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Bee Partners' Industry Insight: NLP on the Verge of Utility

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Companies like StatMuse, SnapTravel, and Cohort are changing commerce by engaging users seamlessly and immediately via conversational experiences.

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Bee Partners' Industry Insight: NLP on the Verge of Utility

  1. 1. Conversational Commerce Natural Language Processing (NLP) on the Verge of Utility September 2016, revised March 2018 Garrett Goldberg Partner (208) 860-7855 garrett@beepartners.vc Seed-stage venture capital firm investing in passionate Founders with deep market insights
  2. 2. The ability of consumers (and enterprises) to conduct e-commerce dynamically through the use of texting or spoken natural language. What is Conversational Commerce? 2
  3. 3. 3rd party Application Transcript USER Automatic Speech Recognition (ASR) Built by Application Owner Built by Platform Owner NLP Horizontal “Handshake” Layer Natural Language Processing (NLP) Text to Chatbot Voice to Chatbot API 3 Virtual Assistant Platform UI Natural Language Processing Enabling Technology API IntegrationLevel IntegrationLevel Agent / Skills / Action Taker Ex: Bot built using SDK Knows Intent + Takes Action + Contextualizes Knows Intent + Takes Action Bee Partners NLP Stack Diagram
  4. 4. 4 Here’s Why It’s Happening… • We are in the midst of a (continuing) paradigm shift in how humans interact with computers (HCI). • We are now using human conversation (voice or text entry) to seamlessly obtain information, goods, and services on our various computers. • This leads consumers to desire “One Place” to dynamically conduct all our business and social activities. • And yet this “One Place” is ubiquitous: Anywhere and everywhere - voice, Siri, in- car, in-home, messaging apps – the distribution channels become infinite 4
  5. 5. 5 This Drive Towards One Place Effectuates the ‘Stackless Interface’ … A single human-computer interface (HCI) that connects the user to any end requirement http://beepartners.vc/investment-snaptravel-rise-stackless-interface/ https://www.linkedin.com/pulse/stack-discipline-garrett-goldberg/ 5
  6. 6. 6 … Which Often Manifests Itself in a “Chatbot” to the User A chatbot is a computer program, driven by natural language processing (NLP) and machine learning (ML), designed to simulate intelligent conversation around a particular expertise. A chatbot is a computer application that provides a consumer with a convenient way to interact (interface) with a business via online texting or voice. A chatbot delivers “conversation experiences” with the enterprise A chatbot is to a messaging app = Website : Browser 6
  7. 7. 7 A chatbot can conduct conversational commerce better than humans in some aspects and worse in others. 7
  8. 8. 8 Chatbot Pros and Cons It is better than humans because: (1) it can chat with thousands of people simultaneously, autonomously, and remotely. (2) it can hold vast amount of knowledge in its memory, and access it quickly. (3) it can handle asynchronous communication. (4) it never gets tired, is consistent, and (nearly) unemotional. And not as good when: (1) talking about subjects outside its vertical knowledge. (2) answering dynamic questions, or generating speech (NLG). (3) being witty or thinking outside the box. (4) linking commerce across platforms or applications. 8
  9. 9. 9 9 How Did We Get Here? The intersection of three trends is driving this evolution of human computer interaction (HCI) towards a conversational commerce interface.
  10. 10. 10 1) Consumer Trends Messaging • Messaging is the go-to [millennial] way of communication. • More people today are using messaging platforms than social networks. • Messaging is no longer limited to personal communication, but is widely accepted as a means of business communication. On-Demand Access • Consumers want on-demand access to information services with minimal barriers – the ‘stackless interface.’ • Native apps are dying and consumers are shifting away from websites and app installs. • Asynchronous communication is now 7/24/365. There is a global movement towards messaging platforms and on-demand services. 10
  11. 11. 11 11
  12. 12. 12 2) Business Evolution Enterprises must focus on delivering personal customer service at scale LOW PERSONALIZATION & HIGH SCALABILITY Conversational Commerce In-Person E-Commerce HIGH PERSONALIZATION & LOW SCALABILITY HIGH PERSONALIZATION & HIGH SCALABILITY
