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Future of conversational commerce july 2018 lr-compressed

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From Alexa and Siri to the use of chatbots as part of customer service, conversational commerce is already present for many in our everyday lives. This summary PPT examines what has enabled the recent rise, the state of play today, how might it evolve in the future and what the implications are for organisations.

Conversational Commerce Today

As part of work to support Mastercard’s thought leadership position on the Future of Conversational Commerce, unveiled at Money 2020 in June 2018, Future Agenda conducted desk research and a series of expert conversations to better understand the current state of play and to uncover emerging shifts of note.

The future of trusted conversational commerce will be shaped by three inter-related themes. These are:

1. Enhanced Customer Experience - As conversational commerce meets proof points of viability, feasibility and desirability
2. Being Human - As bots (and humans) become more informed, more natural and more helpful, powered by real-time AI and fuelled by organisation-wide accessible flows of data. NLP improvements add other ‘human’ psychological elements, e.g. hesitance.
3. Data’s Richness - As the economic imperative to identify and make best use of data – whether generated or procured from multiple sources - remains at the heart of ecommerce activities. With pervasive AI in place, it’s the data, not the engine that differentiates.

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Future of conversational commerce july 2018 lr-compressed

  1. 1. The Future of Conversational Commerce Insights from Multiple Expert Conversations Initial Perspective | July 2018
  2. 2. Context We would like to thank Mastercard for supporting this open foresight programme to explore the future of conversational commerce. We welcome your thoughts and additions to improve this initial perspective. Mastercard Money2020 Press Release - June 2018
  3. 3. Thematic Shifts Building on insights from Future Agenda discussions and additional dialogue in Q2 2018, we have identified three inter-related themes around which the development and impact of trusted conversational commerce will be shaped. Enhanced Customer Experience MainstreamReadiness Greater Relevance Interoperability Hyper-personalisation Safe&secure Being Human Natural Language Visualisation Honest Conversation AppropriateConversation Goodfriction Data’s Richness Clear DataValue DataLiability Ethical Commerce MachineLearning DrivingAccuracy DataOwnership Trusted Conversational Commerce
  4. 4. Theme 1 - Enhanced Customer Experience Conversational Commerce meets proof points of viability, feasibility and desirability MainstreamReadiness Greater Relevance Interoperability Hyper-personalisation Safe &Secure
  5. 5. MainstreamReadiness Fuelled by consumer uptake of a plethora of channels (e.g. chatbots, voice, apps) – and improved technological offerings such as NLP and ML, conversational commerce in 2025 provides ‘opti-channel’ integrated experiences.
  6. 6. Greater Relevance Developments in NL conversation, underpinned with Machine Learning enable more relevant responses to the consumer, both within and across experience domains: Devices become smaller, more embedded and more personal.
  7. 7. Interoperability Channel and interface barriers dissolve with the customer, and not the brand, put centre stage. Customer experience improves dramatically as customers are given what they need, where they need it through the most appropriate interface.
  8. 8. Hyper-personalisation Conversational commerce aims for a hyper-personalised experience, replicating that in the physical world where relevance, meaning, timing (e.g. of replies) are all suited to the context of the experience and which add up to ‘conversational momentum’.
  9. 9. Safe and Secure The multi-layered approach of Prevent, Identify and Protect is rigorously employed by payment facilitators. Improvements gained in fraud detection allow for more focus on authentication and choice management across channels.
  10. 10. Theme 2 - Being Human Bots (and humans) become more informed, more natural and more helpful, powered by real-time AI and fuelled by organisation-wide accessible flows of data. NLP improvements add other ‘human’ psychological elements e.g. hesitance. Natural Language Visualisation Honest Conversation AppropriateConversation GoodFriction
  11. 11. Natural Language A more natural human and real-time conversation is made possible through NLP, with an AI front-end and vast, inter-connected data sets as a back-end. Conversation has flow, cadence, inflection, timing, etc. It feels right, even though we know it’s a bot.
  12. 12. Visualisation Using visual effects to bring to life digital commerce, conversational or transactional, in order to enhance the experience for the user. Stimulating user imagination, especially with VAs, also features as ‘you see her (him) better if she’s not there’.
  13. 13. Honest Conversation As issues of trust continue to challenge brands across a wide canvas, consumers engaging with conversational commerce demand transparency on who or what they are speaking with as well as the agency of bots or VAs and their recommendations.
  14. 14. Appropriate Conversation The ability to access a customers relevant data across channels enables organisations to provide the right assistance in the most appropriate way with the right mix of man and machine.
  15. 15. Good Friction More complex and higher risk transactions may justify higher levels of scrutiny by customers and brands. In the long term ‘good friction’ with conversational commerce, wins over frictionless for most complex / higher-risk commerce decisions.
