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EVENTS - AI in Retail Conference 2019



9:10am Chair's welcome

Keynote interview: What AI and ML can do (and what they can’t do) for your business

  • Practical applications of AI and ML - what they are, and what they can-and can’t do
  • What impact AI will haveon retailers and on customers over the coming 12 months
  • How much to invest in AI and ML, and how much value you can get out of them
  • Choosing the use cases that make most sense for your organisation
  • What is achievable within certain timeframes
  • What intermediate goals retailers currently have for AI and ML
  • How digitally native brands and large offline retailers are each using AI

Keynote talk: Mind-opening innovationsfrom other markets

  • HowAI innovations are already benefitting companies outside the retail sector
  • What customers feel about AI - concerns, likes, trends and changing behaviour
  • How marketing, digital, data and IT are working together to do more in the space

Dr. Geraint Evans, former Group Head of Marketing & Strategic Programmes / Head of Digital, Odeon Cinemas Group


Panel: Building a data platform to underpin your AI and ML strategy

  • Understanding the importance - and role of building a robust infrastructure
  • Deciding where to store your data
  • Guaranteeing data quality – updating or removing inaccurate, incomplete, improperly formatted or duplicated data
  • Ensuring your networking infrastructure, storage capacity, data analytics and security platforms are aligned with your AI aspirations

Ed Child, Head of Customer Data & Data Science, ASDA

Tarun Samtani, Group Data Protection Officer, CISO, Boden

10:50amNetworking break

Case study:Embedding AI into your company culture

  • Establishing the agile practices and team mindsetsneeded todeliver an AI strategy
  • Employing people with the skills to support your use of AI
    • Knowing what a successful AI team looks like
    • Attracting and retaining good data scientists and data engineers
    • Positioning your AI researchers (centrally vs. within each department)
  • Ensuring your AI team is in touch with your company’s problems, capabilities, value proposition and customers

Panel: Building out your technical AI capability

  • Understanding the supplier base and the services offered by potential partners
  • Accurately estimating costs, and optimising cost efficiencies on an on-going basis
  • Understanding how customisable AI technologies can be
  • Building vs. buying vs. renting your AI capability
  • Knowing which AI and ML technologies may not work for a retail business
  • Integrating AI and ML into your existing systems

Karen Harris, Managing Director, IntuDigital

Natalia Konstantinova, Lead Software Engineer R&D, First Utility


Case study: Personalisation for higher conversion rates and happier customers

  • Personalised messaging - what’s cool and what’s creepy
  • Choosing the right data sources for personalisation
  • Collecting and stitching together data to understand each customers’ needs and behaviour, and send the right messages at the right times
  • Modelling how changes to your website impact your customers’ actions
  • Using machine learning to tweak your recommender system and get an uplift
  • Churn prevention - identifying when you need to reactivate a customer

Kerry Dawes, Head of Digital Experience & Intel, Rank Group

12:50pmNetworking lunch

Case study: Turning your customer contact centre into an ‘opportunity centre’

  • Using chatbots and self-service to optimise how you communicate with customersand focus your employees on value-add work
  • Dealing with the consumers who ask questions your chatbot doesn’t understand
  • Seamlessly integrating man and machine - managing the live handoff between chatbot and real person
  • Long-term benefits of chatbots and self-service - reducing headcount and costs
  • Proactive customer service to reduce call volumes and increase customer retention

Natalia Konstantinova, Lead Software Engineer R&D, First Utility


Panel: Creating engaging customer experiences with IoT

  • Using IoT and AI to gain visibility on your customers’ needs and interests, and know which products they are most / least receptive to
  • Using augmented reality (AR) and virtual reality (VR) in-store to reduce friction in the buying process
  • Allowing customers to interact with products after purchase, to deliver insights that feedback into product development
2:50pmNetworking break

Case study: AI in fulfilment, supply chain and logistics to save delivery time and cost

  • AI for inventory- and stock optimisation - ensuring the right products are in right place at the right time
  • How IoT sensors can improve traceability, ensure products are kept in the right conditions, and help avoid counterfeit products being sold
  • How AI can improve the speed and flexibility of delivering products to customers

Case study: Protecting your brand reputation with AI

  • Automated tools to identify potentially harmful incidents and generate useful automated responses
  • Gaining visibility on whether the relevant department(s) highlighted issues to the right people at the right time

Case study: Using AI to connect your online and offline channels and processes

  • How AI can help you to bridge the physical-digital divide
  • Deploying an end-to-end platform powered by AI
4:50pm Chair’s summary and close of summit
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