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Website personalization trends and techniques 2018

Learn the latest best practices with examples from the Smart Insights summit talk on personalization across web, email and media platforms using AI and machine learning.

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Website personalization trends and techniques 2018

  1. 1. 1 #DigitalPriorities Digital Marketing Priorities 2018 brought to you by The 3 key ways to improve the customer journey Joey Moore, Director of Product Marketing Greg Moore, Manager for Personalisation and Campaign Strategy of Episerver
  2. 2. 2 Before we start… house keeping • A recording for the webinar will be sent via Email • Slides will be available via Smart Insights Slideshare • Please get involved with the interactions: • Give your views in the votes • Do ask questions at any point via the Questions panel
  3. 3. 3 Recommended Smart Insights toolkit update
  4. 4. 4 THE IMPORTANCE OF ANALYTICS
  5. 5. 5 THE IMPORTANCE OF ARTIFICIAL INTELLIGENCE
  6. 6. 6 6 THE IMPORTANCE OF MACHINE LEARNING
  7. 7. 7 7 WHY DO YOU EVEN WANT THESE 3 TO CONVERGE?
  8. 8. 8 8 THE IMPORTANCE OF CUSTOMER EXPERIENCE
  9. 9. 9 9 IMPROVE SATISFACTION INCREASE LOYALTY
  10. 10. 10 10 MOST COMPANIES TREAT THEIR CUSTOMERS LIKE THIS
  11. 11. 11 BUT YOU WANT TO TREAT THEM LIKE THIS
  12. 12. 12 12 Start Finish HOW DO YOU START?
  13. 13. 13 Segmentation
  14. 14. 14
  15. 15. 15 SEGMENTATION
  16. 16. 16 SEGMENTATION AUTOMATION
  17. 17. 17 Strategy and Authoring Campaign Orchestration 2. Visitor Intelligence Behavioral Search Optimization Personalized Cross-channel Outreach Rankings & Recommendations 3. Autonomous Personalization Delighting the Customer Marketer Machine Cross-channel Execution Content Personalization 1. Omnichannel Content Management Real-Time Interaction Management Profile and Persona Big Data Store Creativity Helping Differentiate with the Ideal Marriage of Man and Machine
  18. 18. 18 THE 3 TIERS OF PERSONALIZATION Segmentation BehavioralBasic/Standard Hello Joey, Welcome Back Based on what what you’ve browsed and what people with similar behaviors like you  Here’s your product or content that best fits you Brits, who have too many kids and like to travel  This is what they should see
  19. 19. 19 Segmentation BehavioralBasic/Standard Hello Joey, Welcome Back Brits, who have too many kids and like to travel  This is what they should see Based on what what you’ve browsed and what people with similar behaviors like you  Here’s your product or content that best fits you Developers Marketers / Merchandisers AI
  20. 20. 20 Episerver 20 PERFORM (PRODUCT RECOMMENDATIONS)
  21. 21. EpiserverEpiserver
  22. 22. EpiserverEpiserver
  23. 23. EpiserverEpiserver
  24. 24. EpiserverEpiserver
  25. 25. 25 25 50% increase in AOV 65% increase in units per order 5% increase in sales 35% increase in AOV 7% increase in sales 66% increase in units per order
  26. 26. 26 Episerver Advance* | Content Sequencing SEE THINK DO CARE * Planned release, not yet available
  27. 27. 27 Episerver 27 USER GENERATED CONTENT
  28. 28. EpiserverEpiserver Brands are spending more year-over-year increase in brand created content 3X For less return of all brand created content gets noticed 5% of purchase decisions are peer influenced 81% Drive sales ofconsumerstrustearnedmediamorethan ownedmedia 92% Strengthen consumer trust
  29. 29. 29 WWW WWW WWW WWW WWW Target Segment Female Segme nt Male Segme nt Other A/B Test A/B Test 30 days 30 days 30 days INTELLIGENT CAMPAIGN (REACH & CAMPAIGN)
  30. 30. EpiserverEpiserver Drives click through rates up by up to 60% Increase conversion by up to 25% Boost the performance of all your email campaigns Welcom Offers News Browse Abando n Confirmatio nn Shipping Rate/Review Cross-sell Fully Personalize All Types of Emails
  31. 31. 31 Episerver 31 INSIGHT (ACTIONABLE INTELLIGENCE)
  32. 32. 32 Episerver Collect Individual User Level Data Aggregate to Segmented or Persona Level Identify User Journey’s Visualize Relevant Data Take Action and Permeate Through Relevant Systems
  33. 33. 33 Episerver Asadigitalmarketeryou needto beableto…
  34. 34. 34 Episerver 34
  35. 35. 35 Episerver 35 target amulti- dimensionallysegmented audience basedon their historical interactions
  36. 36. 36 Episerver Asamerchandiseryou needtobeableto….
  37. 37. 37
  38. 38. 38 discover interestsin certain productcategories
  39. 39. 39 Episerver Asadeveloperyouneed tobeableto….
  40. 40. 40 Episerver
  41. 41. 41 Episerver utilizeandenrichthe datainanywayyoulike
  42. 42. 42 Episerver Asabusinessleaderyou needtobeableto
  43. 43. 43 Episerver understandand act on your businessobjectives
  44. 44. 44
  45. 45. 45
  46. 46. 46
  47. 47. 47
