Pragmatic Guide to Enhanced Data Capabilities
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The document is a pragmatic guide by Jeff Potter on enhancing data capabilities, emphasizing the importance of data in today's fast-paced environment. It outlines a structured approach for prioritizing and managing data through a hierarchy of needs and provides practical examples for implementing analytics frameworks. Additionally, it discusses potential data projects and suggests methods for building a data-centric team.
Pragmatic Guide to Enhanced Data Capabilities
- 1. A Pragmatic Guide to Enhanced Data Capabilities
- 2. I am Jeff Potter Former Director of Analytics at Jane.com Currently Building an Analytics Consulting Firm Hello! 2
- 3. “ Pragmatic: dealing with things sensibly and realistically in a way that is based on practical rather than theoretical considerations. 3
- 4. 4 Overview 1. Why is data so important right now? 2. How should I think about data? 3. How can I prioritize the right data? 4. What data projects am I missing?
- 5. Why is data so important right now?1 5
- 6. Why is data so important? Speed of Disruption 6
- 7. 7 Time to 1B Valuation
- 8. Why is data so important? Data Volume & Structure Speed of Disruption 8
- 9. “ 9 90% of all the data in the world has been generated over the last two years
- 10. Why is data so important? Data Volume & Structure Speed of Disruption Computational Capabilities 10
- 11. 11
- 12. 12 Do I have these data problems? ● Ecommerce Example ○ Millions of Customers ○ Thousands Products ○ Thousands of Orders / Day
- 13. 13 Do I have these data problems? ● Oil & Gas ○ Few Customers ○ Hundreds of Oil Rigs ○ Thousands of Measurements / Day
- 14. “ 14 Every company will be a technology company
- 15. “ 15 Every company will be a technology data company
- 16. How should I think about data? 16 2
- 17. 17 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI
- 18. 18 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Produce: Track user behavior and business events in applications and send for collection
- 19. 19 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Collect: Collect accurate, comprehensive behavioral data from users and systems
- 20. 20 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Process: Sessionize, stitch identities, classify users, and technology
- 21. 21 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Model: Categorize traffic, connect external data sources, prepare for detailed analysis
- 22. 22 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Analyze: Dashboards, analysis, anomaly detection
- 23. 23 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Optimize: Segmentation, A/B Testing, marketing automation
- 24. 24 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI AI: Machine learning and AI to predict future events
- 25. How can I prioritize the right data? 25 3
- 26. 26 Overview of Process 1. Identify your Data Sources 2. Implement an Analytics Framework 3. Identify your Key Business Events 4. Identify primary business Questions 5. Integrate your Data 6. Create Actions and Measure outcome
- 27. Kora Fitness - Apparel 27
- 28. 28 Process Applied 1. Identify your Data Sources
- 29. Kora Fitness - Data Sources 29 Shopify Google Analytics Zendesk Instagram Facebook Adwords Google Business Harvest Bamboo HR SlackSurvey Monkey Trello
- 30. 30 Process Applied 1. Identify your Data Sources 2. Implement an Analytics Framework
- 31. “ Mental models (or framework) can help shape behaviour and set an approach to solving problems and doing tasks 31
- 32. Pirate Metrics Framework (AARRR) 32 Phase Function Acquisition Generate attention through a variety of activities Activation Turn interest into users who are using your product or service Retention Convince user to come back repeatedly, exhibiting sticky behavior Revenue Business outcomes (purchases, clicks, content created, subscription) Referral Viral and word-of-mouth invitations to other potential users
- 33. Pirate Metrics Framework (AARRR) 33 Phase Function Acquisition Generate attention through a variety of activities Activation Turn interest into users who are using your product or service Retention Convince user to come back repeatedly, exhibiting sticky behavior Revenue Business outcomes (purchases, clicks, content created, subscription) Referral Viral and word-of-mouth invitations to other potential users
- 34. Pirate Metrics Framework (AARRR) 34 Phase Function Acquisition Generate attention through a variety of activities Activation Turn interest into users who are using your product or service Retention Convince user to come back repeatedly, exhibiting sticky behavior Revenue Business outcomes (purchases, clicks, content created, subscription) Referral Viral and word-of-mouth invitations to other potential users
