際際滷

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Social Media Analytics
Challenge and Case Studies
Big Data Engineering, DPU
Global Usage of
Social Media Analytics
Big Data Engineering, DPU
PNERN ASAVAVIPAS (Nern)
CEO & Co-Founder
@ OBVOC
Education
- B.A. Economics, Thammasat University
Experiences
- 6 years in Social Listening & Analytics
What is Social Media Analytics?
Social
Listening
Social
Analytics
Social
Intelligence
Capturing
words
Analyzing Data &
Discovering Insights
Actioning Insights
Nespresso
Using Social Insights to Build a Global Marketing Strategy
Consumer Insights from Co鍖ee Drinking Discussion on Social
Source: Crimson Hexagon
Customer Insights through Audience Competitive Analysis
Source: Crimson Hexagon
Nespresso
Implementation & Tracking
How data contribute Marketing Strategy
Source: Crimson Hexagon
Commercial
Advertising
Events and
Pop Up Store
Sponsorship
Commercial Advertising
Source: Crimson Hexagon
Penelope Cruz - Actress
Lana Del Rey - Singer
Penelope Cruz - Nespresso TV Commercial, Song by Lana Del Rey
Developing Marketing Strategy Based on Insights
Developing Marketing Strategy Based on Insights
Developing Marketing Strategy Based on Insights
Nespresso
Monitoring & Learning From Marketing Efforts
Measuring the E鍖ect of Marketing E鍖orts
Brand Perception: Advocacy Intent to Purchase
Brand
Perception:
Positive
Reputation
Brand
Perception:
Negative
Reputation
Marketing E鍖orts
Source: Crimson Hexagon
Measuring Consumer Exposure to the Brand
Opening of Nespresso boutique
store in San Francisco
Airing of commercial featuring
Penelope Cruz and Lana Del Rey
Beginning of Pop Up events at
Americas Cup, SXSW, and cities
throughout the US
Source: Crimson Hexagon
Measuring Consumer Exposure to the Brand
Source: Crimson Hexagon
Measuring Consumer Exposure to the Brand
Source: Crimson Hexagon
Identifying Key Areas of Success
Source: Crimson Hexagon
Driving Consumer Purchase Intent
The pop-up events increasing from 3% to 21% over the same time period.
Source: Crimson Hexagon
Key Takeaway
Source: Crimson Hexagon
With actionable insights, Nespresso could learn from a targeted campaign, monitor e鍖orts to learn what
marketing events worked and engaged their target audience, and build a global strategy for the future.
As with Nespresso, social insights enable any brand or agency to:
1. Know where to reach new and relevant customer segments and what messaging will most
e鍖ectively engage them.
2. Track speci鍖c campaign e鍖orts and customer interaction with them, to know what worked.
3. Categorize and measure customer interaction to learn about brand perception, method of
exposure, and future opportunities for engagement.
4. Identify key areas of success and quantify return on investment through changes in intent to
purchase and competitor benchmarking.
Social Media Analytics Challenges and Case Studies
Social Media Analytics Challenges and Case Studies
Social Media Analytics Challenges and Case Studies
Social Media Analytics Challenges and Case Studies
Social Media Analytics Challenges and Case Studies
Social Media Analytics Challenges and Case Studies
Process & Implementation
Big Data Engineering, DPU
PUTTASAK TANTISUTTIVET (TOR)
Senior Data Research Analyst
@ THOTH ZOCIAL
Education
- B.Sc. Electronics Engineering, KMITL
- M.Sc. Business Administration (Marketing) , NIDA
Experience
- Social media strategy
- Digital Project Planner
- Content Strategy
- Data Research and Analyst
- Speaker @Young Data Scientist, J.Walter Thomson,
Nitade Chula
Social Media Analytics Challenges and Case Studies
Data Team
Data Team = Chef
Chef
Raw Material Cooking Decorate and Serve
Data Team
Data Collecting
(Raw Material)
Data Processing
(Cooking)
Delivering Insight
(Decorate and Serve)
- NLP
- Text Mining
- Categorize
- Cleansing Data
- Association Rule
- Correlation
- Classification
- Clustering
- Timeline Analysis
- Data Warehouse
- Database
- Sourcing
- Social Media
- Data Hacking
- Tools
- Presentation
- Paper
- Research
Social Media Data Process
Delivering InsightData Collecting Data Processing
Social Media Data Process
Delivering InsightData Collecting Data Processing
2.5 Billion Talks
On 2016
~ 5 Million Talks every day
~ 5,000 Talks every minute
~ 80 Talks every second
Data Collecting.
