Más relevancia: Campañas más efectivas potenciadas por datos profundos de tus usuarios
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"Más relevancia: Campañas más efectivas potenciadas por datos profundos de tus usuarios." Conoce la presentación de Jeff Mills en Digital Marketing University 2013 en Ciudad de México. Dicen que los datos son “el nuevo petróleo.” Pero lograr un entendimiento profundo de quién es cada cliente ha sido históricamente difícil. Hemos evolucionado hasta el punto en que los marketeros ya no necesitan adivinar quiénes son sus consumidores a partir de datos de comportamiento. Mediante la fuente de datos adecuada, un marketero puede construir detallados perfiles de clientes y desarrollar un conocimiento en profundidad del perfil demográfico, intereses e intenciones de su audiencia. En esta sesión describiremos qué datos están disponibles para las empresas, cómo capturar esta información y utilizarla para potenciar la segmentación y targeting en tus campañas de marketing digital.
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Más relevancia: Campañas más efectivas potenciadas por datos profundos de tus usuarios
- 1. Drilling into the Data Well for Deeper Customer Intelligence ©2013
- 2. 9% of marketers use customer data effectively ©2013
- 3. 98% of consumers are frequently mistargeted ©2013
- 4. What we’re talking about today 1 Collecting the right consumer data 2 Transforming data into insight 3 ©2013 How to leverage your data
- 5. Brands that win prioritize engagement over exposure ©2013
- 6. Understanding customers is the key to Engagement ©2013
- 7. But what do marketers really know about us? ©2013
- 8. What does the future hold? ©2013
- 9. ©2013
- 10. Internet Explorer and Firefox have 45% share Internet Explorer Firefox ©2013
- 11. Say goodbye to tracking nearly ½ of consumers? ©2013
- 12. Marketers are incapacitated by data silos Email ©2013 eCommerce CMS CRM Subscription Management
- 13. What’s the formula for personalization? ©2013
- 14. Personalization = P = RD + C + TA Right Data + Content + Technology Automation ©2013
- 15. Collecting the right consumer data ©2013
- 16. Is behavioral data all that matters? It’s not who you are underneath… …It’s what you do that defines you. ©2013
- 19. Demographic data is still the most collected and utilized by marketers SOURCE: 2012 BRITE - NY AMA Marketing in Transition Study ©2013
- 20. Registration data is more important than ever Registration First name:* Last name:* Company name: Email:* Address:* City:* State/Province:* Zip/Postal Code:* Phone Number:* ©2013
- 21. And brands are taking notice ©2013
- 23. Social login leads to more registrations and data Your Site ©2013
- 24. Social profile data is accessed with permission NPR would like to access some of your LinkedIn info: ©2013
- 25. Registration using social login is faster and leads to better data quality ©2013
- 27. ©2013
- 28. Social profile data Demographics Name • Gender • Birthdate Photo • • • • • Location Educatio n Marital Career • Psychographics Friends • • • • ©2013 Interests Music TV Political • • • • Movies Books Hobbies Religious
- 29. But wait, isn’t all data from social networks unstructured? ©2013
- 30. But wait, isn’t all data from social networks unstructured? No. ©2013
- 31. Facebook profile circa 2006 Favorite Books: “mostly biographies and textbooks” ©2013 Interests: “making things”
- 32. In 2010, Facebook began enforcing validation rules on profile fields ©2013
- 33. In 2010, Facebook began enforcing validation rules on profile fields ©2013
- 34. Facebook profile circa 2010 ©2013
- 35. Social profile data comes from multiple sources ©2013
- 36. Social network stream data ©2013
- 37. Social network streams offer inferred insights Brand advocate Customer service candidate In market ©2013
- 38. Surveys drive insight about how customers think ©2013
- 40. Web browsing behavior can predict intent ©2013
- 41. Determine preferences using transaction data Image Quantity Price Date Canon Digital Rebel Camera 1 $550.00 10/4/2013 Universal Camera Case 1 $34.00 10/4/2013 Apple MacBook Pro Notebook PC 1 $2,299.00 7/22/2013 Kenneth Cole New York Men’s Shoes ©2013 Product 2 $321.98 4/16/2013
- 42. Campaign interactions enable relevancy ©2013
- 44. 4 steps to transform data into insight 1 Normalize 2 Cluster 3 4 ©2013 Visualize Segment
- 45. Data needs to be normalized City Portland State Oregon Country United States City Portland State OR Country USA Location Portland, OR ©2013 Country US
- 46. Data needs to be normalized First Last Last, First Full Name Michael Olson Olson, Michael Michael Olson ©2013
- 47. Use machine learning to create clustered segments Likes Animal House Likes Ace Ventura Likes Bradley Cooper Likes Bridesmaids ©2013 Likes Office Space SEGMENT: Comedy Enthusiasts
- 48. Understand the composition of your customers ©2013
- 49. Match content and offers to customer segments Male Age 45-64 Lives in Rural Location Female Age 35-44 Environmental Advocate Male Age 18-29 HH Income $30-$50K ©2013
- 50. Match content and offers to customer segments ©2013
- 53. Universal Music segments emails based on location and interests Emails personalized based on music preferences and location. Significant increase in email open rates ©2013
- 54. Samsung creates targeted email campaigns using social profile data Results 34% more likely to open emails 63% more likely to click-through emails ©2013
- 55. Paper Style employs behavioral segmentation for emails Results • • ©2013 161% increase in email CTR 330% increase in revenue per email
- 57. Comparing purchase conversion rates In-Store 30% ©2013 Online 3%
- 58. The in-store shopping experience is personalized ©2013
- 59. The in-store shopping experience is personalized ©2013
- 61. Sun & Ski sports recommends products based on behaviors Results • • ©2013 79% increase in purchase conversion rates 25% increase in net revenue
- 62. Walmart’s Shopycat app recommends gift ideas based on friends’ interests ©2013
- 63. …and lets consumers treat themselves Interests: Tetris, Bradley Cooper ©2013
- 64. Segmenting travel content based on demographics ©2013
- 65. Segmenting travel content based on demographics Younger audience ©2013 Older audience
- 67. Deconstructing social data Cookie-based data • • • More scale Implicit data Lower CTR and response rate per impression ©2013 First-party consumer data • • • Less scale Explicit data Higher CTR and response rate per impression
- 68. Ad targeting using social data ©2013
- 69. A few final tips 1 Know your buyer personas 2 Start simple – go GAL! 3 Align that content! ©2013
- 70. A few final tips 1 Know your buyer personas 2 Start simple – go GAL! 3 Align that content! ©2013
- 71. A few final tips 1 Know your buyer personas 2 Start simple – go GAL! 3 Keep that content in alignment! ©2013
- 72. A few final tips 1 Know your buyer personas 2 Start simple – go GAL! 3 Keep that content in alignment! ©2013