[Vietnam Mobile Day 2013] - Business intelligence driven marketing

Business Intelligence Driven Marketing
©Copyright 2013-2014. Spicy Cinnamon Pte. Ltd

Introduction
Alex Sung
• Technical Lead at eBay
• Sr. Product Manager at GREE International
• CTO at Spicy Cinnamon

Focus Today
Contents
• Identifying Key Performance Indicators (KPI)
• Designing an Analytics Platform
• What’s next & other notes

KPI

KPI
Topics
• Purpose
• Overview
• Important KPI’s
• Segmentation

KPI - Purpose
KPI’s evaluate the health of your product and your
business. 3 categories:
• Acquisition
• Engagement
• Monetization
Goal: final cost per user is less than final life time
value of user

KPI - Overview
Acquisition Engagement Monetization
• Cost (per user)
• Cost-per-impression (CPI)
• Cost-per-click (CPC)
• Cost-per-install (CPI)
• # Impressions
• # Clicks
• Click-through-rate (CTR)
• # Downloads
• # Installs
• # Activations
• Conversion (CVR)
• K-factor (Virality Rate)
• DAU
• MAU
• Stickiness (DAU/MAU)
• Retention Rate (RR)
• Session Length
• Life Time (LT)
• Product-specific
• Spending DAU
• Spend Amount
• ARPU
• ARPPU
• ARPDAU
• Life-time Value (LTV)

KPI - Overview (Today)
Acquisition Engagement Monetization
• Cost (per user)
• Cost-per-impression (CPI)
• Cost-per-click (CPC)
• Cost-per-install (CPI)
• # Impressions
• # Clicks
• Click-through-rate (CTR)
• # Downloads
• # Installs
• # Activations
• Conversion (CVR)
• K-factor (Virality Rate)
• DAU
• MAU
• Stickiness (DAU/MAU)
• Retention Rate (RR)
• Session Length
• Life Time (LT)
• Product-specific
• Spending DAU
• Spend Amount
• ARPU
• ARPPU
• ARPDAU
• Life-time Value (LTV)

KPI - K-factor (Virality)
Value:
• A measure of how virally effective or social the app is
• More viral = less cost to hit # Installs KPI
• Longer app life time
Definition:
• K = # invites & conversion rate (1 = status quo)
Suggestions:
• Social network integration (FB, Twitter connect)
• Competitive or cooperative systems (raids, trading)
• Friend codes
• Invitation incentives (HC, speed-up’s)

KPI - Retention Rate (RR)
Value:
• Indication of how well the app keeps users returning
• More returns = longer user life = more monetization
• Highly targetable cohorts
Definition:
• Day0 = First time activated users on specific date
• DayX RR = # users from Day0 return / # Day0 users
• Day0 is constantly rolling (every day is a new Day0)
• Day1-14 RR most indicative of user behavior
• Followed by Day30, 60, 90
• View DayX RR as trending or averaged over data points
• Averaging Day30 RR requires 2 months

KPI - Retention Rate (RR) continue
Suggestions:
• Good product and useful service
• Virality – friends are on it
• New content (whether by developers or active community)
• Incentivized returns (HC)
• Special events (discounts, raids, limited time)
• Push notification reminders

KPI - Life-Time Value (LTV)
Value:
• Ultimately, how much revenue each average user provides
Definition:
• Simple, ARPDAU * LT (estimate LT based on RR)
• Most popular, usually assume 30-Day LTV
• Strict, create cohort for first time users for each day for LT
# of days. Track & sum up IAP for each user. Average
across cohorts.
• Difficult to define: are users that provide community
content or are virally active part of value?

KPI - Life-Time Value (LTV) continue
Suggestions:
• Improvement to RR & worth paying service / product
• Discount events to IAP
• Strong visual indicators (juicy feedback)
• Provide enough access points to IAP
• Provide enough options for IAP
• There are high-rollers, provide options for them
• Allow pay-to-speed-up
• Special expression based VG
• Do not allow pay-to-win; risk of damaging community

KPI - Segmentation
Time Acquisition Monetization
• First-time users
• New vs Existing (30-days)
• Cumulative vs Daily
• Hardware
• Model
• Manufacturer
• OS Version
• Marketplace
• Ad Network
• Campaign
• Creative
• Incentivized vs non
• Invitation
• Organic
• Geo-location
• Language
• Spenders vs non-spenders
• One-time spenders
• SC vs HC vs real-cash
• Age
• Gender
• Ethnicity
• Occupation
Platform Location Demographic

Analytics Platform

Analytics Platform
Topics
• Data Collection & Integration
• Data Engine & Big Data Processing
• Visualizations & Services

Data Collection & Integration
Ad NetworksClients
App Engine
Data Collector
Analytics
Logger
Raw Data
Ad Network
SDK
API
Integration
Client SDK
• Client-side SDK’s simpler to integrate
• Some Ad Networks provide analytics
• SDK’s must be scheduled in release
plan
Server API
• API provides scheduling flexibility
• Requires client to send uniqueness
and segmentation data
Data Collector
• Store uniqueness, segmentation, &
event data
• Collect application data via web log
scraping
• Collect Ad Network raw data for
acquisition to engagement mapping
• Sends collected analytics data to Data
Engine for processing

Rules EngineJob Status
Tracker
Scheduling Framework
Validation Framework
Notification Framework
Data Engine & Big Data Processing
ETL
Pig / Hive
Intermediate
Events(HDFS)
Segmentation
Buckets(HDFS)
Big Data Processing
(Hadoop Cluster)
Summary
Containers
Aggregated Storage
Data Collector
Workflow Engine
Analytics
Data
Hadoop
• Intermediate data storage as
files
• HDFS custom data mining
• Scheduled ETL to process
summarized data
• Workflow Engine to manage
Hadoop jobs
Aggregated Storage
• Summary data stored in RDBMS
• Connected to Visualization tools
Real-Time
• Not everything, identify critical
KPI and segmentations
• Revenue
• # Sessions
• Enterprise solutions:
Vertica, Teradata

Visualizations & Services
Dashboards
• Pictures are worth a thousand words
• Tell a story
• Reporting is only valuable if it is
actionable (avoid vanity reporting)
• Standardized KPI reporting for
business health
Services
• Funnel analysis & A/B testing for
product
• Alerts & notifications for engineering
• Sudden drop in # sessions means
app engine may be down
• Visual data mining
Tools & Tech
• 3rd party: Tableau, Microstrategy
• HTML5 for web and mobile support

What’s Next

What’s Next
Ad Networks
• Obtain internal raw data
• Vendor reporting cannot always be trusted
• Cohort to find channels with high-quality users
• Strategize between burst vs consistency
marketing campaigns
• Normalize channel data

What’s Next continue
Engagement
• Acquiring users is expensive
• Focus on Live Ops for re-engagement
• Provide fresh content
• Provide community and discount events
• If you support multiple apps / games
• Cross-Promote (X-Promo) at end of user life
• Be careful to not self-cannibalize

Thank You
AiTi-Aptech & Vietnam Mobile Day 2013
We are HIRING!
alex@cinnamon.is thao@cinnamon.is
http://tinyurl.com/Seconds-Photo-Chatroom

[Vietnam Mobile Day 2013] - Business intelligence driven marketing

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