7 Pillars Of Data Strategy - High Five 2018

8. METHOD SAVVY - ALL RIGHTS RESERVED D A T A I S N O W U B I Q U I T O U S • Proper management and utilization of this resource will differentiate in the short term. • This will be assumed and mandatory to stay competitive in years to come. @EvanLevy

9. METHOD SAVVY - ALL RIGHTS RESERVED D A T A & A N A L Y T I C S S K I L L S C R I T I C A L T O S U C C E S S • To be successful in 2020: the most important skill will be the ability to work with data & analytics.

11. METHOD SAVVY - ALL RIGHTS RESERVED Data must be organized, “refined” and put to use to be valuable. Expensive analytics software with no strategy is the modern “throw money at a problem and hope it goes away.” #High5Co nf @EvanLe vy

18. METHOD SAVVY - ALL RIGHTS RESERVED “We’re not that much smarter than we used to be, even though we have much more information—and that means the real skill now is learning how to pick out the useful information from all this noise.” Nate Silver American statistician and writer Editor in Chief, FiveThirtyEight #High5Co nf @EvanLe vy

23. METHOD SAVVY - ALL RIGHTS RESERVED G R E A T P L A N T O M A K E M Y C O M P A N Y M O R E $ $ $ $ $ • Phase 1: Amazing new (software/agile method/team structure etc.) • Phase 2: ???? • Phase 3: Profit!!!!!

26. METHOD SAVVY - ALL RIGHTS RESERVED Proper use of analytics empowers you to make more (and better!) decisions in the same amount of time, without feeling exhausted by the end. #High5Co nf @EvanLe vy

29. METHOD SAVVY - ALL RIGHTS RESERVED W H A T T O C O N S I D E R W I T H Y O U R D A T A S T R A T E G Y 1. The Questions 2. Technical Implementation 3. The Users 4. Data Storage & Structure 5. Data Security 6. Personally Identifiable Information (PII) 7. Visualization & Analysis Needs @EvanLevy

30. METHOD SAVVY - ALL RIGHTS RESERVED T H E Q U E S T I O N S ( A K A P R O B L E M S )1 @EvanLevy • The more valuable your question, the more valuable analytics is to the company • Walk before you run – start with questions that produce focus for decision makers (including yourself!) • Data maturity • What happened? • What’s happening? • What’s going to happen?

31. METHOD SAVVY - ALL RIGHTS RESERVED A S K S P E C I F I C Q U E S T I O N S O F Y O U R D A T A • Data absent context is rarely helpful. • Push yourself (and your org) to conduct action-oriented analysis that is focused on the business problem. • Will this report help me understand what to do next? • Automate tasks that divert time away from high value analysis as much as possible. @EvanLevy

32. METHOD SAVVY - ALL RIGHTS RESERVED 2 T E C H N I C A L I M P L E M E N T A T I O N @EvanLevy • The most valuable data sets require high levels of customization to the code sending data to your analytics platform • Understand the technical limitations of your developer resources • You don’t have to know how to code it, but you need to be able to translate the VP’s business goal > marketing KPIs > technical needs to create the data set • HBR has recently dubbed this role the “analytics translator”

33. METHOD SAVVY - ALL RIGHTS RESERVED 3 @EvanLevy T H E U S E R S • Who needs to access the data for analysis and who should be allowed to make changes to the platform or data source? • Always make sure there is a company-owned admin user profile that is not attached to a specific individual. • Please. Always have a company-owned Admin user that is not attached to a specific individual.

34. METHOD SAVVY - ALL RIGHTS RESERVED 4 @EvanLevy D A T A S T O R A G E • How much data will you be storing/analyzing? • A few hundred leads? • Millions of site visits? • How long will you need to keep it? • Do you need to combine or clean data before it’s ready for your visualization platform?

36. METHOD SAVVY - ALL RIGHTS RESERVED 5 @EvanLevy D A T A S E C U R I T Y • Are you following appropriate user access controls? • Do your software integrations create other risk points? • Are there government regulations to be aware of (HIPAA, etc)?

37. METHOD SAVVY - ALL RIGHTS RESERVED 6 @EvanLevy P E R S O N A L L Y I D E N T I F I A B L E I N F O R M A T I O N ( P I I ) • Are you capturing PII as a dimension (email, phone #, etc)? • Hint: PII can slip by in URLs, too • Are you passing that information into an analytics platform like Google Analytics? – that can get your account banned! • Use off-line keys to match user data, or anonymize & aggregate (best customers, new customers, etc).

39. METHOD SAVVY - ALL RIGHTS RESERVED 7 @EvanLevy V I S U A L I Z A T I O N & A N A L Y S I S • Evaluate data source flexibility with software • Who is the audience for your analysis and reporting? • What level of context do they have? • What are the top 3 things they’re interested in? • How frequently does the view need to be refreshed?

41. METHOD SAVVY - ALL RIGHTS RESERVED T I P S F O R S U C C E S S F U L D A T A V I S U A L I Z A T I O N S 1. Again, consider the audience 2. Make sure your labels are clear 3. Minimize styling while creating emphasis -- @EvanLevy

43. METHOD SAVVY - ALL RIGHTS RESERVED T I P S F O R S U C C E S S F U L D A T A V I S U A L I Z A T I O N S 1. Again, consider the audience 2. Make sure your labels are clear 3. Minimize styling while creating emphasis - 4. Avoid pie charts if you have more than a handful of segments @EvanLevy

46. METHOD SAVVY - ALL RIGHTS RESERVED T I P S F O R S U C C E S S F U L D A T A V I S U A L I Z A T I O N S 1. Again, consider the audience 2. Make sure your labels are clear 3. Minimize styling while creating emphasis - 4. Avoid pie charts if you have more than a handful of segments 5. Make sure your data visualization accurately represents the data - (I’m looking at you truncated Y axis) @EvanLevy

48. METHOD SAVVY - ALL RIGHTS RESERVED T O R E V I E W – D A T A S T R A T E G Y C O N S I D E R A T I O N S 1. The Questions 2. Technical Implementation 3. The Users 4. Data Storage & Structure 5. Data Security 6. Personally Identifiable Information (PII) 7. Visualization & Analysis Needs @EvanLevy

49. METHOD SAVVY - ALL RIGHTS RESERVED B O N U S ! S O M E O F M Y F A V O R I T E R E S O U R C E S • Analytics Strategy by Avinash Kaushik: https://www.kaushik.net/avinash/ • Advanced Google Tag Manager: https://www.simoahava.com/ • Advanced Google Sheets training: https://codingisforlosers.com/ • Time saving reporting tool: https://supermetrics.com/ • Google Analytics setup: https://www.lunametrics.com/blog/

52. T H A N K S www.evan-levy.com Evan@MethodSavvy.com

7 Pillars Of Data Strategy - High Five 2018

Evan Levy

7 Pillars Of Data Strategy - High Five 2018