Business Opportunities, Challenges, Strategies and Executions in Big Data Era--- A Case of Mobile Ads Big Data
Cases: Duolingo, Google now, Google Flu Trends, JawBone, AppDynamics, SnapLogic, DropCam, Netflix, Ayasdi, Automatic, Nest, Wealthfront, Zephyr Health, OpenGov
3R: Reach, Richness, Range
Business Opportunities, Challenges, Strategies and Execution in Big Data Era--- A Case of Mobile Ads Big Data
1. Big Data 的商機、挑戰、策略與執行
--- 以移動廣告大數據為例
Vpon 行動科技
數據科學家 趙國仁
Data Scientist Craig Chao
craig.chao@vpon.com, chaocraig@gmail.com
Business Opportunities, Challenges, Strategies and
Execution in Big Data Era
--- A Case of Mobile Ads Big Data
2. Prelog – Myths of Big Data
Big Data, Big Hype?
Machine Learning & Statistics have been used in
many places, nothing new in Big Data?
Big Data is Hadoop / Open Source?
3. Agenda
• Innovative Cases of BIG DATA
• What is the BIG DATA eventually?
• A Case of Big Data in Mobile Ads
• Yes! We have lots of DATA?!
• Big Data is not only about Technology
but also Org.+Culture+Eco-system
• Summary
10. Outlook of Big Data
Hard to be handled by traditional RDB/SQL DB
Sources
Intranet:Machine logs
Extranet:Internet users & machines
Difficult to be utilized by only statistical sampling
“If you have people in the loop, it’s not real time.”
Joe Hellerstein, Chancellor’s Professor of
Computer Science at UC Berkeley
12. The Revolution of Big Data
DATA
Hypotheses
Statistical Analysis
BIG DATA
Hypotheses
Machine Learning
Data Mining
Machine-generated
Sampling, Multi-variant… All, Hyper space, …
Volume, Velocity, Variety, Veracity
Human-explainable
15. Mobile Big Data in Vpon
• Profile
• Classification
• Recommendation
Retargeting
2B+ in China
6M+ in HK
17M+ in TW
User Behavior Data Mine
20GB/day
20TB/year
MLDM to mine the data value
23. 3R: Reach, Richness, Range
Reach
Richness
High
High
Low
使用者接觸量(DAU)
資料豐富度
(Behavioral data)
Range
High
使用者情境
(The audience
affiliate of
whole context)
24. Data Economy
Traditional -> Internet Economy
HighREACH
RICHNESS
High
Low
Traditional Economy
Internet Economy
(quality)
(quantity)
25. Reach: The Value Funnel
CPM campaign:
Revenue = N/1000 ⋅CPM
CPC campaign:
Revenue = N ⋅ CTR ⋅ CPC
CPA campaign:
Revenue = N ⋅ CTR ⋅
CVR⋅ CPA
UU Reach (DAU)
ARPU = Life-time Value
30. Range
- Roger Martin
Rothman School of Management, Toronto
If only attach importance to quantify the business
model, it will not have the ability to find a potential
growth opportunities: "The pursuit of quantifying the
biggest problem is that people ignore the context of
the behavior generated, detached from the context of
the event, and have not been included in the model
ignores variables effectiveness. "
企業若只重視量化模式,
將無法擁有尋得潛在成長
契機的能力:「追求量化
最大的問題在於,忽略人
們產生行為的脈絡,把事
件從情境中抽離,且忽略
沒有被納入模式中的變數
效力。」
34. 成功案例:掌握3R成效更優異!
Cross-screen synergy
Big data synergy with Cross-screen effect。
+TV
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
16.00%
0
5000
10000
15000
20000
25000
30000
35000
40000
Thu Fri Sat Sun Mon Tue Wed Thu Fri Sat Sun
APP下載率 優化轉換率
App Download Rate Optimized Conversion Rate
35. 3R: Reach, Richness, Range
Reach
Richness
High
High
Low
使用者接觸量(DAU)
資料豐富度
(Behavioral data)
Range
High
使用者情境
(The audience
affiliate of
whole context)
38. Big Data is not only about
Technology but also
Org. + Culture + Eco-system
39. Challenges of Big Data Company
Tools
Commercial Big Data Tools is Expensive
Open Source Tools need high-skill talents
Organization
Performance metric of developers
Most people do not understand 3R of data
Data BD, Campaign Manager, Data Engineer,
Data Scientist
Time
Accumulate behavioral data, Tuning models, Org
& Culture changes
40. Challenges of Big Data Company
BDSales + AS
Sales + CM
Data BD
Data Engineer +
Data Scientist
Conversions +
3rd Tracking