How to Build a Corporate Culture of Data | Gwen Miller | Kin Community
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Data is a fundamental element of digital media. It’s intertwined with everything we do and when you harness it right you can uncover incredible insights that make your content better, build your audiences and increase sales. There’s so much data available that even if you build a specialized and dedicated data team they still won’t be able to manage and interpret all of it. The only way to manage this flood of data in today’s modern digital media companies is to empower every employee to be a data expert. But how do you do that? This seminar provides a detailed road map to how to transform your organization into a data-first group, drawing on Gwen Miller’s experience doing just that at Kin Community. Learn how you can first become an expert data evangelist, then best practices for developing custom data priorities for every individual and team and then how to teach those teams to replicate the process outwards, and begin their own personal data journeys.
![The weighted-average first 30 day [engagements / views] on
all videos that turned 30 days old in the last 3 months on a
channel, compared to a platform average baseline.
ER30](https://image.slidesharecdn.com/gwenmillerdatadrivenorgfull-170626232149/85/How-to-Build-a-Corporate-Culture-of-Data-Gwen-Miller-Kin-Community-12-320.jpg)
![How good a channel is at converting unsubscribed views
into subscribers.
Efficiency Rate [YT Only]
Subscribers Gained
Unsubscribed Views](https://image.slidesharecdn.com/gwenmillerdatadrivenorgfull-170626232149/85/How-to-Build-a-Corporate-Culture-of-Data-Gwen-Miller-Kin-Community-13-320.jpg)
![How many of a video’s views came from your subscribers.
Subscribed Views [YT ONLY]](https://image.slidesharecdn.com/gwenmillerdatadrivenorgfull-170626232149/85/How-to-Build-a-Corporate-Culture-of-Data-Gwen-Miller-Kin-Community-32-320.jpg)
![How many of a video’s views came from people who were
not subscribed to your channel at the time of viewing.
Unsubscribed Views [YT ONLY]](https://image.slidesharecdn.com/gwenmillerdatadrivenorgfull-170626232149/85/How-to-Build-a-Corporate-Culture-of-Data-Gwen-Miller-Kin-Community-34-320.jpg)
![How many views on a FB video were pushed by shares.
Shared Views [FB ONLY]](https://image.slidesharecdn.com/gwenmillerdatadrivenorgfull-170626232149/85/How-to-Build-a-Corporate-Culture-of-Data-Gwen-Miller-Kin-Community-36-320.jpg)
![Engagement Rate [YT]
Total Comments + Total Likes
+ Total Dislikes + Total Shares
Total Views](https://image.slidesharecdn.com/gwenmillerdatadrivenorgfull-170626232149/85/How-to-Build-a-Corporate-Culture-of-Data-Gwen-Miller-Kin-Community-39-320.jpg)
![Engagement Rate [FB]
Total Comments + Total Reactions
+ Total Shares
Total Views](https://image.slidesharecdn.com/gwenmillerdatadrivenorgfull-170626232149/85/How-to-Build-a-Corporate-Culture-of-Data-Gwen-Miller-Kin-Community-40-320.jpg)
![Graph which shows whether the % of
audience still watching at any given
second in a video is above or below
platform average for videos of a similar
length.
Relative Retention Graph [YT Only]](https://image.slidesharecdn.com/gwenmillerdatadrivenorgfull-170626232149/85/How-to-Build-a-Corporate-Culture-of-Data-Gwen-Miller-Kin-Community-45-320.jpg)
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How to Build a Corporate Culture of Data | Gwen Miller | Kin Community
- 1. How to Build a Corporate Culture of Data GWEN MILLER DIRECTOR, DATA & STRATEGY
- 3. 1. Get Access 2. Spend time in the data 3. Pick a couple of metrics you understand and concentrate on those first 4. Be a Data Evangelist Dig Into the Data Yourself
- 4. 1.Add teammates to your analytics systems I. As possible, add people as analysts, not admins for security reasons. Empower Everyone to Find Data
- 6. Talent Team
- 7. Average first 30 day views for all videos that turned 30 days old in the last 3 months on a channel. V30
- 12. The weighted-average first 30 day [engagements / views] on all videos that turned 30 days old in the last 3 months on a channel, compared to a platform average baseline. ER30
- 13. How good a channel is at converting unsubscribed views into subscribers. Efficiency Rate [YT Only] Subscribers Gained Unsubscribed Views
- 17. 291 3524 = 8%
- 18. Year over year views growth when comparing the last 90 days to the same 90 day period one year ago. Views Growth Rate (Current Views – Past Views) Unsubscribed Views
- 24. (Current Views – Past Views) Past Views
- 25. (26,503– 1,298) 1,298 = 1942% Growth
- 26. The average videos uploaded per month over the past three months Avg Monthly Video Uploads Total Uploads Last 90 Days Three
- 29. 13 3 = 4.33
- 30. Search YouTube for videos from related creators and/or similar topics to the video you’re uploading. Upload Consistency
- 31. Production Team
- 32. How many of a video’s views came from your subscribers. Subscribed Views [YT ONLY]
- 34. How many of a video’s views came from people who were not subscribed to your channel at the time of viewing. Unsubscribed Views [YT ONLY]
- 36. How many views on a FB video were pushed by shares. Shared Views [FB ONLY]
- 39. Engagement Rate [YT] Total Comments + Total Likes + Total Dislikes + Total Shares Total Views
- 40. Engagement Rate [FB] Total Comments + Total Reactions + Total Shares Total Views
- 41. Average View Duration Average length of time viewers viewed your video. Average Percentage Viewed Average percentage of your video viewers viewed.
