Ticketing Technology Forum - Opportunities within cloud technology

Mar 19, 2015Download as pptx, pdf

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Cloud technology provides on-demand access to scalable computing resources and services. It allows applications to easily scale to meet demand, such as a ticketing company handling the sale of 150,000 tickets in 10 seconds. Platforms in the cloud provide instant access to innovation without requiring on-premise updates and enable reliable and personalized services like push notifications across devices. Analytics of event data streams can predict demand and improve customer experiences through dynamic pricing and proximity-based offers.

Technology

in a mobile first world
cloud is the default

the cloud democratizes
access to scale & reach

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

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

Ticketing Technology Forum - Opportunities within cloud technology

platform gives instant access to innovation
no need to deploy updates

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

push notifications
integral part of modern applications

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

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

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

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

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

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

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

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

proximity based interactions
make interactions relevant through
location and time

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

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

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

predictive assistant
make predictions personal

predictive analytics
predictions based on models

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?

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)

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

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

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

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Ticketing Technology Forum - Opportunities within cloud 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

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Ticketing Technology Forum - Opportunities within cloud technology

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