WebTomorrow Keynote
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Presented in Belgium, June 2017
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WebTomorrow Keynote
- 1. THE NEXT YOU: DISRUPT YOURSELF Deep dive // November 24th 2015 Tom De Ruyck Managing Partner Man-Machine Collaboration
- 2. Automation and Artificial Intelligence | @tomderuyck
- 3. “Automation and Artificial Intelligence will, over a period of time, replace the worst 75% of market research, leaving just the best as having a significant human component.” Ray Poynter NewMR | @tomderuyck
- 4. “Automation does indeed substitute for labor. However, automation also complements labor, raising economic outputs in ways that often lead to higher demand for workers.” Irving Wladawsky Berger | @tomderuyck
- 8. PROACTIVE COMMUNITY MANAGEMENT Low quantity 1. Low quality 2. Participation Threat | @tomderuyck
- 9. BUILD QUANTITY QUALITY Low High Low High Community Stars Passivists High- Potentials Annoyers PROACTIVE COMMUNITY MANAGEMENT | @tomderuyck
- 10. TEST IMPACT DETECTION ABILITY: 78% (QT) & 71% (QL) ACCURACY WHAT A T I FROM REACTIVE TO PROACTIVE MANAGEMENT SEE WHAT THE MODERATOR CAN’T SEE MODERATION TIME PROACTIVE COMMUNITY MANAGEMENT PREVENTION CAPABILITY: IMPACT CRM APPROACH | @tomderuyck
- 11. LEARN Increase adoption by trade-off between predictive accuracy, believability & actionability Volume and quality necessary preconditions Prediction model as pattern reveal tool Database Adoption Insights PROACTIVE COMMUNITY MANAGEMENT | @tomderuyck
- 12. | @tomderuyck
- 13. Low efficiency 1. Low effectiveness 2. Impact Threat INSIGHT ACTIVATION BOT | @tomderuyck
- 14. BUILD A SMART ASSISTANT INSIGHT ACTIVATION BOT FIND ME SOME INSIGHTS ABOUT PACKAGING Case 3 LET’S MEET THE CONSUMER Case 1 SHOW ME THE LATEST NEW INSIGHTS Case 2 | @tomderuyck
- 15. TEST A T I IMPACT INSIGHT ACTIVATION: ADOPTION & SATISFACTION INSIGHTS ANYTIME, ANYWHERE, IN YOUR POCKET CONSUMER-CENTRIC DECISION MAKING MARKETING MANAGER TIME WHAT INSIGHT ACTIVATION BOT | @tomderuyck
- 16. LEARN In addition to core- behavior, challenging to enable small talk Logic Map out human behavior for defining use cases Relevance Associating a personality and humanizing the chatbot for increased adoption Adoption INSIGHT ACTIVATION BOT | @tomderuyck
- 18. THE NEXT YOU: DISRUPT YOURSELF Deep dive // November 24th 2015 www.insites-consulting.com Man-Machine Collaboration Thank you for your attention!
Hinweis der Redaktion
- automation
- Given the continuing automation of so much human work over the past couple of centuries, why are there still so many jobs left? The answer isn’t very complicated, although frequently overlooked. As Prof. Autor succinctly puts it: “tasks that cannot be substituted by automation are generally complemented by it.” Automation does indeed substitute for labor. However, automation also complements labor, raising economic outputs in ways that often lead to higher demand for workers.
- Challenge of Member disengagement for CCB’s Low quantity if the member does not participate enough in the topics that are organized in the community low quality if what the member says doesn’t say anything at all. As a result, if those types of behavior occur frequently, the community may not be able to deliver useful insights anymore. Therefore, as we want to sustain ongoing ccb’s on the long-term, it’s crucial to battle member disengagement. The moderator can do a pretty good job, but it still requires extra energy that could be better used for analyses & insight generation motivation
- Delete? Enough time? Now how, can we make this more practical in a community context. By combining the two dimensions (quantity & quality) & their respective activation levels (low & high), we can come up to a four quadrant framework This allows you to identify easily the future performance of each member. Now, we can classify each member into one of the quadrants & see the future of each member
- With this project, we aim to maximize capabilities to identify & prevent member disengagement, while maximizing moderator convenience The impact: Automational: automatic detection of destructive behavior leads to time reduction in community moderation Transformational: through the prediction models, we can go from reactive (when it’s already to late) to proactive community management (prevention) Informational: through the prediction models, subtleties & destructive community patterns arise that lead to destructive community behavior
- Process learnings: Data preparation is time-consuming, but key for prediction quality Objective is to enjoy benefits of AI in a community context & to maximize adoption; Therefore, we gave up predictive accuracy through explore other models that are more justifiable & comprehensible for the moderator Prediction model as pattern reveal tool Models show that narcissistic moderators & negative community environments increases chances of member disengagement
- Challenge of user assistance for Insight Activation Environments Who is my consumer? Which insights define my consumer? Insight inspiration for new projects? The Marketing department overloaded with consumer insights; in meeting & urgent need for insight? Guiding users through your insight database
- Galvin is connected to the insights database, having the right information at hand to help marketers. It uses Luis AI to understand language It uses cortona to become an intelligent personal assistent Both powered by AI technologies
- With this project, we aim to maximize user assistance in the insight The impact: Automational: because it’s a 100% digital chatbot, the marketing manager’s time can be spend more wisely Transformational: the chatbot for market research impersonates your personal market research assistent Informational: access to insights anytime, anywhere, right availble in your pocket