dating – Pertinent Observations

Christian Rudder and Corporate Ratings

One of the studdest book chapters I’ve read is from Christian Rudder’s Dataclysm. Rudder is a cofounder of OkCupid, now part of the match.com portfolio of matchmakers. In this book, he has taken insights from OkCupid’s own data to draw insights about human life and behaviour.

It is a typical non-fiction book, with a studmax first chapter, and which gets progressively weaker. And it is the first chapter (which I’ve written about before) that I’m going to talk about here. There is a nice write-up and extract in Maria Popova’s website (which used to be called BrainPickings) here.

Quoting Maria Popova:

What Rudder and his team found was that not all averages are created equal in terms of actual romantic opportunities — greater variance means greater opportunity. Based on the data on heterosexual females, women who were rated average overall but arrived there via polarizing rankings — lots of 1’s, lots of 5’s — got exponentially more messages (“the precursor to outcomes like in-depth conversations, the exchange of contact information, and eventually in-person meetings”) than women whom most men rated a 3.

In one-hit markets like love (you only need to love and be loved by one person to be “successful” in this), high volatility is an asset. It is like option pricing if you think about it – higher volatility means greater chance of being in the money, and that is all you care about here. How deep out of the money you are just doesn’t matter.

I was thinking about this in some random context this morning when I was also thinking of the corporate appraisal process. Now, the difference between dating and appraisals is that on OKCupid you might get several ratings on a 5-point scale, but in your office you only get one rating each year on a 5-point scale. However, if you are a manager, and especially if you are managing a large team, you will GIVE out lots of ratings each year.

And so I was wondering – what does the variance of ratings you give out tell about you as a manager? Assume that HR doesn’t impose any “grading on curve” thing, what does it say if you are a manager who gave out an average rating of 3, with standard deviation 0.5, versus a manager who gave an average of 3, with all employees receiving 1s and 5s.

From a corporate perspective, would you rather want a team full of 3s, or a team with a few 5s and a few 1s (who, it is likely, will leave)? Once again, if you think about it, it depends on your Vega (returns to volatility). In some sense, it depends on whether you are running a stud or a fighter team.

If you are running a fighter team, where there is no real “spectacular performance” but you need your people to grind it out, not make mistakes, pay attention to detail and do their jobs, you want a team full of3s. The 5s in this team don’t contribute that much more than a 3. And 1s can seriously hurt your performance.

On the other hand, if you’re running a stud team, you will want high variance. Because by the sheer nature of work, in a stud team, the 5s will add significantly more value than the 1s might cause damage. When you are running a stud team, a team full of 3s doesn’t work – you are running far below potential in that case.

Assuming that your team has delivered, then maybe the distribution of ratings across the team is a function of whether it does more stud or fighter work? Or am I force fitting my pet theory a bit too much here?

Hinge koDaka

Being married to Marriage Broker Auntie means that I sometimes get to participate, either directly or indirectly, in some of her “experiments”. Her latest experiment was to get on to dating apps, to see what the hell they are all about, so that she can advise her clients better about them.

She has written about her experience on these apps in the latest edition of her newsletter. Oh, and you should totally subscribe to her newsletter if you haven’t already. You will get some very interesting relationship insights, which you can appreciate even if you aren’t looking for a relationship.

Anyways, once she started her latest experiment, I asked myself “why should girls have all the fun?”, and got curious to get on these apps myself. I spoke to her about it, and she suggested that I check out Hinge. “It’s the most decent among all the apps”, she said.

I mean, this wasn’t my first time on a dating app. Though they all appeared well after I had got married, I remember trying out Tinder a few years back, possibly as part of another of my wife’s experiments. I remember getting disillusioned by it and deleting it in less than a day. I had even forgotten about it, except that when I was searching for Hinge on the app store, I found that I had already “bought” Tinder in the past (I now realise I’d tried TrulyMadly in the past as well – yet another unmemorable experience).

Anyways, I quite liked Hinge. I spent a whole week on it, before I decided that people who don’t know what’s happening might think I’m a creep and deleted my account.

What makes Hinge so nice is the way it is structured and the user experience. For starters, there’s no easy swiping left or right – there are (fairly small) buttons to either like or dismiss a profile, and in case there has been a mutual like, then there is a “match” and you can start chatting.

Also, from one little experiment (where the wife and I decided to like each other on Hinge), I found that Hinge has implemented something that I have always believed in – basically don’t tell both parties that there is a match immediately after the second person has liked. That way, the pair know who liked whom first and that can set an unhealthy prior in the relationship. Instead, if the app waits for a “random period of time” before announcing the match, you don’t know who liked whom first.

