need to be shown that information along with the recommendations.

Another book I read recently was Todd Rose’s The End of Average. The book makes the powerful point that nobody really is average, especially when you’re looking a large number of dimensions, so designing for average means you’re designing for nobody.

I imagine that is one reason why a lot of recommender systems (Netflix or Amazon or Tinder) fail is that they model for the average, building one massive machine learning system, rather than learning each person’s fast and frugal tree.

The latter isn’t easy, but if it can be done, it can result in a significantly superior user experience!

What Makes The Athletic Great

In recent times I’ve bought subscriptions to two online media outlets – The Ken and The Athletic. I’d subscribed to the Ken a year ago, and was happy enough with the hit rate of their pieces (I’d find one in two pieces insightful) that I extended my subscription for three years earlier this year.

And since I did that extension, the product has been disappointing. They lost half their team to The Morning Context, a breakaway (and similar) outlet. They decided to expand in South East Asia, and since I have little interest in articles about that reason (at least not enough to pay for the writing), that automatically means less content that interest me. In some senses their quality is slipping. All this together means that I find less than one in five articles in The Ken compelling, and with the frequency of their publication (one article every weekday) I’m pretty disappointed.

Maybe it has to do with Marie Kondo’s popularity, or interest in behavioural economics research about the paradox of choice, but organisations are starting to make minimalism and limitations in inventory a virtue. The Ken started with the aim of “exactly one long form article every day”.

Having less choice, and being minimalistic, is good when this limited choice fits the appetite of the customer. However, if the choice isn’t particularly relevant, then minimalism becomes a bug rather than a feature – the customer doesn’t find what she is looking for and goes on to another outlet.

In that sense, I quite like the model of The Athletic, which I bought a year-long subscription to a year back. The Athletic’s model is just the opposite – massively high volumes with a highly curated personal feed. And maybe they’ve got their curation right, in terms of getting customers to click on the right kind of tags at the time of sign up, but so far I’ve found at least two useful articles on their site every single day since I turned up. And that’s insane value for money!

And that is despite me being interested in exactly one out of the nine sports that The Athletic covers (it’s mostly US-centric, and I don’t follow American sport at all. However I guess I’ll find it useful when I have to follow any controversy in American sport). And I’m interested in a subset of that – I follow one league (English Premier League) and games played by a handful of clubs in that league.

If I compare The Athletic to Netflix (both subscription-driven media outlets with large volumes of content), where the former scores is in its discoverability.

Maybe sport is easier compared to movies/tv shows in order to understand someone’s interests. Maybe it is that The Athletic, right up front, asked me to identify which sports, leagues, authors and teams I’m interested in (Netflix never made an attempt to do that). Maybe it is that The Athletic, with loads of fresh content every single day, is able to serve my preferences far easier than Netflix.

In any case, reading the Athletic makes me think that if I were to run a media outlet some day, I would want to follow that kind of a model – produce lots of content, so that lots of people will be interested in buying subscriptions, and then hope to use superior algorithms to make sure that people can see what they want and not have to cut through too much noise in order to do so!

Schelling segregation on High Streets

We’ve spoken about Thomas Schelling’s segregation model here before. The basic idea is this – people move houses if not enough people like them live around them. A simple rule is – if at least 3 of your 8 neighbours around you aren’t like you, you move.

And Schelling’s insight was that even such a simple rule – that you only need more than a third of neighbours like yourself  to stay in your place, when applied system wide, can quickly result in near-complete segregation.

I had done a quick simulation of Schelling’s model a few years back, and here is a picture from that

Of late I’ve started noticing this in retail as well. The operative phrase in the previous sentence is “I’ve started noticing”, for I think there is nothing new about this phenomenon.

Essentially retail outlets want to be located close to other stores that belong to the same category, or at least the same segment. One piece of rationale here is spillovers – someone who comes to a Louis Philippe store, upon not finding what they want, might want to hop over to the Arrow store next door. And then to the Woodland store across the road to buy shoes. And so on.

When a store is located with stores selling stuff targeted at a disjoint market, this spillover is lost.

And then there is the branding issue. A store that is located along with more downmarket stores risks losing its own brand value. This is one reason you see, across time, malls becoming segmented by the kind of stores they have.

A year and half back, I’d written about how the Jayanagar Shopping Complex “died”, thanks to non-increase of rents which resulted in cheap shops taking over, resulting in all the nicer shops moving out. In that I’d written:

On the other hand, the area immediately around the now-dying shopping complex has emerged as a brilliant retail destination.