  13. 13. 13 3) Technology Advancements Advancements in Artificial Intelligence • Advances in machine learning such as deep neural networks (DNNs) have allowed bots to learn as they are fed more data. This improves the utility beyond keyword searches. Access to new messaging and speech platforms • Big tech companies have opened up their speech and messaging platforms to developers. Distributed platforms of IoT • Voice platforms like Siri, Cortona and Okay Google have become ubiquitous in phones, laptops, and cars. Artificial intelligence and access to new messaging and speech platforms have enabled the emergence of conversational UI. 13
  14. 14. 14 14 So What Does This Mean for Investors? Bee Partners Preliminary Guide to Evaluating the Conversational Commerce Paradigm
  15. 15. 15 1) Effective Conversational Commerce Must Leverage Existing Platforms We do not expect adoption of a chatbot that forces users to embrace a new or application specific platform. 15
  16. 16. 16 2) Effective Conversational Commerce Must Have Functional Expertise and Vertical Depth in a Specific Industry • CONTEXT IS KING: if you go deep enough in any vertical (the most data with the best lexicon), the application is going to be differentiated and deliver a better result. • It’s more difficult to imagine a functional horizontal chatbot. The bot would need to be able to have a conversation across a diverse set of topics. • It’s difficult to pick a winner in horizontal enterprise or broad enterprise that still requires the client to customize. • Current horizontal opportunities do exist at the “Handshake” or infrastructure layer where the application connects to the platform. 16
  17. 17. 17 3) Effective Conversational Commerce Leverages the Best of Both Consumer and Enterprise Properties • Bots and personas must feel human but drive business (conduct commerce). Consumer and enterprise simultaneously. • Team must pair deep technical knowledge in NLP, AI and machine learning with vertical business experience. • Must intimate direct, custom relationships at scale. • Consistent with the consumerization of enterprise SaaS. 17
  18. 18. 18 4) Effective Conversational Commerce Must Add Value Beyond Just Being a ‘Stackless Interface’ • Price arbitrage, assisted selling, previously unavailable channel or way to convert customers. • Chat is the new search; must immediately get customers deep in the application/company to find relevant information. • Ability to close the transaction with the same seamless experience; this may differ between platforms’ technical capabilities. 18
  19. 19. 19 5) Effective Conversational Commerce Often Looks Internally within an Enterprise • Using NLP in a non-customer-facing way can make employees more effective in searching for requested information. • Additional employee capacity drives better outward customer support and better customer outcomes. • Customer service is the marketing of the future; brands will struggle to be competitive without an effective service layer. 19
  20. 20. 20 The Result of All This Is... • Continued Democratization of Information • Additional Friction Layers Dropped • Approaching “One Place” 20
  21. 21. 21 And Finally, the Future! • Your conversational searches reveal immediate answers (faster). • Everyone has an effective personal assistant (more accessibility). • Every online brand interaction has a conversational (bot) element. • Your phone only has 3 apps! – Phone app – Social media – Messaging Maybe… it won’t even have a keyboard! What might the world look like 10 years from today? 21
  22. 22. 22 Bee Partners’ Core Positions Include Application, Handshake, and Infrastructure Layers 22 Find and book the perfect hotel room over a delightful conversational experience [Exited] The next generation of voice-driven and context-aware human- computer interaction (HCI). The company has pioneered Speech Team as a Service (STaaS) around its Deep Neural Network-based speech recognition solution A creative technology company, offering a language-based artificial intelligence platform for sports fan engagement. Solving EHR complexity with specialized clinical AI and NLP
  23. 23. 23 Looking Ahead… We welcome introductions to experienced Founders with a deep vertical insights who: • have deep vertical domain expertise; strategic thinking about what this new UX paradigm delivers. • whose thinking is consistent with the 5 points of Bee’s thesis on effective conversational commerce. And of course... please use and evangelize Cohort, SnapTravel and StatMuse! 23

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