Spelling and other minor fixes for the Netflix post

content/posts/2024-netflix-best-shows/index.md

@@ -28,7 +28,7 @@ Most recently my 10 year old had this experience for the first time also, as I h
 
 ## Big Data Is Hard
 
-Statistical analysis is very easy to skew into "expected results". This is known as Confirmation Bias - often Data Analysts will unconciously (or even conciously) slice and aggregate their data to fit their theories. With Watching data I can see where it is infinetely harder, because people watch in so many different ways and patterns. Some bindge entire seasons, others watch episode or even part of an episode at a time - in sessions that may have days/weeks between them. Is it because show is uninteresting or because they have busy lives?
+Statistical analysis is very easy to skew into "expected results". This is known as Confirmation Bias - often Data Analysts will unconsciously (or even consciously) slice and aggregate their data to fit their theories. With Watching data I can see where it is infinitely harder, because people watch in so many different ways and patterns. Some binge entire seasons, others watch episode or even part of an episode at a time - in sessions that may have days/weeks between them. Is it because show is uninteresting or because they have busy lives?
 Another huge factor is Exposure - Can't watch something you never heard about! When Netflix started producing their own content - their biggest issue became making consumers Aware that show/movie exists! They didn't yet have any venue for "coming soon", there were no Ads in their own content, to cross-promote. Really they had Nothing - yet they somehow expected consumers to all Jump on new Original Content and when they didn't - conclusion "Bad Content!". I loved Sense8 and The OA, but by the time I discovered that they exist - they were Long Cancelled!
 A very large factor in distorted results is incomplete or inaccurate data collection. Are they correctly collecting viewership on all devices - what if it is casting from phone to SmartTV with some exotic OS? or Nest device with a screen? And what about the all too common situation where content keeps playing long after the viewer fell asleep?
 A related phenomena I saw first hand is in Ad business - most Ads, even those clicked on, are "false positives". Advertisers (on DSP) know that "exposure" data is flawed - if you start asking consumers who supposedly saw your Ads what do they remember - majority don't remember anything, not the product name nor the company name...
@@ -41,11 +41,12 @@ I really wish they instead embrace the beautiful "Leaving soon, Watch Now!" warn
 ## Solution Ideas
 
 I don't claim to have all the answers, these are hard problems that will take time to solve. For starters it is important that we understand our limitations when making decisions based on data. Last thing Netflix wants is disgruntled consumers - some get so emotionally invested that they may swear-off Netflix from young age!
-1. Focus on continously improving data collection, with real-world testing to confirm accuracy. All analysis is only as good as the input data it gets!
+
+1. Focus on continuously improving data collection, with real-world testing to confirm accuracy. All analysis is only as good as the input data it gets!
 2. Don't be afraid of creative approaches to confirm assumptions. Actually ask in the app - would you like to remove this show from Continue Watching because you didn't like it?
-3. Discovery is still a huge problem - find ways to show trailers even to non-Ads consumers. Offer bigger banners for new releases with some teasers. Be creative here - and ensure all analysis of popularity takes into account how "discoverable" and "promoted" this new content was in the first place! And why not have Netflix's own annual Awards show for original content - cheap enough to produce and viewers can quickly get a taste of "What's new and good" on the platform?
-4. People get invested into seeing stories to conclusion - this is both Useful for content producers and a possible trap. One solution for expensive productions is to make a single-story movie (perhaps with underlaying hints for a bigger "conspiracy"), and if successful make additional movies in the same Universe/Series.
-5. Consider the cost from the get-go - I am sure productions get green-light based on some sort of statitical analysis for how many subscribers like similar content and thus potential viewers. But how accurate is this - if director isn't the same, or actors differ, it can have huge impact on seemingly similar script. And what about Potential subscribers - surely Netflix needs to entice people who look at the catalog today and say "nothing interesting for me here"...
+3. (New Show) Discovery is still a huge problem - find ways to show trailers even to non-Ads consumers. Offer bigger banners for new releases with some teasers. Be creative here - and ensure all analysis of popularity takes into account how "discoverable" and "promoted" this new content was in the first place! And why not have Netflix's own annual Awards show for original content - cheap enough to produce and viewers can quickly get a taste of "What's new and good" on the platform?
+4. People get invested into seeing stories to conclusion - this is both Useful for content producers and a possible trap. One solution for expensive productions is to make a single-story movie (perhaps with underlying hints for a bigger "conspiracy"), and if successful make additional movies in the same Universe/Series. On a related note - Latest Neuroscience can help here, for example excellent book by Jonah Lehrer [How We Decide](https://www.amazon.com/How-We-Decide-Jonah-Lehrer/dp/0547247990?tag=craftonia-20).
+5. Consider the cost from the get-go - I am sure productions get green-light based on some sort of statistical analysis for how many subscribers like similar content and thus potential viewers. But how accurate is this - if director isn't the same, or actors differ, it can have huge impact on seemingly similar script. And what about Potential subscribers - surely Netflix needs to entice people who look at the catalog today and say "nothing interesting for me here"...
 
 ![Netflix Viewers In Pain](people_crying_for_netflix_cancellations.png)