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UX STRAT USA 2021: Sönke Rohde, Salesforce

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Deep Learning UX
AI-powered, Personalized Design at Scale
Twitter: @soenkerohde #DLUX #UXSTRAT
Sönke Rohde (he/him/his), V...

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This presentation contains forward-looking statements about the Company’s financial and operating results, which may includ...

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Personalization
Is everywhere

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UX STRAT USA 2021: Sönke Rohde, Salesforce

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Sönke Rohde gave a presentation at UX STRAT USA 2021 on the topic: "Deep Learning UX: AI-Powered, Personalized Design at Scale"

Sönke Rohde gave a presentation at UX STRAT USA 2021 on the topic: "Deep Learning UX: AI-Powered, Personalized Design at Scale"

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UX STRAT USA 2021: Sönke Rohde, Salesforce

  1. 1. Deep Learning UX AI-powered, Personalized Design at Scale Twitter: @soenkerohde #DLUX #UXSTRAT Sönke Rohde (he/him/his), VP UX R&D
  2. 2. This presentation contains forward-looking statements about the Company’s financial and operating results, which may include expected GAAP and non-GAAP financial and other operating and non-operating results, including revenue, net income, earnings per share, operating cash flow growth, operating margin improvement, expected revenue growth, expected current remaining performance obligation growth, expected tax rates, stock-based compensation expenses, amortization of purchased intangibles, shares outstanding, market growth, environmental, social and governance goals, expected capital allocation, including mergers and acquisitions (such as the proposed acquisition of Slack Technologies, Inc.), capital expenditures and other investments, expectations regarding closing contemplated acquisitions and contributions from acquired companies. The achievement or success of the matters covered by such forward-looking statements involves risks, uncertainties and assumptions. If any such risks or uncertainties materialize or if any of the assumptions prove incorrect, the Company’s results could differ materially from the results expressed or implied by the forward-looking statements it makes. The risks and uncertainties referred to above include those factors discussed in Salesforce’s reports filed from time to time with the Securities and Exchange Commission, including, but not limited to: risks associated with our ability to consummate the proposed Slack Technologies, Inc. transaction on a timely basis or at all; our ability to successfully integrate Slack Technologies, Inc.’s operations; our ability to realize the anticipated benefits of the proposed transaction; the impact of Slack Technologies, Inc.’s business model on our ability to forecast revenue results; disruption from the transaction making it more difficult to maintain business and operational relationships; the impact of, and actions we may take in response to, the COVID-19 pandemic, related public health measures and resulting economic downturn and market volatility; our ability to maintain service performance and security levels meeting the expectations of our customers, and the resources and costs required to avoid unanticipated downtime and prevent, detect and remediate performance degradation and security breaches; our ability to secure and costs related to data center capacity and other infrastructure provided by third parties; our reliance on third-party hardware, software and platform providers; the effect of evolving domestic and foreign government regulations, including those related to the provision of services on the Internet, those related to accessing the Internet, and those addressing data privacy; current and potential litigation involving us or our industry, including litigation involving acquired entities such as Tableau; regulatory developments and regulatory investigations involving us or affecting our industry; our ability to successfully introduce new services and product features, including any efforts to expand our services beyond the CRM market; the success of our strategy of acquiring or making investments in complementary businesses and strategic partnerships; our ability to compete in the market in which we participate; the success of our business strategy and our plan to build our business; our ability to execute our business plans; our ability to continue to grow unearned revenue and remaining performance obligation; the pace of change and innovation in enterprise cloud computing services; the seasonal nature of our sales cycles; our ability to limit customer attrition and costs related to those efforts; the success of our international expansion strategy; the demands on our personnel and infrastructure resulting from significant growth in our customer base and operations; our dependency on the development and maintenance of the infrastructure of the Internet; our real estate and office facilities strategy and related costs and uncertainties; fluctuations in, and our ability to predict, our operating results and cash flows; the variability in our results arising from the accounting for term license revenue products; the performance and fair value of our investments in complementary businesses through our strategic investment portfolio; our ability to protect our intellectual property rights; our ability to develop our brands; the valuation of our deferred tax assets and the release of related valuation allowances; uncertainties regarding our tax obligations in connection with potential jurisdictional transfers of intellectual property; uncertainties regarding the effect of general economic conditions; and risks related to our debt and lease obligations. Forward-Looking Statements 031621
  3. 3. Personalization Is everywhere
  4. 4. Personalization What about Design?
  5. 5. Personalization Today Personalize the channel & time to deliver the content Personalize which content to show Content Messaging
  6. 6. Personalization Today Personalize the channel & time to deliver the content Personalize which content to show Template Content Messaging
  7. 7. Shopper Experience Paula Beth
  8. 8. Paula Beth Shopper Experience
  9. 9. Paula Beth Shopper Experience
  10. 10. One size does not fit all Personalized Design
  11. 11. One size does not fit all Personalized Design 1 3 2 4
  12. 12. Meaningful, bespoke experiences tailored to each individual Relationships by Design
