This document summarizes a quantitative analysis of the author's Tinder data over 5 years. Some key findings include: the author's message and match rates were lower than average; he spent over 100 hours swiping with a success rate of 0.07% per swipe; and his success rate declined over time. The author concludes Tinder may not be for him and offers to build an app to analyze others' Tinder data for entertainment with no productive use.

1. Match. Chat. Date… Analyze?
A quant study falling down the tinder rabbit hole

2. “Our Objective”
None really, just see how much fun stuff we can learn with a little bit of ruby,
your tinder data, and an abundance of time

3. A Wildly Mediocre Introduction

4. Their story…
sort of
4
It’s a dating app, you swipe
left, you swipe right, you get
laid… are you fucking stupid?
“
”
- My friend Nico

5. By the
numbers
5
33% of men admitted to
casually liking pretty much
anything, regardless of
attraction or connection
… surprise surprise
Source: Know Your Mobile , Tech Jury
50M estimated users, 76.9% are male 🙋🏻♂️🙋🏻♂️🙋🏻♂️🙋
🏻♀️
1.6 Billion Swipes per day 🏻
The hashtag #tinderwedding has been used more than
1,700 on Instagram 👰🏻
95% of Tinder matches meet within 2 to 7 days of
matching 🏃♀️

6. By the
numbers
6
I’m not saying height is all that
matters guys, but apparently
height is all that matters
Source: Know Your Mobile , Tech Jury

7. By the
numbers
7
We’re out here wading in nerdy
active professionals and
sarcastic shy bitches
… apparently
Source: Know Your Mobile , Tech Jury

8. By the
numbers
8
Dogs are the cornerstone of our
society… this pleases me
Source: Know Your Mobile , Tech Jury

9. By the
numbers
9
And for me, I started sometime
back in 2014 at Georgia Tech
where I used the app on and off
with mixed success off some
interesting ploys and social
experiments
I did not have the same luck after trying the same cringy tactics unfortunately, but I did
have a few interesting convos… sigh 😐

10. But more recently…

11. It was the
summer of love
11
And by summer I mean the past 3 years,
where I would move from:
LA 🏻 MIA 🏻 PDX 🏻 BCN
I was tindering across America and abroad, I
liked to call myself Pitbull aka Mister 205 aka
Mister World Wide.
My friends preferred to call me a walking
billboard advocating the need for STD testing
Source: TravelMap
Over the course of those years I was maniacal about tinder. Often times
when I moved to a new place, the only way to meet new people was
through dating apps

12. And I’m
…a nerd
12
Exploring sites like r/tinder and
brushing off my coding skills, it
was too good an opportunity to
pass up, and so just like in
”Teen Witch”, it was time to…

13. 13If you haven’t seen this video, do yourself a favor and watch it now… Go on, I’ll wait, it’s that good.

14. So just like poor Dorothy;
down the rabbit hole we go
14
This data is super easy to get.
Simply go here and request
your data.
In a few days you’ll have a
massive JSON file to start
exploring

15. If only I knew,
how deep it went

16. Some ruby, excel, and 5 years of data
16
More on this data later…
For those of you doing the math, my avg. swipe right
ratio is 40.73%
As a benchmark women on avg. swipe right 14% of
the time, and men at a whopping 46% of the time.
So I guess you could say I’m picky… 😑
My Code: github repo

17. 17

18. What was
I saying?
18
After a class lecture where we
tabulated word frequencies in text
files, I thought, heck that might be
interesting for my messages. What
exactly was this game that I was
spitting…?
From this at least I know I’m not a
complete creep. Obsessive… yes.
Cringey… no. I ended up teaching this same lecture later on, and did this
exercise with my students. Pointless exercises tabulating
lorem ipsum files suck.