Back to Hinge – what I liked about it was how the profiles had been designed. You are asked to upload six photos of yourself doing different things, and also answer a few questions. The answers to these questions are displayed in bold on your profile, and this means that anyone who pays some amount of attention is likely to see these answers.

This means that you don’t need to impress your potential counterparties with your photos (or one photo) alone – you can show off your “well rounded personality” (if you have one that is). For example, I found this girl whose profile seemed unremarkable until I saw that she “got turned on by probability and maths”. That, of course, grabbed my attention and I immediately paid much more attention to her full profile. This kind of information (conveying your possibly unusual interests) is a little hard to get across on other dating platforms.

The other nice thing about Hinge is that you can choose what part of a person’s profile you want to like. You could choose one of the pictures, for example, or one of their answers to some question. Like if I were actually in the market (and not casually “researching”) I would have tried to start a conversation with the above mentioned person by liking (and possibly commenting on) her interest in probability.

This specific liking provides an automatic conversation starter. And in a congested market (see chapter 4 of my book here), anything that can help you distinguish yourself can be a sure winner. So it helps that you can write about your interest in probability. It helps that you can tell someone you like her for her interest in probability and not for her tattoo. In marketing jargon, it allows you to be “a qualified lead”.

I had fun for about a week. I must mention that I had used my real name (rather, my oldest nickname that everyone knows me by), and my real photo (my wife picked that one) on the platform. And then I got likes from two women (apart from the one from my wife).

Given that I’m not actually looking for a relationship, that made me feel like I’m doing something wrong. I felt horrible about myself for putting myself on a dating app when I’m not looking to date. There was also the thing that people who found me on the app and knew me would think of me as a creep (or get the wrong kind of ideas about my marriage). So I deleted it.

However, if you are in the market and looking to date, I strongly recommend Hinge. Among the apps that I’ve used, it’s easily among the best.

Truly Madly: Review

So the wife and I both decided to sign up on the dating app TrulyMadly, she to conduct research for her matchmaking service, and me as part of my research for the book that I’m currently revising. Based on our collective usage of our respective apps for about an hour, here are some pertinent observations.

Sexism: The wife can see salaries of men she is getting matched with, while I don’t get to see salaries of women being recommended to me. Moreover, women are allowed to “lurk” (and not have a public profile) on the platform, but no such thing for men. I’m surprised no one has called out TrulyMadly on their sexism
Job board: To list on the app you need to indicate your profession and job, and how much you are making. So if you are a woman on this site, apart from getting to check out men, you get to check out what jobs pay how much, and it’s not inconceivable that you use the app to find yourself a job.
Judgments: This should possibly go down under sexism again. Anyway, the wife has mentioned her qualifications as “MBA”, and she is only being shown men who are graduates of top B-schools in India. No such thing for me – women shown to me had all kinds of qualifications. It’s like TrulyMadly has decided that women should only date men who are at least as well qualified as them. Moreover, the app also decides that men can only date women who are shorter than them, though there’s a setting somewhere to change this.
Age bar: Based on my age (which I entered as 34), the app decided that I should only be allowed to check out women between the ages of 26 and 34. These can be moved around, in case I have fetishes outside this age range, but I’m shocked that they are not aware of the N/2+7 rule – based on which the lower limit should’ve been set at 24 (34/2+7) and not 26.
Gender imbalance: The app gave up on me after I rejected some half a dozen women, after which I deactivated my account and deleted the app. The wife’s app, however, continues to go strong, as she might have rejected some two or three dozen men by now (apart from having done research on what jobs pay how much). Just goes to show the gender imbalance on the app. I can imagine this leading to a lot of frustrated people, of both genders.

Ok that’s it for now. Any more insights you can read in my book (I hope to get it out in the next month or two)!

Moral of the story: Product management pays better than category leader.

Good boys don’t get laid

Last night I bought Christian Rudder’s Dataclysm: Who We Are (When We Think No One’s Looking) and started reading it. I’m now about 10% into the book, well past the Kindle sample (I bought the book in entirety after I’d finished the sample). I’m past the first couple of chapters and am now reading a chapter on the contributions of Twitter to linguistics.

Rudder is a co-founder and Chief Data Scientist at the matchmaking website OkCupid, and he draws upon some aggregate data that his website has collected to point out some rather interesting stuff about how people think, view themselves, and the kind of partners they are looking for. One very interesting piece of analysis (which includes a couple of brilliant graphs) shows the preference for the partner’s age among men and women of different ages. So far the book has been absolutely spectacular.