- 35. Pirate Metrics Framework (AARRR) 35 Phase Function Acquisition Generate attention through a variety of activities Activation Turn interest into users who are using your product or service Retention Convince user to come back repeatedly, exhibiting sticky behavior Revenue Business outcomes (purchases, clicks, content created, subscription) Referral Viral and word-of-mouth invitations to other potential users
- 36. Pirate Metrics Framework (AARRR) 36 Phase Function Acquisition Generate attention through a variety of activities Activation Turn interest into users who are using your product or service Retention Convince user to come back repeatedly, exhibiting sticky behavior Revenue Business outcomes (purchases, clicks, content created, subscription) Referral Viral and word-of-mouth invitations to other potential users
- 37. Pirate Metrics: An Analytics Framework 37 Acquisition Activation Revenue Retention Referral
- 38. 38 Process Applied 1. Identify your Data Sources 2. Implement an Analytics Framework 3. Identify your Key Business Events
- 39. Kora Fitness - Data Sources 39 Shopify Google Analytics Zendesk Instagram Facebook Adwords Google Business Harvest Bamboo HR SlackSurvey Monkey Trello
- 40. Kora Fitness - Data Sources 40 Shopify Google Analytics Zendesk Instagram Facebook Adwords Google Business Harvest Bamboo HR SlackSurvey Monkey Trello
- 41. 41 Data Sources Key Business Processes Framework Phase Google Analytics New Visitor Product Page Viewed Item Added to Cart Order Created Acquisition Activation Activation Revenue Shopify Order Created Return Created Customer Created Revenue Revenue (Contra) Activation Facebook Campaign Run Acquisition Zendesk Ticket Created Ticket Resolved Retention Retention
- 42. 42 Data Sources Key Business Processes Framework Phase Google Analytics New Visitor Product Page Viewed Item Added to Cart Order Created Acquisition Activation Activation Revenue Shopify Order Created Return Created Customer Created Revenue Revenue (Contra) Activation Facebook Campaign Run Acquisition Zendesk Ticket Created Ticket Resolved Retention Retention
- 43. 43 Data Sources Key Business Processes Framework Phase Google Analytics New Visitor Product Page Viewed Item Added to Cart Order Created Acquisition Activation Activation Revenue Shopify Order Created Return Created Customer Created Revenue Revenue (Contra) Activation Facebook Campaign Run Acquisition Zendesk Ticket Created Ticket Resolved Retention Retention
- 44. 44 Data Sources Key Business Processes Framework Phase Google Analytics New Visitor Product Page Viewed Item Added to Cart Order Created Acquisition Activation Activation Revenue Shopify Order Created Return Created Customer Created Revenue Revenue (Contra) Activation Facebook Campaign Run Acquisition Zendesk Ticket Created Ticket Resolved Retention Retention
- 45. 45 Data Sources Key Business Processes Framework Phase Google Analytics New Visitor Product Page Viewed Item Added to Cart Order Created Acquisition Activation Activation Revenue Shopify Order Created Return Created Customer Created Revenue Revenue (Contra) Activation Facebook Campaign Run Acquisition Zendesk Ticket Created Ticket Resolved Retention Retention
- 46. 46 Data Sources Key Business Processes Framework Phase Google Analytics New Visitor Product Page Viewed Item Added to Cart Order Created Acquisition Activation Activation Revenue Shopify Order Created Return Created Customer Created Revenue Revenue (Contra) Activation Facebook Campaign Run Acquisition Zendesk Ticket Created Ticket Resolved Retention Retention
- 47. 47 Data Sources Key Business Processes Framework Phase Google Analytics New Visitor Product Page Viewed Item Added to Cart Order Created Acquisition Activation Activation Revenue Shopify Order Created Return Created Customer Created Revenue Revenue (Contra) Activation Facebook Campaign Run Acquisition Zendesk Ticket Created Ticket Resolved Retention Retention
- 48. 48 Data Sources Key Business Processes Framework Phase Priority Google Analytics New Visitor Product Page Viewed Item Added to Cart Order Created Acquisition Activation Activation Revenue Low Low High High Shopify Order Created Return Created Customer Created Revenue Revenue (Contra) Activation High High High Facebook Campaign Run Acquisition Medium Zendesk Ticket Created Ticket Resolved Retention Retention Low Low
- 49. 49 Data Sources Key Business Processes Framework Phase Priority Google Analytics New Visitor Product Page Viewed Item Added to Cart Order Created Acquisition Activation Activation Revenue Low Low High High Shopify Order Created Return Created Customer Created Revenue Revenue (Contra) Activation High High High Facebook Campaign Run Acquisition Medium Zendesk Ticket Created Ticket Resolved Retention Retention Low Low
- 50. 50 Process Applied 1. Identify your Data Sources 2. Implement an Analytics Framework 3. Identify your Key Business Processes 4. Identify primary business Questions
- 51. 51 Unsolved Business Questions 1. Am I spending my marketing dollars wisely? 2. How long are customers staying with me? 3. How is my onboarding experience? 4. Which products are my best? 5. How long until I need to reorder?