19. And how was
I saying it?
19
After building the word cloud and realizing I
was as exciting as watching paint dry, I
wondered if there was something to unearth
about how I was saying things.
So sentiment analysis it was. I used the gem
‘sentimental’ from 7compass to analyze 470
messages to come to the wild conclusion
that my overall sentiment was positive…
Thrilling… I know
{ 0.191 }
😐Anything over 0 is positive, so apparently I’m a nice guy?
So far the indications are pretty clear on how successful I
am dating…

20. We want graphs!
We want graphs!
We want graphs!

21. OK… my game is whack,
What about my behavior?
21

22. So exactly how thirsty was I… by day?
22
0
10
20
30
40
50
60
70
January7,2015
February7,2015
March7,2015
April7,2015
May7,2015
June7,2015
July7,2015
August7,2015
September7,2015
October7,2015
November7,2015
December7,2015
January7,2016
February7,2016
March7,2016
April7,2016
May7,2016
June7,2016
July7,2016
August7,2016
September7,2016
October7,2016
November7,2016
December7,2016
January7,2017
February7,2017
March7,2017
April7,2017
May7,2017
June7,2017
July7,2017
August7,2017
September7,2017
October7,2017
November7,2017
December7,2017
January7,2018
February7,2018
March7,2018
April7,2018
May7,2018
June7,2018
July7,2018
August7,2018
September7,2018
October7,2018
November7,2018
December7,2018
January7,2019
February7,2019
March7,2019
April7,2019
May7,2019
June7,2019
July7,2019
Sep 25, 2015: 65 Opens
Fri: Safety training day at work
Jul 25, 2018: 50 Opens
Wed: Music festival that weekend,
Trying my best not to be that weird Chad
by himself

23. By month?
23
0
50
100
150
200
250
300
350
400
450
500
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2015 2016 2017 2018 2019
Jul 2018: 396 Opens
Life in Miami was funny 🏻♂️
Feb 2019: 435 Opens
Just about to quit job

24. No…
Thirst is measured in swipes

25. 0
1000
2000
3000
4000
5000
6000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2015 2016 2017 2018 2019
How about Swipes per Month?
25
“Over” online dating
Apr 2019: 5399 Swipes
Last month in PDX
Oct 2015: 1629 Swipes
Driven solely by Halloween Wknd,
Looking for my TInderella
Jul 2019:
3859 Swipes
Landed in BCN

26. 0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2015 2016 2017 2018 2019
Sum of Swipe Right Sum of Total Swipes
And my standards, how did those fare?
26
Shaved my head bald,
Feeling VVEERRRYYY
SELF CONSCIOUS
I regret nothing
BENCHMARK
Women: 14%
Men: 46%
Me: 40%

27. 0
10
20
30
40
50
60
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2015 2016 2017 2018 2019
For all my shenanigans, was I improving?
27
…even with my massive increase in
swiping, my monthly matches while
growing did not match pace

28. Ok… too many graphs

29. Let’s talk about this again instead
29
Specifically about this portion

30. But first, what were the people seeing?
30

31. So you’ve seen
the photos…
31
And you say wow, he doesn’t look like he fell
off the ugly tree and hit every branch on the
way down…lemme swipe right. What happens
next?
Well, chances were pretty good that if we
matched, I would message you 72% of the
time, compare this to the 7% message rate on
average by men.
That’s a 10X metric right there, driven by most
men’s post-match filtering strategy. You’re
welcome everyone.
Yes, I was that guy who posted a shirtless pic, sue me.
Source: A First Look at User Activity on Tinder

32. Just call me Liam Neeson
32
Because if you engage with me…
I will message you, I will make you laugh, and I will take you on a wonderful date.
Overall, my odds of getting a date out of a swipe were pretty slim, at 0.07% 😭
It improved when you looked at my odds of getting a date out of a match at 2.91%
But my favorite was the odds of getting a date if I managed to have a fruitful conversation (2+
messages) with you, which ended up at 12.93% 🎉
So how much effort did all this tindering take exactly?