  13. 13. Why don’t we see Personalized Design today? It’d take an army
  14. 14. “Pick two”
  15. 15. Personalized Design Requires a New Approach (hint: AI) Personalization of the Experience Layer: 1. variations covering the spectrum of preferences 2. continuously explore and validate learnings Variations (at Scale) • Programmatic/Declarative UI • Generative UI Experimentation (1:1) • A/B & Multivariate testing • Contextual Bandit
  16. 16. Deep Learning UX AI-Powered, Generative Design
  17. 17. ● ~1K web pages of the Fortune 500 and Unicorns ● Extracted screenshots, normalized DOM and styles Data Analysis Color Full Height Website Color Distribution / Content Block Data Viz by Moritz Stefaner for Salesforce
  18. 18. Color Split by Industry
  19. 19. ● Typography is intrinsic to design and gives content structure and hierarchy. ● Style relationships are complex and brand specific Data Analysis Typography Font Size Distribution Style Relationships Human bias towards even over odd # Font Face Distribution
  20. 20. Latent Style Space Data Exploration Takeaways The latent space is basically a representation of compressed data which in this case enables the featurization of design rules and heuristics. The key takeaway from our Data Science research is that there is a meaningful latent space when it comes to style encapsulating aspects around color, typography, layout and other design aspects.
  21. 21. Simulation
  22. 22. Placing Content on Image Assets Templates don’t cut it
  23. 23. Computer Vision Copyspace ● Identifies/predicts the best regions for placing content on top of an image ● Avoids covering areas of interest ● Accessibility (color-contrast) built in
  24. 24. Design & Content Variations Design Variations Content Variations
  25. 25. Experimentation Turning into Personalization
  26. 26. A/B & Multivariate (MVT) testing ● Tests consist of a randomized experiment with a set of variants ● Multivariate testing : testing multiple variables to find the ideal combination Experimentation Terminology Contextual Bandit ● MAB + feature & context vector (e.g. user and state) ● Experimentation turning into Personalization (Explore/Exploit) Multi-armed Bandit (MAB) ● A/B/n Testing + Machine Learning ● Dynamically allocate traffic to variations based on performance to mitigates “regret” A/B Testing Multi-armed Bandit Testing Contextual Bandit Testing Variation A Variation B Variation D Variation C t %
  27. 27. AI-Powered, Personalized Design at Scale AI-generated Variations e.g. DLUX Learn Feedback Loop AI Personalization Engine e.g. Contextual Bandit
  28. 28. Artificial yet Ethical How might we mitigate unintended consequences?
  29. 29. Conducted during initial conception, roadmap planning, and feature creation. Answers 3 questions: 1. What are the intended and unintended consequences of this product or feature? 2. What are the positive consequences we want to focus on? 3. What are the negative consequences we want to mitigate? Consequence Scanning An agile practice for responsible innovators “Consequence Scanning is a lightweight methodology that gets teams accustomed to flexing their ethical foresight and building moral muscle memory.” — Yoav Schlesinger, Director, Ethical AI Practice ● Answers are logged, responsibilities to act are assigned, actions tracked in product backlog More info: https://doteveryone.org.uk/project/consequence-scanning/
  30. 30. Source: NATIONAL HIGHWAY TRAFFIC SAFETY ADMINISTRATION https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety Levels of Driving Automation
  31. 31. Level 2: Automate Tedious, Repetitive Tasks Design Automation Levels Design Assistance Partial Design Automation Conditional Design Automation High Design Automation No Design Automation Full Design Automation Hand-drawn designs (e.g. Photoshop) using a style guide to ensure consistency. Hand coded UI. Modern design tools assist with design and Design Systems for consistency. Component development. Computational model of a brand’s design generating experience fragments. Automatic composition of experience fragments and layout variations. TBD TBD 1 2 3 4 0 5 Goal Today Tomorrow Scope Accelerate Designer & Developers tasks Automate tedious, repetitive Junior Designer/Developer tasks Automate tedious, repetitive Senior Designer/Developer tasks TBD TBD
  32. 32. Human in the loop Augmented Intelligence Design AI Customer User AI Variations Personalization
  33. 33. Human in the loop Augmented Intelligence Design AI Customer User AI Variations Selections Personalization
  34. 34. Human in the loop Augmented Intelligence Design AI Customer User AI Variations Selections Prediction Personalization
  35. 35. Human in the loop Augmented Intelligence Design AI Customer User AI Variations Selections Prediction Feedback Loop Personalization
  36. 36. Human in the loop Augmented Intelligence Design AI Customer User AI Variations Selections Prediction Feedback Loop Personalization
  37. 37. Human in the loop Augmented Intelligence Design AI Customer User AI Variations Selections Prediction Feedback Loop Personalization Implicit & Explicit
  38. 38. Einstein Designer Powered by Deep Learning UX
  39. 39. Marketing Cloud Humanize every moment with real-time personalization Einstein Designer creates relevant content with the help of AI in seconds using variations of available images, copy, and headlines.
  40. 40. Democratization of Design Today Marketing Specialist Creative Designer days or weeks images and text creativ e assets Creative Designer Tomorrow Marketing Specialist minutes images and text creativ e assets Elevate designers to think creatively about the brand. Designers perform repetitive work combining images and text Einstein Designer enables Marketing Specialists to operate autonomou sly Creative team can update DLUX to control their brand from a single point. seasonally Tune Branding Einstein Designer
  41. 41. Personalized Design at Scale AI-generative Design • Automates tedious, repetitive tasks - Democratize Design • Generates variations for experimentation/personalization AI-powered Experimentation • Enables efficient data-driven design - take the subjectiveness out of the creative process • Advanced experimentation frameworks like Contextual Bandit enable 1:1 personalization of design Personalized Design • No more “one size fits all” for the experience layer • Meaningful, bespoke experiences tailored to each individual Building Relationships by Design
  42. 42. Thank You

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