And now I see this Schelling-ian game playing out in the area around the Jayanagar Shopping Complex. This is especially visible on two roads that attract a lot of shoppers – 11th main and 30th cross (which intersect at the Cool Joint junction).

These are two roads that have historically had a lot of good branded stores, but the way they’ve developed in the last year or so is interesting.

I don’t know if it has to do with drainage works that have been taking forever, but 32nd Cross seems to be moving more and more downmarket. A Woodland’s shoe store moved out. As did a Peter England store. Shree Sagar, which once served excellent chaats, now looks desolate.

The road has instead been taken over by stores selling “export reject garments” and knock down brands. And as I’ve observed over the last few months, these kind of shops continue take over more and more of the retail space on that road. In that sense, it is surprising that a new Jockey store took over three floors of a building on that road – seems completely out of character there. I expect it to move in short order.

I must mention here that over the last few years, the supply of retail space in Jayanagar has exploded, and that has automatically meant that all kinds of brands have space to operate there. It was only natural that a process takes place where certain roads become more upmarket than others.

Nevertheless, the way 30th cross (between 10th and 11th mains) and 10th main have visibly evolved over the last year or so is rather interesting.

Video Geographic Monopolies

There is one quirk about video which we don’t face with print – some content is simply impossible to access legally in some parts of the world.

I’m specifically talking about BBC’s Match Of The Day, their end of day highlights package covering the English Premier League. It was one show that I watched unfailingly during my time in London, both for the match highlights, and for the quality of the discussion featuring Gary Lineker, Alan Shearer, Ian Wright et al.

Now I find that the show is simply not available in India – some youtube channels illegally offer the show (before they are taken down, I guess), but without the bits that show pictures of the game (which they are not allowed to show). And that makes for rather painful watching, knowing that you’re watching something substandard.

This is not the case with something like text – as long as I’m willing to pay, I’m able to access content produced anywhere in the world. I can sit here in Bangalore and buy a subscription to the New York Times, and access all its content. Audio is also similar – I can sit here and subscribe to any international podcast, and be able to access the content.

Video doesn’t work that way. The problem is with the way rights are sold – the Star network, for example, has a monopoly on showing pictures from the Premier League in India (having paid a substantial amount for it). And part of their arrangement means that nobody else is allowed to broadcast this material in India. A consequence of this is that we are stuck with whatever (mostly crappy) analysis Star decides to provide around its games. Stuff that is unwatchable.

There is a lot of great sport content online, but the video part is constrained by the inability to show pictures. Check out analysis by Tifo Football, for example – it’s absolutely top class. However, for most games, they have to rely on stock images and block diagrams since they can’t show the pictures which someone has a monopoly on. And that makes the analysis less rich (the Athletic, which I have a subscription to, “solves” this in an interesting way – by using screenshots of the TV footage of the game as part of their text analysis).

I wonder if there is a way out of this. Some leagues such as the NBA have shown some enlightened thinking on this – while they are anal about copyright of their live feed, they don’t care about copyrights on recorded footage. This means that anyone can use footage from historical NBA games as part of their analysis. Better analysis means more people interested in the sport, which means more people watching the live feed, which makes more money for the league (read this excellent interview of NBA Commissioner Adam Silver).

I’m also beginning to think if there is a regulatory antitrust response to this issue. Video distribution (especially of live content) is a natural monopoly, so it doesn’t make sense to have competing broadcasters. However, I wonder if there is any regulation possible for historical feeds that makes them more tradable (with the rights holders getting appropriately compensated without much transaction costs)!

One can only hope..

Evolution of sports broadcasting

I had a pleasant surprise yesterday morning when I was watching the highlights of Liverpool’s 4-0 victory at Leicester. The picture quality suddenly looked better. The production aesthetics in the first few seconds (before coverage of the actual match began) looked “American”. I doubted myself for a minute if this was actually English football I was watching.

And then I remembered that the pictures for this  game came from Amazon Prime. The streaming service had got rights to broadcast two full rounds of Premier League games this season, making a small chink in the duopoly of Sky Sports and BT Sport.

Traditional media wasn’t too impressed by it. Streaming necessarily meant a small delay in broadcast, and that made it less exciting for some viewers. The Guardian predictably made a noise about the “corporate takeover” with Amazon’s entry. From all the reports I read (mostly across the Guardian and the Athletic), commentators seemed intent on picking holes in Amazon’s performance.

That said, the new broadcaster also brought a fresh production aesthetic. While there were the inevitable teething problems (I must confess I didn’t watch these games live – being midweek evening games, they were very late night in India), Amazon for sure brought some new ideas into the broadcast.

