Singles Events

Here is my list of singles events, organized by how much I liked them, what the key success factor is, and who they attract.

* Dinner out. Show up, eat, talk to the three people to the left right and front of you. A variation on this theme is spectator event (like some show), followed by a group dinner out.

* Lock and key event. It’s an elaborate trick to get everyone to talk to many people. Guys get keys, girls get locks, the game is to find the person you has the reciprocal part.

Night club with a ice breaker. Ice breakers are important because bars already exist–a singles event provides no value add value without it, except that presumably the crowd knows that people might hit on them and it is expected, unlike a regular bar where flirting is done by complicated unconscious and secret signals.

* Speed dating. Continually restarting a 4 minute conversation with random people. Groups larger than 40 people are not really speed dating unless held inside an airplane hangar on account of sound problems.

* Singles Volunteering. Work at a volunteer event doing minimum wage labor for free, then go out for dinner. It works unless people are tired after work and don’t want to go out for dinner. Depending on the

* Hiking. Good event because you get a chance to talk to someone for a long time. It literally takes time to break the ice for some people–event extroverts don’t get to the interesting conversational bits for at least half an hour.

* Night club without an ice breaker. Fine for raging extroverts. But raging extroverts find twenty friends walking to the metro, why are they going to a singles event? Still, some how people show up at these in large numbers, someone must like them.

* Classes. Obviously no one interacts during a lecture, unless they are rude to the teacher. So a successful singles class will have to do something that requires student to student interaction, like breaking into mini-discussion groups.

* Discussion/Round circle. In DC, these often get really big, so they use the 3-5 minute rule and a token that gets passed around to indicate who speaks. This is important in mixed gendered groups because the large the group, the more likely men are to hog time and women to not talk at all (It’s proven by sociologists! Don’t make me have to pull a reference on you!)

* Book Club. These are slow to start, require planning sometimes months in advance. The long lead times leads to sometimes poor group cohesion ( losing/gaining lots of members). Obviously a singles book club would try to pick a book that is interesting to both men & women and may be topical to relationships and the like.

* Un-singles groups, e.g young adults groups. This would include any special interest group that has high cohesion (same large core of people at all events) So far the only group I’ve seen like this at a church event, although I suppose some work and school environments are like this.

* Pot luck. See above & basic singles event.

* Holiday party. See above & basic singles event.

Basic Singles Event. Dissuade married people from coming, encourage singles, provide opportunity for people people to interact. Sometimes events are gender balance, sometimes not. The ever popular 50%/50% target ratio is broken because women travel in pairs and the wing woman isn’t necessarily open dating. Sometimes participants are expected to ask for numbers and follow up on their own, sometimes the organizer gives everyone the attendees email’s afterwards.

Age range targeting is similarly tricky. To broad of an age range spread and no one can find someone in their preferred age range. A singles party with conversants 40 years apart is wishful thinking on the part of one or the other. And for some reason women tend to date older men and men date younger women, so the optimal announcement would say something like, women aged x to y and men aged x-1 to y + 5. But that is too much math.

Pros in the City Speed Dating

I went to a pro’s in the city event, 16 of the expected 20 people showed.  There wasn’t an age range advertised, so demographically we were all over the place, probably 22-to-45.  I was planning to check off everyone this time.    Half the women visibly didn’t write anything down.  There were two pairs of women where one was accompanying a friend.  In these cases usually one of the two is utterly uninterested in dating.  So I was only able to check off 6 out of 8.  Minus the two wing-women, that makes 4 out of 8.  If the yes-rate for an event like this is anything under 50% to 75%, my intuition says a mutual match is mind bogglingly unlikely.

Interestingly, some of the women out of this very small sample size were either very wealthy or seemed that way.

I’d rate the event: meh.  It was a lot of money to pay to be introduced to four random qualified women.

At least I’m slowly improving at the conversation thing.

Dating: By the numbers again

I’ve sent 100+ email by match.com. What is so frustrating is the lack of feedback.  I can tell if the email has been read, if my profile was viewed or if there was hesitation before they rejected me.  Simply reading can be predicted by the last time they logged on and if they have a picture.  But being an active account doesn’t mean they will respond positively.  In fact, so far, I’ve gotten about a dozen profile views and 8 canned rejections.

To use quantitative models to improve the situation, I need some positive feedback.  In other words, you can’t explain 100 no’s, but you can explain a small number of yes’es mixed in with a large number of no’s, say by using multiple regression.

So far the closest I can get to measurable positive feedback is a profile view or a delay between reading the email and sending me a rejection, and even there there isn’t much data to work with.

I tried using binomial distributions to model the situation. If I have a random number generator that returns 1′s and 0′s and it returns 100 zeros in a row, then I can ask myself, how likely is that given that the random number generator is calibrated to return a 1, say 5% of the time?   I’m not sure if I did my math right, but 100 zeros in a row is what you could expect 95% of the time if the random number generator was calibrated to return a one 1 in 1000 times.  In other words, if you get 100 no’s on match.com, if you don’t change your strategy, it will take 1000+ emails to get a single positive response.

There in lies the problem again, how can you improve without some positive feedback?  One doesn’t even get feedback on how vehemently one has been rejected.  Somehow, asking people to respond if the hate me with the fury of one thousand suns or only two hundred seems counterproductive.

Sigh.  Maybe that is what match is all about, ripping off people who don’t have a good feel for statistics.

Dating: Speed Dating

Speed dating, as I’ve said before is a parlor game.  And this evening it was also a parlor game.  It was $15 and organized through Pro’s in the City, held at Stacy’s Coffee in Falls Church.  Excellent people, although the geographic spread was huge.  We had people from the outer Virginia suburbs to Baltimore.

Today I was practicing ‘fessing up to my status, a single dad with joint custody.  Ironically, in my effort to be utterly honest, I kept misstating my age as 33 instead of 34.

Demographically speaking, the only downside was that the group of people was 30-39, so the youngest guy and the oldest women will have the fewest matches.  I’m not sure if there is a mathematically optimal way to solve the problem, but if the age range was say, 35-45 for men and 30-40 for women, then the youngest guy and the oldest women would still be the right age for half the possible matches.

Advice I should remember: bring some canned questions that cover some real qualifying territory, concentrate on facial reactions, be meticulous in accounting. 

Also, research says when forced to make a quick decision, men fall back on quick evaluations of health and women fall back on quick evaluations of wealth. Now all I need to do is track down myself a nice loud wrist watch.

Hypothesis about age brackets and singles events

Here is something that needs scientific testing. If someone holds a single’s event and says that everyone will be between age 30 and 40 (men and women), then who will show?

We start with the possibly sexist but probably true assumption that men prefer younger women and women prefer men of thier age or older.

So a guy of age 30 suspects women there will be 31 years or older, since it has already been announced that the youngest guy will be 30. He decides not go.

Another woman 40 years old considering going knows that the 30 old guy, won’t go, so she expects everyone there to be age 31-40. Since she is as old as the oldest guy there, she also decides not to go.

A guy of 31, expecting the above two prospects to follow that reasoning, calculates the age range is 32to 39. He drops out.

And so on. I guess eventually, only 35+ year old men will arrive and 30 to 35 year old women would arrive.

My thinking on the matter right now is a bit fuzzy, but I’m sure simulation with a variety of parameters probably could solve the problem. Or experimentation.