  48. 48. 48
  49. 49. 49
  50. 50. 50 From Data Management to Data Intelligence Episerver Profile Store | Data Management Platform (DMP) Episerver Personalization Engine | Machine Learning Algorithms Data Analytics • Records what happened • Stores visitor behavior • Low customer value Customer profile Interaction preferences Transaction history Case history Recent browsing activity Recent chat activity Social activity Location and device GDPR compliance Data Science • Calculates and predicts intent • Relies on Data Analytics • Mid value to customer Episerver Advance Episerver Find Episerver Perform Data Intelligence • Visualize results • Relies on Data Science or Data Analytics or both • High value to customer Search Rankings Product Recommendations Content Sequencing Event Triggering Individual or Group Profiles and Journeys Personas and Persona Journeys Multi-Dimensional Segments Episerver Reach Episerver Campaign Episerver CMS Episerver Commerce Episerver Insight
  51. 51. 51 Capture Data capture and data processing  Customer segmentation  RFM  Store Transactions  Margin  Product sales  Inventory & Stock  Prices and promotion  Social interests  Social Likes  Store location  Competitive intelligence  Ratings & Reviews Loyalty Data Sales & Inventory Social data Secondary data
  52. 52. 52 Capture Analyze Run analytics-algorithms learn from data capture Single customer behavior Product attributes Other customers’ behavior  Clustering  Product Identification  Customer Profiles  Product Association  Collaborative Analytics & Algorithms  Customer segmentation  RFM  Store Transactions  Margin  Product sales  Inventory & Stock  Prices and promotion  Social interests  Social Likes  Store location  Competitive intelligence  Ratings & Reviews Loyalty Data Sales & Inventory Social data Secondary data Data capture and data processing
  53. 53. 53 Capture Analyze Visualize Data capture and data processing Run analytics-algorithms learn from data capture Push relevant content and products to consumer Product attributes  Clustering  Product Identification  Customer Profiles  Product Association  Collaborative  Customer Insights  Recommendation  Push relevant content and suitable products back to customers Analytics & Algorithms Visualization Action  Customer segmentation  RFM  Store Transactions  Margin  Product sales  Inventory & Stock  Prices and promotion  Social interests  Social Likes  Store location  Competitive intelligence  Ratings & Reviews Loyalty Data Sales & Inventory Social data Secondary data Single customer behavior Other customers’ behavior
  54. 54. 54 Unknown Customer Inactive Customer Customer with Intent Abandoned Purchase Comparison Browsing Purchasing Anticipation Care Post purchase Delivery Re-activated Re-targeting SEO/Social/Ads
  55. 55. 55 Ad Targeting SEO Listings Perform: Highly relevant alternatives based on product attributes and behavior
  56. 56. 56
  57. 57. 57 Perform: Related Recommendations - Product and Category predictive recommendations Advance: Related Recommendations Perform: Product and Category predictive recommendations Personalised Find: Site search and category landing based on previous orders and interactions Inspired
  58. 58. 58 Perform: Related Product Recommendations Advance: Conversion intent Content/Promotions Abandoned browse trigger Related Product Recommendations Conversion intent Content Store or Online?
  59. 59. 59
  60. 60. 60
  61. 61. 61 Perform: Related Product Recommendations Advance: Conversion intent Content/Promotions Order confirmation Reach: Abandoned Purchase Thank you for your order: Order #12345
  62. 62. 62 Delivery Notification
  63. 63. 63 Episerver UGC, Powered by Stackla
  64. 64. 64 Auto identify customer Reach: Related Recommendations Ad Targeting Cross-device Merging Rules based landing content & PLA Optimisation Campaign or Reactivation Automation SEO Listings Insight: Dynamic audience selection based on all behaviour
  65. 65. 65 Capture Analyse Visualise Single customer behavior Product attributes Other customers’ behavior Product Data Click Stream Behavioural Transactional Contextual Manually Crowd Behaviour Establish Intent Individual Behaviour Optimised PPC Landing Personalised Emails Relevant Triggers Individualised Recommendations
  66. 66. 66 First Name: Surname: Location: Last visit: Last online Purchase: Last instore Purchase: Store name: Served by: Days since last purchase: AOV: Last search Keyword: Last category viewed: Last product viewed: Most viewed Category: Most viewed Brand: Number of devices: Holly Golightly London, UK 10/09/2016 10/09/2016 16/11/2017 Carnaby Street Jane 43 £78.00 Black Dresses Dresses M100Blk Womens Reiss 2
  67. 67. 67 Episerver Q&A

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