Just like Fox Sports had done when it had done a big launch into NFL broadcasting in the early 90s. Read this oral history of that episode. It’s rather fantastic. Among the “innovations” that Fox Sports brought into American broadcasting (based on its sports broadcast in Australia, primarily) was this box at the corner showing the time and the live score. The thing wasn’t initially well received, but is now a fixture.

For evolution to happen, you need sex. And that means mixing things up, in ways they weren’t mixed before. If we were all the children of a super-god and a super-goddess, we would all be pretty much the same since the amount of “innovation” that could happen would be limited. And things would be boring, and static. Complex forms such as human beings could have never happened.

It is similar in business, and sports broadcasting, as well. When you have the same channels covering the same sports, they get into well-set local optima, and nothing new is tried. There is no necessity for improvement in that sense.

When new players comes in, preferably from another market, however, they see the need to differentiate themselves, and bring in ideas from their former market. And this leads to a crossover of ideas. In their efforts to stand out and make an impact, they might also bring in some ideas never seen anywhere – “mutations” in the evolutionary sense.

A lot of them don’t make sense and they die out. Others score unexpected hits and catch on. And that way, this memetic evolution leads to better business.

The great thing about memetic evolution is that while bad ideas come along much more often than good ideas, they get discarded fairly quickly, while the good ideas live on. And that leads to overall better products.

Right now in India we have a duopoly in sports broadcasting, controlled by the Star family and the Sony family. I’ve ranted several times about how the latter is absolutely atrocious and does nothing to improve the game. Hopefully a new player getting rights of some sport here will shake things up and bring in fresh ideas. Even if some of the ideas turn out to be bad, there will be plenty of good ideas.

Check out the highlights of the Leicester-Liverpool game, and you’ll get an idea.

Arzoos

Founders, once they have a successful exit, tend to treat themselves as Gods.

Investors bow to them, and possibly recruit them into their investment teams. Startups flock to them, in the hope that they might use their recently gained wealth to invest in these companies. Having produced one successful exit, people assume that these people have “cracked the startup game”.

And so even if they have started humbly after their exit, all this adulation, and the perceived to potentially make or break a company by pulling out their chequebooks, goes to their head and the successful exit founders start treating themselves as Gods. And they believe that their one successful exit, which might have come for whatever reason (including a healthy dose of luck), makes them an authority to speak on pretty much any topic under the sun.

Now, I’m not grudging their money. There would have been something in the companies that they built, including timing or luck, even, that makes these people deserving of all the money they’ve made. What irritates me is their attitude of “knowing the mantra to be successful”, which allows them to comment on pretty much any issue or company, thinking people will take them seriously.

Recently I’ve come up with a word to represent all these one-time-successful founders who then flounder while dispensing advice – “Arzoos”.

The name of course alludes to Arzoo.com, which Sabeer Bhatia started after selling Hotmail to Microsoft. He had made a massive exit, and was one of the poster children of the dotcom boom (before the bust), especially in his native India. Except that the next company he started (Arzoo) sank without a trace to the extent that nobody even knows (or remembers) what the company did.

There is a huge dose of luck involved in making a small company successful, and that someone had a good exit doesn’t necessarily mean that they are great businessmen. As a corollary, that someone’s startup failed doesn’t make them bad businessmen.

Then again, it is part of human nature that we attribute all our successes to skill, and all our failures to bad luck!

 

Reliance Jio Tariffs Seem Stupid

For the longest time I used a post-paid mobile phone. The hassle of recharging regularly, combined with the attractive rates available on post-paid “corporate” plans, meant that right from the time I graduated business school (in 2006) till I moved to England in 2017, I almost wholly used postpaid phones.

And then in England, I got a prepaid sim upon landing, and then soon discovered that it wasn’t more expensive than a postpaid (and there was no paperwork), and I kept the prepaid. Upon returning to India earlier this year, I’ve continued with a prepaid phone, with a Reliance Jio number. A few months back, I took an annual plan with Jio, paying for a year what I used to pay Airtel in less than two months before I moved out of India.

One of the reasons I don’t really mind having a pre-paid now is that it is far less of a hassle than postpaid. I have a 12 month program, for which I paid once, and until next May I don’t need to worry at all. There is one less bill to be paid each month.

And one thing that makes this “hassle-free” is that I don’t need to check my usage at all, either in terms of voice and data. It is a nicely bundled plan, with zero marginal cost for either calling or using data (the latter up to a (very high) limit). When there is a per-call charge, the balance notification at the end of each call places a mental cost (even if it is a low marginal cost), and you sometimes wonder if you need to call at all, or when you need to recharge.