- 45. Graph which shows whether the % of audience still watching at any given second in a video is above or below platform average for videos of a similar length. Relative Retention Graph [YT Only]
- 48. Sales Team
- 49. 1. General A. Total Views B. Total Followers C. General Demographics (Age, Gender, Country) D. V30 E. ER30 Facebook Audience Insights
- 50. Your viewer's detailed demographics, habits, hobbies, spending habits and values, etc. In-depth Demographics + Psychographics
- 53. 1. Demographics A. Lifestyle B. Relationship Status C. Education Level D. Job Title 2. Page Likes A. What other FB pages they like 3. Locations A. Cities/ Countries/ Languages 4. Activities A. Content + Ad Engagement vs platform average B. Devices Used 5. Household A. Household Income B. Home Ownership C. Household Size D. Home Market Value E. Spending Methods 6. Online Purchases A. Retail Spending B. Online Purchases C. Purchase Behavior D. Home Market Value E. Vehicle In-Market Data Facebook Audience Insights
- 55. 1. In-market Audiences A.E.G. Costumes, Toys & Games, Fine Jewelry, etc. 2. Affinity Audiences A. E.G. Family Television Fans, Action Game Fans, Water Sports Enthusiasts. 3. Demographics A. Age B. Gender C. Parental Status 4. Devices YouTube Remarketing List Insights
- 56. Compare metrics to the average of your competitive set. Benchmarking
- 57. 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 MultiplierfromAverage Engagement Rate as Compared to Average (Average = 1) Facebook Average Kin Pushes 2x the Average Facebook Engagement Rate
- 58. 1.64x 7,000 4,275 = V30 Competitive Benchmarking Example
- 60. Finance Team
- 61. ? Views ? Monetized Views/Monetization Rate ? CPM The Components of Adsense Revenue
- 62. Amount earned per 1000 ad impressio
- 63. Amount earned per 1000 monetized playbacks
- 64. 1.Pre-Roll 2. Mid-roll 3.Overlay Ads 4.Display Ads Ad Types
- 65. This number will always be higher than
- 66. this number
- 67. # of Playbacks that have at least 1 ad appear on them.
- 68. YouTube Ad Revenue = (Estimated Monetized Playbacks/1000) X Playback- Based CPM
- 69. YOUR Estimated Ad Revenue = YouTube Ad Revenue X Your Split
- 70. ? Your Views go down ? Your CPM goes down ? Your Monetization Rate goes down 3 Reasons Your Revenue Goes Down
- 71. Monetization Rate Estimated Monetized Playbacks Total Views
- 73. Factors that go into monetization rates 1. Viewer Ad Load A. How many ads have they already watched in this session? B. How tolerant of ads is the viewer? 2. Content Ad Receptivity A. Ad View Rate (Effected by content type, content length) 3. Market Demand A. Seasonality B. Demographics C. Preferred Program 4. Monetization Status A. Content Eligibility B. YouTube Kids App C. Embed Location D. Ad Blockers
- 74. Final Thoughts
- 75. 1. Talent Team A.V30 B.ER30 C.Efficiency Rate D.Views Growth Rate E.Avg Monthly Video Uploads 2. Production Team A. Subscribed Views B. Unsubscribed Views C.Shared Views D.Engagement Rate E.Average View Duration F. Average % Viewed G.Retention Graphs 3. Sales Team A. Total Views B.Total Followers C.General Demographics (Age, Gender, Country) D.V30 E.ER30 F. Advanced Demographics/ Psychographics Benchmarking 4. Finance Team A. How monetization works B.Total Views C.Monetization Rate D.CPMs Cheat Sheet - Concepts by Department
Editor's Notes
- #2: 1) Gwen Miller 2) Digital Lifestyle Company - Imagery 3) Corporate Culture of Data - everyone empowered 4) Small companies - excuse - no expertise 5) Large companies - excuse - we have a data team for that 6) simple easy things you can no matter what the expertise level 7) I don’t care how big the data team, not gonna be big enough. 8) so simple, grade school math 9) experts more so for you.? 10) Gonna go through the departments and what they should know. ?She’s so wrong, think about it.? 11) We’re just gonna touch on some key areas for each department. If you want my full guide to what I think the essentials, there is a a longer version of this deck which I believe Jim will be sending out post Vidcon. And/or you can screen cap my overall cheat sheet at the end of this presentation which should get you close.? 12) Last note, most of the?metrics I’m going to talk about can be found in the YouTube and the Facebook CMS’s so if you are a company that creates the content or has access to creators in your CMS, you can get this info for free. If you’re a brand working with a creator, you may have to ask them to screen cap this info for you. And the remainder of the metrics, come from a tool called Tubular Labs, which is a third party analytics collector that can be really useful, but all the metrics I’m going to share from them today can be found on the free version of their product on their website.? Let’s get started.??
- #74: .