Participants by start month, year on year change


Year on Year % change of Melbourne participants by start date.

Participants by start month, year on year change per destination

Destination Month 2014 %change 15 2015 %change 16 2016 %change 17 2017 %change 18 2018
Melbourne01 Jan850%128%13-15%11
Melbourne02 Feb1200%367%520%617%7
Melbourne03 Mar1200%3167%8-50%475%7
Melbourne04 Apr1100%2150%520%617%7
Melbourne05 May2150%520%6-83%1500%6
Melbourne06 Jun90%9167%24-4%234%24
Melbourne07 Jul989%1718%2035%27-44%15
Melbourne08 Aug1600%70%714%8-25%6
Melbourne09 Sep2200%617%743%10-40%6
Melbourne10 Oct2750%17-59%729%9-22%7
Melbourne11 Nov2100%475%70%70%7
Melbourne12 Dec5-60%2
London01 Jan1619%19-37%12125%274%28
London02 Feb138%1414%1663%260%26
London03 Mar8-50%4125%967%15-7%14
London04 Apr560%863%1315%15-20%12
London05 May1718%2015%23-9%21-14%18
London06 Jun6633%889%9635%1302%133
London07 Jul3213%3622%4430%57-12%50
London08 Aug176%1844%264%277%29
London09 Sep24-13%2110%2361%375%39
London10 Oct1267%20-20%1656%25-4%24
London11 Nov813%933%1283%229%24
London12 Dec10-30%786%1315%15-40%9
Colombia
Colombia01 Jan9-33%617%729%9-11%8
Colombia02 Feb5-60%2150%5-20%425%5
Colombia03 Mar920%20%2
Colombia04 Apr2-50%10%1200%30%3
Colombia05 May20-80%4175%11-18%9-11%8
Colombia06 Jun1878%32-16%27126%61-2%60
Colombia07 Jul10140%244%2524%3116%36
Colombia08 Aug475%757%11-45%6-83%1
Colombia09 Sep1300%4125%911%10-40%6
Colombia10 Oct40%4-75%1900%1020%12
Colombia11 Nov8-13%70%70%7271%26
Colombia12 Dec5
Madrid01 Jan8-38%5140%12-8%1164%18
Madrid02 Feb250%333%4200%12-33%8
Madrid03 Mar5-60%2450%11-91%11000%11
Madrid04 Apr20%2350%9-67%367%5
Madrid05 May13-46%714%825%1010%11
Madrid06 Jun2588%47-23%3697%71-21%56
Madrid07 Jul1533%2020%2421%29-38%18
Madrid08 Aug7-29%5-40%31
Madrid09 Sep1030%1338%1867%30-7%28
Madrid10 Oct6117%138%14-36%9-67%3
Madrid11 Nov5-20%450%60%6-33%4
Madrid12 Dec367%50%50%5-20%4
Hong Kong01 Jan40%475%714%8-38%5
Hong Kong02 Feb4-75%1500%667%10-40%6
Hong Kong03 Mar40%4-50%2450%1118%13
Hong Kong04 Apr2100%4-50%2100%4-75%1
Hong Kong05 May6-83%1800%944%1346%19
Hong Kong06 Jun1916%2227%2818%3318%39
Hong Kong07 Jul1644%2330%303%31-13%27
Hong Kong08 Aug825%100%1070%1712%19
Hong Kong09 Sep4175%1118%1323%1650%24
Hong Kong10 Oct8-50%450%6-17%50%5
Hong Kong11 Nov30%367%560%8-13%7
Hong Kong12 Dec4-50%2200%6-67%250%3
New York01 Jan743%10
New York02 Feb1500%667%10
New York03 Mar2100%475%7
New York04 Apr9-11%8
New York05 May50%520%6
New York06 Jun5900%504%52
New York07 Jul15107%31-52%15
New York08 Aug80%875%14
New York09 Sep22-36%1414%16
New York10 Oct1127%1493%27
New York11 Nov6-33%40%4
New York12 Dec11000%11-9%10
Shanghai01 Jan5
Shanghai02 Feb5-60%2
Shanghai03 Mar4
Shanghai04 Apr2
Shanghai05 May6100%12
Shanghai06 Jun771%12
Shanghai07 Jul1613%18
Shanghai08 Aug580%9
Shanghai09 Sep250%3
Shanghai10 Oct5-60%2
Shanghai11 Nov5-60%2
Shanghai12 Dec6-50%3
Chicago
Chicago01 Jan2
Chicago02 Feb1
Chicago03 Mar1
Chicago04 Apr1
Chicago05 May1
Chicago06 Jun6
Chicago07 Jul5
Chicago08 Aug4
Chicago09 Sep3
Chicago10 Oct5
Chicago11 Nov2
Dublin01 Jan8
Dublin02 Feb7
Dublin03 Mar3133%7
Dublin04 Apr20%2
Dublin05 May80%8
Dublin06 Jun2596%49
Dublin07 Jul90%9
Dublin08 Aug4200%12
Dublin09 Sep1267%20
Dublin10 Oct838%11
Dublin11 Nov3
Dublin12 Dec20%2
Toronto01 Jan
Toronto03 Mar4
Toronto04 Apr1
Toronto05 May1
Toronto06 Jun7
Toronto07 Jul9
Toronto08 Aug1
Toronto09 Sep1
Toronto10 Oct2
Toronto11 Nov2
Toronto12 Dec5
Tokyo
Tokyo01 Jan5
Tokyo02 Feb2
Tokyo03 Mar5
Tokyo04 Apr
Tokyo05 May15
Tokyo06 Jun32
Tokyo07 Jul16
Tokyo08 Aug13
Tokyo09 Sep11
Tokyo10 Oct9
Tokyo11 Nov3
Tokyo12 Dec


Company wide year on year change per month

Month 2014 %change 15 2015 %change 16 2016 %change 17 2017 %change 18 2018
01 Jan3714%4219%5050%7533%100
02 Feb25-8%2361%3786%697%74
03 Mar27-52%13162%3418%4088%75
04 Apr1242%1776%3057%47-15%40
05 May58-36%3768%6223%7638%105
06 Jun13745%1989%21692%41422%506
07 Jul8246%12032%15853%241-6%226
08 Aug3727%4738%6520%7841%110
09 Sep4134%5567%9242%13126%165
10 Oct3281%58-5%5555%8526%107
11 Nov264%2759%4344%6237%85
12 Dec22-27%1656%2564%4110%45


Company wide year on year change per quarter

Quarter 2014 %change 15 2015 %change 16 2016 %change 17 2017 %change 18 2018
189-12%7855%12152%18435%249
220722%25222%30874%53721%651
316039%22242%31543%45011%501
48026%10122%12353%18826%237


Company wide year on year change per year

2014 %change 15 2015 %change 16 2016 %change 17 2017 %change 18 2018
53622%65333%86757%135921%1638


Company wide year on year change per year amd destination

Destination 2014 %change 15 2015 %change 16 2016 %change 17 2017 %change 18 2018
Chicago31
Colombia901%9116%10643%15213%172
Dublin7678%135
Hong Kong829%8939%12427%1586%168
London22816%26415%30338%417-3%406
Madrid10125%12619%15025%187-11%167
Melbourne35137%8330%1086%114-10%103
New York76114%16310%179
Shanghai5922%72
Tokyo111
Toronto33