Day 2

29 November 2018

AI and the Consumer

Gartner predict that by 2020 – 85% of customer interactions will not be managed by humans. Customers now have a wealth of information at their fingertips and can easily compare price, quality and service so how can brands stand out from the crowd and really engage with their customers? From using chatbots to communicate to using AI to predict behaviours and buying patterns, to recommendations and personalisation, this session will look at how AI is changing the customer experience.


AI and the Consumer: Chair’s welcome and opening comments


Keynote: The Future of AI for Customer Experience

  • Explore how AI is being used to accelerate customer-centric experience design
  • Practical applications to leverage AI
  • How big data and contextual computing is influencing the consumer
  • A look at the next generation of consumer analytics
  • Using computer vision and natural language processing to enhance customer experience
  • How does GDPR effect things?


Panel: ChatBots – The Next Generation of Messaging Apps

  • Understanding the messaging platform of the future
  • Creating personalized interaction between the consumer and a brand
  • Measuring the success of your chatbot though engagement levels, sentiment analysis, response rates, bot mentions and click through rates


AI in Action

Real use case studies of brands using AI to drive growth and engage with their customers.
A look at best practise and common pitfalls to avoid.


Networking Break


Panel: Examining AI Uses in Banking & Finance Services

  • Explore current AI applications within the financial & banking sectors
  • The advancement of Robo advisers into Robo trading
  • Automated financial advisors and planning developments, and data driven lending systems
  • The future value of machine learning within the finance & banking sectors enabling fraud reduction


Case Study: Future of Travel – Man vs Machine

  • Looking at real life examples of Artificial Intelligence within the travel sector


Panel: AI Transforming Healthcare

Senior Representative, SAS

Associated Talks:

12:45PM - Day 2

View Panel: AI Transforming Healthcare

10:30AM - Day 1

View Keynote: Information is Everything

09:30AM - Day 1

View Keynote: AI Powering Digital Transformation

View Full Info

  • How is AI changing the way that healthcare is delivered?
  • Machine learning and big data – how to leverage new data sets to deliver personalised medicine
  • Innovative ways machine learning and deep learning are being used to develop new drugs
  • Challenges for the future
. Senior Representative, SAS, ,


Networking Lunch


Afternoon Keynote: Digital Assistants and Their Relationship with the Consumer

  • What does the advent of digital intelligent assistants mean for businesses and consumers?
  • How are artificial intelligence and machine learning programmes being used in everyday consumer products
  • Building consumer trust in AI in areas such as financial planning, education and medical diagnosis
  • What are the privacy issues surrounding the use of intelligent assistants & how do we protect data


Panel: The Revolutionising of Customer Experiences Through AI

  • The impact of AI and understanding when AI is most effective as a tool for customer service
  • Why smart tech are key to creating contextual experiences
  • Using AI to predict consumers intentions
  • Effective personalisation of communications to create positive impacts
  • What’s the most effective way of engaging staff and help them work along-side AI?
  • What are the cost implications both short and long-term?


Case Study: Influencing the New Wave of Marketing

A case study from a world leading brand discussing how AI and ML can create truly 1:1 marketing experiences, and help lower costs, and man hours whilst bridging the gap between data and personalised customer experiences


Panel: Predictive Analytics for Customer Recommendations

  • How to deliver truly personal and unique recommendations
  • Deep learning tools that personalize a user’s experience
  • Enhancing suggestions using self-learning algorithms
  • Taking recommendations to the next level


Session Close

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