Ticketing Technology Forum - Opportunities for ticketing and event technology

1. cloud technology

2. in a mobile first world
cloud is the default

3. the cloud democratizes
access to scale & reach

4. ticketing company scales to sell
150,000 tickets in 10 seconds
http://azure.microsoft.com/en-us/case-studies/customer-stories-flavorus/

5. reliability and elasticity at scale
a new level of abstraction
from servers to datacenters

7. platform gives instant access to innovation
no need to deploy updates

9. managing user identity
no more username and password - PLEASE!
use established identity providers instead

10. push notifications
integral part of modern applications

11. unique token per device and app
persist, refresh and retrieve millions of tokens
challenge - registration management

12. 1 millisecond to send an async notification
~16 minutes to send 1 million notifications
~32 servers to send them within 30 seconds
challenge - time to deliver message

13. personalized per user and/or device
language, message format, visuals
metrics (currency, temperature, length))
challenge - message personalization

14. users/apps subscribe to topics
only interested in rugby and tennis events
and only when taking place in the UK or US
challenge - message routing

15. notification hubs are @ your service
highly scalable pub/sub based cloud service

16. Android app
iOS app
{
aps: {
alert: "$(msg)"
}
}
notification hub
{
"data" : {
"msg" : "$(msg)"
}
}
app
back-end
hub.send(“
{msg: “hello”}
”);

17. Android app
iOS app
{
aps: {
alert: "hello"
}
}
notification hub
{
"data" : {
"msg" : “hello"
}
}
app
back-end
hub.send(“
{msg: “hello”}
”);
apns
gcm

18. Android app
iOS app
{
aps: {
alert: "$(msg_GE)"
}
}
notification hub
{
"data" : {
"msg" : "$(msg_EN)"
}
}
app
back-end
hub.send(“
{msg_EN: “good morning”}
{msg_GE: “guten Morgen”}
”);

19. Android app
iOS app
{
aps: {
alert: “guten Morgen"
}
}
notification hub
{
"data" : {
"msg" : “good morning"
}
}
app
back-end
apns
gcm
hub.send(“
{msg_EN: “good morning”}
{msg_GE: “guten Morgen”}
”);
good
morning
guten
Morgen

21. proximity based interactions
make interactions relevant through
location and time

22. notify customer about offerings in real-time
e.g. 20% voucher for food/merchandising
triggered by queue length
valid for 5 minutes

23. stream analytics
transformingest
beacon triggered
by device proximity
notify
event hubs
store in table
storage for further
analytics
use
machine learning
to predict the most
suitable
voucher/offering
notify customer
about voucher
using push
notification
storage predictive analytics
event & data
producers

24. monitor and analyze attendee flow
create heat maps using time series of data
improve location layout for future events

27. predictive assistant
make predictions personal

31. predictive analytics
predictions based on models

33. ask the right question!
when will the event sell-out?
versus
what is the probability that the event is sold
out within the next 2 weeks?

34. sales predictions
clustering events (e.g. frequency, day/month)
customer clusters (e.g. booking behavior)
geo event calendar (e.g. similar events)
social (e.g. tweet sentiment/frequency)

35. use of stream analytics to detect patterns
buying volume increase/decrease
abandoned shopping carts
tweet volume/sentiment

36. dynamic pricing
ml to predict optimum pricing per category
proximity based incentives
stream analytics triggers re-pricing

37. use stream
analytics to trigger
re-pricing
transformingest
beacon triggered
by device proximity
notify
event hubs
store in table
storage for further
analytics
use
machine learning
to re-price
categories
update prices in
sales portal
storage predictive analytics
event & data
producers
sales data
social data
dashboard
notify subscribers