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Ray Poynter, The Future Place – JMRX Lectures 2015
第1回
2015.4.28
19:30-21:30
What’s Hot in
Market Research?
レイ・ポインターの
白熱教室2015
盛況でした。
嬉しくなってこんなの
つくっちゃいました。
Tomoko Yoshida
当日のスライドはこちらです
Ray Poynter, The Future Place – JMRX Lectures 2015
What’s Hot in Market Research?
Ray Poynter
The Future Place
JMRX – Tokyo – April 28, 2015
Now &
The near future
Ray Poynter, The Future Place – JMRX Lectures 2015
Still Hot
Hot
Bubbling
What About?
Interaction Time
Ray Poynter, The Future Place – JMRX Lectures 2015
Still Hot
Ray Poynter, The Future Place – JMRX Lectures 2015
Mobiles in Traditional Research
CATI
GRIT Number 1
Ray Poynter, The Future Place – JMRX Lectures 2015
Communities
GRIT Number 2
Ray Poynter, The Future Place – JMRX Lectures 2015
DIY
DIY  Automation
Ray Poynter, The Future Place – JMRX Lectures 2015
Comm-
unities
Still Hot
Efficacy
Scalable
Mobiles in
Trad. MR
DIY
Ray Poynter, The Future Place – JMRX Lectures 2015
Hot
Ray Poynter, The Future Place – JMRX Lectures 2015
In the Moment
Ray Poynter, The Future Place – JMRX Lectures 2015
Location-based Research
Ray Poynter, The Future Place – JMRX Lectures 2015
Micro Surveys
Ray Poynter, The Future Place – JMRX Lectures 2015
Automation
Ray Poynter, The Future Place – JMRX Lectures 2015
Hot
Efficacy
Scalable
In the
moment
Micro
Surveys
Auto-
mation
Location
Ray Poynter, The Future Place – JMRX Lectures 2015
Bubbling
Ray Poynter, The Future Place – JMRX Lectures 2015
Text Analytics
Text
Analytics
Sentiment analysis
Inbound comms analysis
Reaction marketing
Service delivery
Analysis of open-ended data
Bots
Ray Poynter, The Future Place – JMRX Lectures 2015
Web Messaging
February 2014
$19billion
Ray Poynter, The Future Place – JMRX Lectures 2015
Research Bots
John Griffiths
Ray Poynter, The Future Place – JMRX Lectures 2015
Social Media Research
I agree most SMR has under delivered, but my
company are doing it right.
1. Social is widely used, but to a much smaller extent
than was forecast – in MR
2. Most clients I have spoken to have scaled back
their SM stuff – within MR
3. Social answers questions we never asked – good,
but there is not always a demand for those
4. Social is usually bad at answering clients’ MR
questions
Ray Poynter, The Future Place – JMRX Lectures 2015
BT Case Study
Ray Poynter, The Future Place – JMRX Lectures 2015
BT Case Study
• BT have identified that Net Easy is a key metric in
reducing churn
• DebateScape trawls social media for relevant
conversations
– Finding relevant comments and treating as CRM in a
workflow situation
– Also delivers key metrics
• ROI?
– £2 million cost reduction, per year
– 600,000 contacts dealt with via social, instead of voice
Ray Poynter, The Future Place – JMRX Lectures 2015
Bubbling
Efficacy
Scalable
Text
Analytics
Research
Bots
Web
Messaging
Social
Media
Ray Poynter, The Future Place – JMRX Lectures 2015
What About?
Big Data
Passive Data
Behavioural Economics
Gamification
Neuroscience
Smartphone Ethnography
Biometrics
Facial coding
Geotracking
Wearables
Quantified Self / Life Logging
Ray Poynter, The Future Place – JMRX Lectures 2015
What About?
Efficacy
Scalable
Big Data
Passive
Data
BE
Gami-
fication
Neuro-
science
Mobile
Ethno.
Ray Poynter, The Future Place – JMRX Lectures 2015
What About?
Efficacy
Scalable
Big Data
Geo-
trackingWearables
QS, LL
Facial
Coding
Ray Poynter, The Future Place – JMRX Lectures 2015
Beyond MR?
Ray Poynter, The Future Place – JMRX Lectures 2015
THANK YOU
Q & A
Ray Poynter, The Future Place – JMRX Lectures 2015
The Next Five Years - Global
Automation will change
– Survey design
– Project management
– Reporting
– Video analysis
– Social media analytics
– Big data analytics
– Text analytics
– Online qual moderation
– MROC management
What are the
implications
for Japan?
Ray Poynter, The Future Place – JMRX Lectures 2015
Automation and the Implications for Japan
Strengths Weaknesses
Opportunities Threats
レクチャーももちろんすばらしかったけれど、
その直後(というか、リアルタイムで)、
FBでDragonflyさんが
こういう投稿をしてくださったことで、
もっともっと素敵になりました。
該当する(と思われる)
スライドと並べてみます。
Ray Poynter先生、ありがとうございました。
Dragonflyさん、ありがとうございました。
通訳してくださったクロダさん、ありがとうございました。
ご参加くださったみなさん、ありがとうございました。
次回は5月12日(火)またお会いいたしましょう。シノプシスはこちらです。
【ビッグデータと先進アナリティクス】
ビッグデータとは何か? ビッグデータは何をしてくれて、何をしてくれないのか、実例をあげながら紹介します。たとえば
今、Predictive Analytics (※調べてみたけど、オーソライズされている日本語はちょっと見つからないのでとりあえ
ずそのまま)が注目を浴びています。果たして、この人気の正体は何なのか、 Predictive Analyticsでどのようなこ
とがわかるか、同時に、その限界や課題などについて、解説します。
フリーランスモデレイター 吉田朋子より

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