33. I need
to use my
time way better
33
So let’s take one of those first
numbers (64843 swipes)
Assuming 5.7 – 6.26 sec per swipe, I
spent 6,484 min swiping ( ~ 108
hours) 🏻🏻♂️
In terms of effort per date, I put in 5.7
hours per date…
What else could I have done with
that time?
Seen the Lord of the Rings trilogy over 9 times 💍
With 108 hours I could have…
Done 2.5 weeks of actual productive work 👨🏻💼
Flown around the world twice 🏻
Watched every episode of “The Office” 1.5 times 🏢
Made 13 more of these presentations 🏻
Flown to NYC from MEL, visit Liberated Movement Dance
Studio on Broadway, take every one of their interpretive dance
classes, flown back to MEL, and still have enough time to make
this presentation 👯♀️

34. How about the highlights?

35. Not super proud of all these “records”
35
740 Total Swipes on December 3, 2018, I chucked a sickie and went
snowboarding, guess what I was doing on the lift? 🏂
Most Swipes in a Day
231 Right Swipes on July 11, 2019, Sitting in class “learning” about
inheritance and class methods 🏻♂️
Most Right Swipes in a Day
45 Messages with Hannah, ended up going on a date, but sadly, no
chemistry between us 👩🔬
Record Length Conversation

36. or these… 🤦🤦
36
“All right [Insert Name], pick your poison, endless tinder messages that
ultimately amount to nothing or let’s just grab a drink this week. Life’s too
short for the whole tinder thing ad nauseam”
Most Successful Canned Opener
1. “If I'll be your Prince Charming, will you be my tinderella?”
2. “If you were a vegetable you'd be a cutecumber.”
Worst Lines ( I’ll never forgive myself for )
🐳  You’re probably wondering why?
Because my second most popular opener usually was:
“🐳🐳🐳 what do we have here?”
Most Used Emoticon

37. 0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
April17,2015
April25,2015
May5,2015
June29,2015
July7,2015
July17,2015
August3,2015
August14,2015
August30,2015
September11,2015
September20,2015
October1,2015
October12,2015
October23,2015
November1,2015
March28,2016
April8,2016
May6,2016
May14,2016
May23,2016
June19,2016
July2,2016
July13,2016
July23,2016
July31,2016
August22,2016
September5,2016
September20,2016
September30,2016
December5,2016
December15,2016
December23,2016
January1,2017
January14,2017
April1,2017
April19,2017
July3,2017
July11,2017
February1,2018
May17,2018
June9,2018
June18,2018
June29,2018
July7,2018
July15,2018
July24,2018
August1,2018
August26,2018
September4,2018
September12,2018
September21,2018
September30,2018
October8,2018
October16,2018
October24,2018
November9,2018
November20,2018
November30,2018
December8,2018
December17,2018
January5,2019
January15,2019
January26,2019
February4,2019
February12,2019
February20,2019
February28,2019
March8,2019
March16,2019
March26,2019
April3,2019
April11,2019
April20,2019
April30,2019
May8,2019
May21,2019
June4,2019
June12,2019
June26,2019
July4,2019
July12,2019
But was I improving?
37
This is my cumulative success rate
average, defined by my matches sum
over my right swipes sum over time
CSRA = ∑Matches / ∑Right Swipes
This literally means I am
quantitatively becoming less
successful on tinder over time!

38. 38

39. But this
was absurd
39
As I’ve been getting more attractive
since college ended, as can be seen
from the extremely scientific graph to
the right.
And if I extrapolate 10 years further
into the future, well I think the data
speaks for itself.
Alas, maybe tinder just isn’t for me 🏻♂️
Time →
←
H
o
t
n
e
s
s
2014
2016
2017
2018
2030

40. In Closing: Sy’s Hot Takes

41. 1. Don’t listen to my advice on tinder
… clearly
*gestures at all of this*

42. 2. See One

43. So where do
we go from here
43
As I was building all of this out, I realized,
hopefully, some of you may also want to see
some of this info for your own data.
And again, because I love making things that
have no real productive use, I started building
an app with a few friends to do just that.
Once we finish we’ll be posting the app here
on our github. Send us an email and we’ll let
you know when it’s ready.

44. Thank you, Let’s grab coffee