- 52. 52 Process Applied 1. Identify your Data Sources 2. Implement an Analytics Framework 3. Identify your Key Business Processes 4. Identify primary business Questions 5. Integrate data and refine data
- 53. 53 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Shopify Data: Does a lot of this for you but if you want to export the data you will lose several layers
- 54. 54 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Shopify Data: Exportable Shopify Data is at this stage of the hierarchy
- 55. Integration Overview 55 Shopify Google Analytics Zendesk Your Database Reports Dashboards Analysis
- 56. 56 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Integrated Data: Model the data into more accessible table using SQL, reformat dates, and lookup enrichment data.
- 57. 57 Process Applied 1. Identify your Data Sources 2. Implement an Analytics Framework 3. Identify your Key Business Processes 4. Identify primary business Questions 5. Integrate data and refine data 6. Create actions and measure outcome
- 58. 58 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Integrated Data: 1. Setup basic visualization tool to speed up analysis. 2. Conduct analysis based on onboarding question
- 59. 59 Data Hierarchy of Needs Produce Collect Process Model Analyze Optimize AI Integrated Data: Create an A/B test to improve onboarding rate X%
- 60. What data projects am I missing? 60
- 61. 61 Churn Prediction E-Commerce Shopify Support Move up Hierarchy OrderPlaced ShipmentCreated OrderCount ShippingCarrier ShippingClass SupportTicketCreated Predict
- 63. 63 Churn Prediction Telecom Phone System Support PhoneUsedInMinutes VoicemailConfigured FeatureXUsed FeatureYUsed SupportTicketCreated Predict Move up Hierarchy
- 66. Cohort Analysis 66 Month 0 Month 1
- 67. Cohort Analysis 67 Month 0 Month 1 Month 2
- 74. Cycle Time Analysis 74 How many times does a customer perform the core action on the expected cycle?
- 80. Amazon Prime Cycle Time 80 $30 Avg Cart * 365/7-day shipping cycles = $1560 $30 Avg Cart * 365/2-day shipping cycles = $5475
- 81. Additional Project Ideas ● Scenario Modeling ● Recommender Systems ● CLV Prediction ● Lead Scoring ● Employee Churn Prediction ● Funnel Analysis ● Behavioral Segmentation 81
- 82. 82 Overview 1. Why is data so important right now? 2. How should I think about data? 3. How can I prioritize the right data? 4. What data projects am I missing?
- 83. Any questions ? You can find me at ◉ LinkedIn: Jeff Potter ◉ jeff.potter6@gmail.com Thanks! 83
- 84. BONUS: How can I build a data team? 84 2
- 85. Analytics Maturity Model 85 Phase Questions Foundations Is the data correct? Descriptive Analytics What is happening? Diagnostic Analytics Why did this happen? Predictive Analytics What will happen?
- 86. Foundations Team 86 Marketing Lead Support Lead Engineer Low Cost Dashboard Cloud Services Built-in Reports
- 87. Descriptive Team 87 Marketing Lead Support Lead Mid-Level Analyst Mid Tier Dashboard Integration Service Providers Engineer
- 88. Diagnostics Team 88 Marketing Lead Support Lead Mid-Level Analyst BI Platform Integration Service Providers Data Engineer Data Warehouse
- 89. Prediction Team 89 Marketing Lead Support Lead Mid-Level Analyst BI Platform Integration Service Providers Machine Learning Engineer Data Warehouse Data Engineer Business Predictions Product Predictions Analyst
- 90. Analytics Defines and monitors metrics, and crafts narratives around data. Data Science Paths 90 Algorithms Builds and interprets algorithms that power products. Inference Establishes causal relationships with statistics
- 91. Analytics Information Systems Accounting Finance Economics Where to find these? 91 Algorithms Computer Science Game Programming Physics Robotics Math Inference Statistics Economics Finance Math
- 93. 93 References Pirate Metrics: Dave McClure - https://www.slideshare.net/dmc500hats/startup-metrics-for-pirates-long-version Cycle Time Analysis: Josh Elman - https://news.greylock.com/the-only-metric-that-matters-now-with-fancy-slides-23 2474cf414c Airbnb Data Science Tracks - https://www.linkedin.com/pulse/one-data-science-job-doesnt-fit-all-elena-grewal/