  16. 16. Theme 3 – Data’s Richness The economic imperative to identify and make best use of data – whether generated or procured from multiple sources - remains at the heart of ecommerce activities. With pervasive AI in place, it’s the data, not the engine that differentiates. Clear DataValue DataLiability Ethical Commerce MachineLearningDrivingAccuracy DataOwnership
  17. 17. Clear Data Value Organisations seeking to transact have to be clearer about why they value specific types of data, on what terms and how they will deploy it (esp. beyond first disclosure) or they risk losing public trust and their license to operate.
  18. 18. Data Liability Storing some kinds of data could come to be seen as a liability as the mere act of storing – and with it, protecting - erodes user trust, meanwhile the costs of securing data can be seen to outweigh the costs associated with losing it.
  19. 19. Ethical Commerce Increased outsourcing of decisions to autonomous machines feed the debate on the accountability and ethicacy of machines using our data - and their regulation. The more democratised datasets become, the greater potential to drive behaviour.
  20. 20. Machine Learning Driving Accuracy As usage of “AI” advisors for commerce (and more) increases, the data pool and contextual learning is enriched. Machine learning feeds on this ‘training opportunity’ and in return improves significantly, rewarding brands and users with accuracy.
  21. 21. Data Ownership With data’s value still on the rise, and customer familiarity of data exchange for better service increasing, traditional models of ownership of digital data cause debate. The focus shifts from ownership to the question of who is benefitting and fromwhat data.
  22. 22. Conversational Commerce – Implications, Opportunities, Key Questions
  23. 23. Impact on Customers Implications Increasing ease, and convenience for all brand interactions Soulless “digital” channels become more human Opportunities Personal agents conduct commerce on my behalf, involving me when required Threats Security and privacy concerns Concentration of power in the hands of my virtual agent Discovery may become harder
  24. 24. Key Questions for Customers Which brands do I trust and what do I trust them to do for me? Who makes it easy and enjoyable for me to discover, buy and service? Where is my data and how valuable is it / am I to brands? What are my views on data privacy and protection? What is my ‘social signal’ and influence footprint?
  25. 25. Impact on Brands and Retailers Implications Accelerating shift from ecommerce to mcommerce to conversational commerce (and after that) to ‘community commerce’ Opportunities Representation of offering and services within customer’s conversation Shift marketing from ecommerce and app conversion to relationships Threats Being left out of the conversation by the customer or messaging service Inability to collect and apply data across channels in real-time
  26. 26. Key Questions for Brands & Retailers What use cases lend themselves to conversational commerce? How will we ensure we are part of the conversation? How (quickly) can we build integrated, seamless and consistent experiences across access points and channels? What data do we have / need to integrate and to what end? How will we build deeper, more meaningful and appropriate ‘conversational’ relationships? What new areas of the ecommerce economy should we be investing in for the future?
  27. 27. Impact on Banks Implications Brand visibility removed at point of purchase, removing payment and credit provision opportunity Opportunities Real time transaction alerts Enhanced data, security and privacy Partnerships & Brand Alliances Threats Removal of card or card use from wallet Disintermediation by platform providers
  28. 28. Key Questions for Banks Can we locate a valuable role within the ‘conversation’? How will our brand show up across the transaction? How can the data we hold help the customer and retailer? How do we mitigate against disintermediation? Are we ready to participate in deeper collaboration with others?
  29. 29. What do you think? As an open foresight programme we’d welcome your thoughts to help build a stronger perspective. What do you agree with, what don’t you, what is missing and what will be the key impacts and implications. Thank you.
  30. 30. FutureAgenda 84BrookStreet London UK W1K5EH +442030088141 www.futureagenda.org

From Alexa and Siri to the use of chatbots as part of customer service, conversational commerce is already present for many in our everyday lives. This summary PPT examines what has enabled the recent rise, the state of play today, how might it evolve in the future and what the implications are for organisations. Conversational Commerce Today As part of work to support Mastercard’s thought leadership position on the Future of Conversational Commerce, unveiled at Money 2020 in June 2018, Future Agenda conducted desk research and a series of expert conversations to better understand the current state of play and to uncover emerging shifts of note. The future of trusted conversational commerce will be shaped by three inter-related themes. These are: 1. Enhanced Customer Experience - As conversational commerce meets proof points of viability, feasibility and desirability 2. Being Human - As bots (and humans) become more informed, more natural and more helpful, powered by real-time AI and fuelled by organisation-wide accessible flows of data. NLP improvements add other ‘human’ psychological elements, e.g. hesitance. 3. Data’s Richness - As the economic imperative to identify and make best use of data – whether generated or procured from multiple sources - remains at the heart of ecommerce activities. With pervasive AI in place, it’s the data, not the engine that differentiates.

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