cloud technology

in a mobile first worldcloud is the default

the cloud democratizesaccess to scale & reach

ticketing company scales to sell150,000 tickets in 10 seconds

http://azure.microsoft.com/en-us/case-studies/customer-stories-flavorus/

reliability and elasticity at scalea new level of abstractionfrom servers to datacenters

platform gives instant access to innovationno need to deploy updates

managing user identityno more username and password - PLEASE!use established identity providers instead

push notificationsintegral part of modern applications

unique token per device and apppersist, 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, visualsmetrics (currency, temperature, length))

challenge - message personalization

users/apps subscribe to topics only interested in rugby and tennis eventsand only when taking place in the UK or US

challenge - message routing

notification hubs are @ your servicehighly 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

gutenMorgen

proximity based interactionsmake interactions relevant throughlocation and time

notify customer about offerings in real-time e.g. 20% voucher for food/merchandising

triggered by queue lengthvalid 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 analyticsevent & data

producers

monitor and analyze attendee flowcreate heat maps using time series of dataimprove location layout for future events

predictive assistantmake predictions personal

predictive analyticspredictions based on models

ask the right question!when will the event sell-out?versuswhat 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 patternsbuying volume increase/decreaseabandoned shopping carts tweet volume/sentiment

dynamic pricingml to predict optimum pricing per categoryproximity based incentivesstream 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 analyticsevent & data

producers

sales data

social datadashboard

notify subscribers