- Millions Millions message per month (and Very fluctuate)
- Depend on platform, Always Change!
- Junk Source and Data
- Data Limitations
- Both Structure and Unstructure Data
- Varieties type of Data (Text, Video, Image, Numbers)
- Coverage VS Accuracy
Social Media Data Process
Data Collecting Data Processing Delivering Insight
Data Processing.
- Natural language
processing
- Text Mining
- Cleansing Data
- Categorize
- Association Rule
- Correlation
- Classification
- Clustering
- Data Modeling
NLP Procedure
Data
(input)
Word
segmentation
Feature
extraction
Weight
optimization
Results
(output)
Classification
 Word
 Sentence
 Paragraph
 Document
 Tokenization
 Part-of-speech tagging
 Binary
 Numeric
 Bag-of-words (BOWs)
 TF-IDF
 Sub-words (prefixes,
suffixes)
 etc.
 Supervised learning
 Machine learning
 Unsupervised learning
 Clustering
 Target output
 Sentiment score
 Opinion
 Keywords
 etc.
Social Media Data Process
Delivering InsightData Collecting Data Processing
Data interpretation.
犖犖ム険犖犖犖迦犖犖犖犖犖犖犖ム険犖犖÷顕 犖犖項犢犖犖犖劇犖犖犖犖巌犖犖犖犖犖伍犖犖項犖∇鹸犖
犖犖犖伍犢犖ム鍵犖÷元犖犖犖犖犖巌犖犖犖犖犖ム険犖犖÷顕犢犖犖犖犖謹犖犖犖犖謹犖 犖犖犖
犖犖犖犖犖犖犖犖園犖犖犖犢犖犖犖伍犖犖萎犖犖犖巌検犢犖犖犖迦鍵犢犖犖犖園犖犖о犢犖
犖犖犖犢犖犖犖劇犖犖犖犖巌?
犖 ) 犖犖о犖犖朽犖犖項犖∇鹸犖犢犖∇賢犖
犖) 犖犖о犖犖朽犢犖¥犖犖項犖∇鹸犖

Turn Data into
Value Information
Social Media Analytics Challenges and Case Studies
- Text
- Image
- Video
- Time
- Location
- Engagement
- Etc.
- Segmentation
- Interested
- Behaviors
- Trend
- Attitude / Perceptions
- Unknown Insight
Data interpretation.
Data interpretation.
Data interpretation.
Challenge: Social Media Data
Big Data Engineering, DPU
Social Media Data
is
Junk VS Accuracy
Crawled Data
iPhone 7S
iPhone7S
iPhone7 S
iPhone 7S
犢犖犢犖犖7s
犢犖犢犖犖 7s
犢犖犢犖犖 7s
犢犖犢犖犖7 s
犢犖犢犖犖7s
犢犖犢犖犖 7s
.
.
.
Huawei P9 Plus
5*2*3*2*2 = 120 Keywords
Subject
(Huawei | 犖犖園硯犢犖犖э犖≒ | 犖犖園硯犢犖э犖≒ | 犖犖園硯犢犖犖э犖≒)
&
(P9plus | P9 plus | P9+ | 犖犖9)
Social Media Data
is
World of ASSUMPTION
Mobile Voice | Assumptions
- Voice 犖犖犖犖ム犖犖萎犖犖犖犖犖о顕犖÷賢犖∇顕犖犖犖劇犖犖犖犖 Users 犢犖犖?
- 犖犖犖犖犖迦犢犖犖ム鍵犖犖犖犖犖迦 犖÷元犖犖ム犖犖萎犖犢犖犖迦犖園犢犖犖?