The “current” zero marginal cost plan by Jio (I had a similar plan from EE in the UK) means that there is no such mental cost, and you can treat your prepaid mobile like you used to a postpaid.

Now things are changing. There are regulatory issues in India – on the “inter connection charge”. When a Jio customer calls an Airtel customer, Jio has to pay Airtel 6 paise per minute for Airtel’s service of completing the call on its network. This was earlier 14 paise a minute, which came down to 6 thanks to Jio’s lobbying, and was supposed to go away entirely in 2020.

When the entire market has settled on a zero marginal cost plan, like it is the case in the UK, inter connection charges don’t really matter. In India, however, there is massive asymmetry. People on older plans from Airtel and Vodafone still pay a lot for their calls, so they don’t mind paying a high interconnection charge, and want to receive a high inter-connection charge.

So over the last couple of months you’ve had massive lobbying, and hilarious exchanges like the debate among the major telcos regarding “missed calls” and how long the phone should ring.

Anyway, it appears that the inter connection charges won’t go away next year as planned. Jio is not happy. And in order to show its spite, it has decided to start charging for calling. A marginal charge of 6 paise a minute is going to be applied on Jio customers calling non-Jio phones.

I don’t see how this is going to be good for the Jio customer (I’m protected since I’d bought a long term plan earlier this year). The mental cost of calling comes back. You need to start worrying about what network the person receiving your call uses. You start getting that balance notification at the end of your call. You might need to recharge before your validity is over, creating more mental cost.

In other words, it seems like a rather dumb move by Jio. While it has clearly been taken to show that the operator is pissed off with the competition and the regulators, it is likely to hurt Ji0’s own business and drive its customers to the competition.

There were several smarter ways to handle this. Basically the problem is that Jio’s costs aren’t coming down as expected, so it needs to charge more. And there are several ways of charging more without imposing a mental cost.

One, the price point itself can be increased. Instead of Rs. 150 a month, it can charge Rs. 160. Second, instead of “unlimited free calls”, they can offer “1000 minutes of free calling per month” or something like that, with a different plan offering 2000 minutes of free calling per month. And so on.

But no. Reliance is more interested in making a statement than serving its own customers. And so it comes up with hare-brained schemes like charging per call “outside the network”. It will be interesting to see how their growth goes like over the next few months.

Dunzo and Urbanclap

I realise that Dunzo and Urbanclap (and many other apps) grew in a particular way. Initially they weren’t sure of the exact problem that they were solving, and instead focussed on a particular “problem class”.

And then over time, based on pattern recognition and segmentation/cluster analysis of the kind of problems that people were using these apps to solve, they started providing more targeted solutions that made better business sense.

Dunzo started off as a “we’ll do anything for you” app. People making fun of the company would talk about a Dunzo executive who would come home, collect your bean bag, get the beans refilled and bring it back to you, and only charge for the beans.

I’m pretty sure that there were many other such weird use cases in which people sort of abused Dunzo in its early days. However, most of the users of the app, I’m guessing, used it for sending packages across town, and to fetch stuff for them from shops and restaurants. And now, four years down the line, Dunzo highlights these specific streamlined use cases in the app, and has figured out a good way of charging for each of them.

It’s similar with Urbanclap. While I didn’t use them in the early days, I used their competitor HouseJoy. I used the app to request for “a plumber”. A plumber duly arrived and did all sorts of odd jobs in our apartment building, some of which were dangerous. And then at the end we paid him in cash, and he told us that “if someone from the app calls, tell them you paid me only 200 rupees” (we had paid him 2000).

Soon, after being a marketplace for all sorts of odd jobs, Urbanclap and its ilk noticed patterns and started specific services. So last week we got someone from Urbanclap to “repair our water heater” (this had a fixed fee on the app). It is another set of such specific services that UrbanClap offers.

I may not have said much new in this post, but it’s basically a crystallisation of some of my thoughts of late – sometimes it’s okay to not have a particularly precise business plan as long as you know what problem class you’re tackling. If you manage to get funded and are willing to burn money, you can learn the best set of problems from the market (within your identified class).

It’s an expensive process for sure, since until you figure this out you’ll be spending a lot of time and money doing random shit, but if you and your investors are willing to bear this kind of expense, it might be worth it.

The worst thing that can happen to you, though, is that after you’ve burnt your company’s money in learning about the market’s precise problem statement, another well-capitalised firm moves faster than you to address this specific market. The question is how well you can put to use your learnings from the early period for later on.

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?