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Deep dive // November 24th 2015 ARTIFICIAL INTELLIGENCE IN MARKET RESEARCH Discussing 2 case studies Tom De RuyckManaging Partner Steven DebaereData Scientist
CONFERENCE TALK DEEP LEARNING MACHINE LEARNING AUTOMATION PATTERN RECOGNITION …. PREDICTIVE ANALYTICS BIG DATA ARTIFICIAL INTELLIGENCE | @tomderuyck @steven_debaere | @InSites
HYPES? extravagant or intensive publicity or promotion hype (Oxford dictionary) | @tomderuyck @steven_debaere | @InSites
UMBRELLA TERM Artificial Intelligence is the broader concept of machines being able to carry out tasks in a waythatwewouldconsider « smart » (Bernard Mahr, Dec 2016, Forbes) | @tomderuyck @steven_debaere | @InSites
WE KEEP HYPING IT massive promotion implies massive adoption? | @tomderuyck @steven_debaere | @InSites
HYPE OR REALITY? 67% INTERESTING TREND, TOO EARLY TO TELL OR MUCH ADO ABOUT NOTHING 23% GAME CHANGER (GRIT 2016) | @tomderuyck @steven_debaere | @InSites
BUILD TEST SHARE LEARN | @tomderuyck @steven_debaere | @InSites
AI IN FUTURE-PROOF ENVIRONMENTS insight activation insight generation & Consumer Consulting Board Insight Activation Studio | @tomderuyck @steven_debaere | @InSites
FUTURE-PROOF? insight activation insight generation communities impact gap 50% 45% as % of MR budget 5% OF MARKETERS BELIEVE MR OF MR PROJECTS 2016 LEADS TO CHANGE LEADS TO CHANGE IN 70% 2026 ATTITUDES & DECISIONS (Ray Poynter, 2016) (MR Impact Study, InSites Consulting, 2014) | @tomderuyck @steven_debaere | @InSites
AI ADOPTION CASESTUDIES insight activation insight generation & Her Minority Report | @tomderuyck @steven_debaere | @InSites
PROACTIVE COMMUNITY MANAGEMENT Participation Threat 1. 2. Low quantity Low quality | @tomderuyck @steven_debaere | @InSites
BUILD PROACTIVE COMMUNITY MANAGEMENT DISENGAGEMENT PREVENTION PAST FUTURE Future Past Nov Sep Aug Jul Oct | @tomderuyck @steven_debaere | @InSites
BUILD PROACTIVE COMMUNITY MANAGEMENT High High-Potentials Community Stars QUALITY Low Annoyers Passivists QUANTITY Low High | @tomderuyck @steven_debaere | @InSites
TEST PROACTIVE COMMUNITY MANAGEMENT WHAT DETECTION ABILITY: 78% (QT) & 71% (QL) ACCURACY PREVENTION CAPABILITY: IMPACT CRM APPROACH IMPACT A MODERATION TIME I SEE WHAT THE MODERATOR CAN’T SEE T FROM REACTIVE TO PROACTIVE MANAGEMENT | @tomderuyck @steven_debaere | @InSites
LEARN PROACTIVE COMMUNITY MANAGEMENT Adoption Increase adoption by trade-off between predictive accuracy, believability & actionability Database Insights Volume and qualitynecessarypreconditions Prediction model as pattern revealtool | @tomderuyck @steven_debaere | @InSites
INSIGHT ACTIVATION BOT Impact Threat 1. 2. Low efficiency Low effectiveness | @tomderuyck @steven_debaere | @InSites
BUILD INSIGHT ACTIVATION BOT A SMART ASSISTANT Case 2 Case 3 Case 1 SHOW ME THE LATEST NEW INSIGHTS FIND ME SOME INSIGHTS ABOUT PACKAGING LET’S MEET THE CONSUMER | @tomderuyck @steven_debaere | @InSites
TEST INSIGHT ACTIVATION BOT WHAT INSIGHT ACTIVATION: ADOPTION & SATISFACTION IMPACT A MARKETING MANAGER TIME I INSIGHTS ANYTIME, ANYWHERE, IN YOUR POCKET T CONSUMER-CENTRIC DECISION MAKING | @tomderuyck @steven_debaere | @InSites
LEARN INSIGHT ACTIVATION BOT Relevance Map out humanbehavior for defining use cases Logic Adoption In addition to core-behavior, challenging to enable small talk Associating a personality and humanizing the chatbot for increased adoption | @tomderuyck @steven_debaere | @InSites
LET’S KEEP MOVING LET’S START EXPERIMENTING | @tomderuyck @steven_debaere | @InSites
Deep dive // November 24th 2015 ARTIFICIAL INTELLIGENCE IN MARKET RESEARCH Discussing 2 case studies Tom De RuyckManaging Partner Thank you for your attention! Steven DebaereData Scientist www.insites-consulting.com