- 犢犖犖迦犖犖犖迦鍵 Users 犢犖犖犖 犖犖犖劇賢犢犖犖迦犖朽 Page 犢犖犖犖犖犖о権?
- 犖犖犖犖迦権犖犖項犖犖謹犖 IG 犢犖ワ犖о犖 #Huaweip9 犖犖萎犖園犢犖犖?
- 犖犖迦牽犖犖朽犖犖犖犖項犖э犖迦犖朽犢犖ム犖園肩犖犖朽犖迦権 = 犢犖犖萎犢犖迦犖犢犖犖犖劇犖犢犖犖÷見犖犖劇賢犢犖犖犖犖?
- 1 犖犖犖犖о顕犖÷検犖朽犖迦牽犖犖項犖犖謹 2 犖犖醐犖 犖犖萎犖園犢犖∇犖犖園犖犖犖劇賢犖犖園犖犖о検
- 1 犖犖犖犖о顕犖÷犖朽犖犖項犖犖謹 Feature 犖犖迦犢 犖犖萎犖園犢犖∇犖犖犖劇賢犖犖園犖犖о検
- 1 犖犖犖犖о顕犖÷犖朽犢犖犖犖園 Engagement 犖犖萎犖犖ム犖о顕犖÷見犖÷顕犖∇犖犖 Engagement 犖∇険犖犢犖犖犖?
Social Media Data
is
Thai Culture and Lang is not easy
Beautiful of Thai Lang
Beautiful of Thai Lang
Social Media Data
is
Limitations
Social Media Data
is
Not fit for all
Brief
- 犖犖∇顕犖犖о険犖犢犖犖犖犖巌犖犖犖犖犖犖朽硯犖朽犖 Social Media
Social TV Rating
- Data 犖犖伍犢犖犖犖犖 Social Media 犖犖朽犢犖犖犖犖園硯犢犖犖犖犖犖 Rating?
- 犖犖 Video View?
- 犖犖 Voice 犖犖朽犖犖項犖犖謹犖犖迦権犖犖迦牽犖犖園犖?
- 犖犖 Engagement 犖犖 Video?
- 犖犖園犖犖о顕犖÷肩犢犖迦犖園犖犖萎見犖э犖迦犖犖犖÷弦犖ム犖犖 Live Video 犖犖園 VOD 犖∇険犖犢犖?
- 犖犖萎犖犖犖 FB Video 犖犖犖劇賢 Youtube Video 犖犖犖劇賢犖犖о検犖犖園?
- Facebook Live 犖犖劇賢 Time Base 犖犖犖劇賢 VOD?
- 犖犖萎犖犖 Voice 犢犖犖 Rating 犖犖犖劇賢犢犖犖 Amplifier?
- 犢犖ワ犖 Sentiment 犖犖ム鍵??
- 犖犖迦犖迦犖犖迦犖¥犖犖迦検犖迦牽犖犢犖犢犖犢犖
Social TV Rating
3 Sec = 1 Views 30 Sec = 1 Views
Challenge:
Business Stakeholder
Big Data Engineering, DPU
Expectation Reality
Social Media Analytics Challenges and Case Studies
Its CONFIDENTIAL!
Jargon!
Social Media Analytics Challenges and Case Studies
How to prevent?
Upper-level
User
MorePower&
Unapproachable
Middle-level
Start with small and Build Trust
Business Expertise
1. Engage with higher position as much as you can.
2. Start with small and build their trust.
3. Be careful your jargon words.
4. Keep learning on your fields.
5. Talk less and show more.
Key Takeaway
Enjoy Analyzing!
Case Studies
Big Data Engineering, DPU
Ways to apply Social Media Data
犖犖÷犖
犖犖
犖犖迦犖
犢犖犖犖犖
Use Correlation Technique
MOMs Insight
Ways to apply Social Media Data
Answer : 33% 犖犖劇犖, 31% 犖犖, 21% 犢犖犖巌, 21% 犖犖巌
Store Visit #1 : {  犢犖 + x ... store } (Use Association Technique)
Question : 犖ム弦犖犖犖迦犖犖犢犖迦賢犖萎犖犖犖朽犖o犖迦?
