Title: Applying AI, ML, Automation in Marketing Research
Wednesday, December 15, 2021; 12 PM EDT
According to ESOMAR’s User and Buyer Global Insights Study 2020, nearly three quarters (71%) of client-side survey respondents believed that AI Machine Learning and Automation were among the important priorities for business in the next 2-5 years, ranking fourth in a tie among 12 priorities ranging from confidentiality of data, data protection, AI ethics to chatbots. The same research revealed that the focus of firms was going to be doing research simply and ethically. What are the current prevalent trends in AI, machine learning and automation, and how can researchers and clients prepare for success in this realm as they achieve client outcomes?
This webinar will bring in leading experts and researchers who will speak to their contributions, foundations and research insights in the realm of AI, Machine Learning and Automation to answer the following questions with unique data points techniques and client stories / case studies:
- Predictive power for client centricity: How can we use AI and ML to build effective predictive models that allow us to understand consumer behaviour, citizen behaviour and employee behaviour? How do you optimize insights from multiple data sets and sources to predict satisfaction scores, propensity of churn, of customers choosing one brand/product/service over another. How to improve client centricity with AI and machine learning?
- Data minimalism for actionable insights: How do researchers predict and improve major client outcomes by collecting the minimum possible data? With every new input of data we improve prediction models and improve precision power as we let the data improve the models when live data feed the models. It is about letting the data dictate action for the clients and researchers.
- Breaking the jargon: What are the key differences between AI, machine learning and automation in the industry? How have machine learning, AI and automation evolved in marketing research in 2021?
- Best practices: What are the ethical considerations for using Machine Learning, AI and automation in research ? How does human intelligence work best with machine and artificial intelligence? What do the next five years look like for AI, Machine Learning and Automation? Where are the areas of opportunity for various client sectors?
- Workforce and talent implications: What new skills and talent-pools are we going to need to look to for success in these emerging yet rapidly evolving fields?
Format – Speakers present for 10 minutes each, followed by a focused moderated discussion and audience Q-A.
Speakers Danny Heuman, Chief Analytics Officer, Environics Analytics; Roger Sanborn, Chief Product Officer, mTab; Arundati Dandapani, CIO of CRIC and COO of CAIP
Format: Each presenting team speaks for 10-15 mins and then it will be followed by a moderated discussion and then Q-A.