The part of the book that I’ve found most fascinating so far is the one on averages and variances. Rudder looks at the average ratings of a large number of women registered on OkCupid (as rated by men) and tries to correlate their ratings with their success on the site (measured in terms of the number of messages they have received from men on the site wanting to date them). Given the scale of the data that Rudder has access to (rather large), the results are rather stupendous.

What Rudder finds is that for a given level of average rating for a woman, the higher the variance in her rating, the more the number of messages she receives. There are some quirky statistics he quotes (a lot of which has been extracted in this post on Brain Pickings – it was after a friend sent me this post that I got interested and bought the book) which show that women who are consistently rated a 3 (on a scale of 1-5) by men are much less likely to get a message than someone who gets a mix of 1s and 5s.

From this Rudder concludes that negative ratings actually boost a woman’s chances of getting a date – the fact that a number of men have rated someone unattractive means that there is something about her that a lot of men don’t like. This implies that the “competition” for getting her is possibly low, and you might be able to get a “bargain” or an “arbitrage” if you are able to get her.

While this is a plausible and rather palatable thesis, I have an alternate explanation for the same data – I posit that low ratings don’t matter. Some people might have rated you lowly but they don’t matter since they aren’t interested in you. What matters simply is the number of high ratings that you get – people are always on the lookout for spectacular people to date, and by getting a number of 5s, you are showing that you are found rather attractive by a number of people. The ratings of 1 that you have received are an anomaly – messages of rejection from people who don’t want to date you, and all they do is to pull down your average. A better way of comparing women would be to throw away the bottom 20% of all ratings that a woman gets and then calculate the average – and a lot of 3s that Rudder has analysed in his book are likely to come out as something more than that.

Irrespective of the reason for the correlation of variance with attractiveness, though, what is undisputed is that people look for spectacular people to date. If you are a consistent three, irrespective of whether you go by Rudder’s thesis or mine, a large number of men are likely to rate you as being “unspectacular”. When given a choice between dating someone who is a “common minimum program” on most dimensions and someone who has a “spike” (as recruiting management consultants like to put it), you are likely to be more interested in the one that has the spike. What you consider to be a spike might be considered to be a trough by others, which probably leads to an average average rating (but high variance), but it is the spike that attracts you to her.

The problem with the arranged marriage market in India is that it is set up such that people show off their “average” side. As I had argued several years earlier (back when I was in the market), the Indian arranged marriage market is dominated by people who are themselves “common minimum programmes” and who are looking for “common minimum programmes” to marry. Thus, if you want to enter that market yourself, you try to mould yourself as yet another common minimum program and try to hide your spike rather than to enhance it (it is also a result of counterparties sharing notes in the arranged marriage market, something that doesn’t happen in the dating market. If you have a spike that one girl considers to be a trough, her folks are likely to tell people known to them about your trough (which is actually a spike), and that might pull down your average rating).

Most Indian parents bring up their kids to become good materials in the arranged marriage market, and since it is the unspectacular CMP that succeeds in that market, parents aspire to get their grown up kids to fit such moulds. Any possibly deviant behaviour is quickly dissed, non-standard careers are strongly discouraged, you are encouraged to dress unspectacularly and so on. Taking this together with Rudder’s thesis, what this means is that if you prime yourself for the arranged marriage market, you are losing out on the dating market!

What it takes to be a success in the arranged marriage market (solidity, unspectacularity, CMPness) are directly at odds to what it takes to succeed in the dating market (a spike, quirkiness, character) and so once you have decided to enter one market you automatically become a failure in the other. This thesis also explains why people who break up in their mid/late twenties and who consequently enter the arranged marriage market (possibly since it offers the quickest chance of a rebound) struggle significantly in that market – they have been primed for the dating market which makes them unhot in the arranged marriage market.

One “spike” that I consider to be a part of my character is this blog. Back in the Benjarong conference, I was given sage advice that I do not disclose this blog to prospective brides from the arranged marriage market, thanks to posts like this one and this one. Finally I ended up marrying someone who I met as a consequence of this blog (this post to be precise – she later told me) – who messaged me on Orkut saying she likes my blog, because of which we got talking and so forth. It was the spike – possibly considered abhorrent by many – that was responsible for my finding my wife!

So decide which market you actually want to be in before you prime yourself. “I’ll also casually look at the other market” is never likely to work.