Solution : Listen & Extract only talks about store or check-ins at store.
Identify 犢犖 and adjacent keyword.
Ways to apply Social Media Data
Store Visit #2 : {  犢犖 + 犖犖劇犖 + x ... store }
Question : 犖ム弦犖犖犖迦犖 犖犖劇犖犖犖萎犖犖犖朽犖o犖迦?
Solution : Listen & Extract only talks about store or check-ins at
store. Identify 犢犖+犖犖劇犖 and adjacent keyword.
Answer : 12% 犢犖犖, 10% 犢犖, 77%
Ways to apply Social Media Data
Store Visit #2 : {  犢犖 + 犖犖劇犖 + x ... store }
Question : 犖ム弦犖犖犖迦犖 犖犖劇犖犖犖萎犖犖犖朽犖o犖迦?
Solution : Listen & Extract only talks about store or check-ins at
store. Identify 犢犖+犖犖劇犖 and adjacent keyword.
Answer : 12% 犢犖犖, 10% 犢犖, 77% 犢犖¥
Ways to apply Social Media Data
犢犖犖
犖犖о顕犖
犖犖ム賢犖犖犖園権
Condo Insight
Ways to apply Social Media Data
犢犖犖
犖犖о顕犖
犖犖ム賢犖犖犖園権犢犖÷元犖Condo Insight
Ways to apply Social Media Data
犖犖犖迦犖迦 XXX
Followed by
Superstar name
Ways to apply Social Media Data
Ways to apply Social Media Data
1
2
Kumamoto > Fukuoka > Nagasaki
Fukuoka > Kumamoto > Mountain Aso
1
2
Mountain Aso > Kumamoto > Fukuoka
Fukuoka
Kumamoto City
(Castle, Suizenji, etc.)
Travel Behavior
Ways to apply Social Media Data
Event Analysis
Ways to apply Social Media Data
Event Analysis
Ways to apply Social Media Data
Precisions Ads
Ways to apply Social Media Data
Traditional Ads Targetings Ads Personalized Ads
Improve way to advertising
Ways to apply Social Media Data
CHATBOT
Application and interface (Input)
Natural language processing (NLP)
Intelligent search
BOT knowledge
Keyowords/Pattern matching and sorting
Ontology PlatformDictionary
Conversational AI
Ways to apply Social Media Data
Sarcasm Prediction
犖犖迦犢犖э犢犖犖犖巌肩犖.
- 犖犖巌犖犖犖朽犖犖∇顕犖犖犖朽犖犖伍犖犖犖犖犖迦牽犖犢犖迦犖迦犖犖犖÷弦犖ム犖劇賢犖犖迦牽犢犖¥犖÷元犖犖犖÷弦犖
- 犖犖迦牽犖犢犖迦犖迦犖犖園 Data 犖犖犖犢犖犢犖о献犖, 犖犖犢犖犖巌犖!
- 犖犖迦犖犖園犖犖萎犢犖迦犖迦犖犖迦犖犖朽犖犖犖巌 犖犖犖迦牽犖園犢犖犖朽権犖犖犖迦牽犢犖犖 犖犖迦牽犢犖犖犖犖犖÷弦犖モ
- 犢犖¥犢犖犖犖伍犖犖犖犖朽犖犖迦検犖迦牽犖犖犖園犖犖迦犖園硯犢犖犖犖犖犢犖犖犢犖犖犖伍犖犖迦
- 犢犖¥犢犖犖犖伍犖犖犖犖朽犖犖萎犖犖迦犖犢犖ム鍵犖犖犖 Data
- Data 犢犖¥犢犖犢犖о犖犖÷犖
犢犖犢犖犖 犖犖 犖犖迦犖犖迦犖犖朽犢犖 Data 犢犖犖劇犖犖犖o犖迦犢犖о犖犖÷犖
Social Media Analytics Challenges and Case Studies
THANK!
Social Media Analytics Challenges and Case Studies

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Social Media Analytics Challenges and Case Studies