Netflix’s Calculated Bet on Streaming

October 4, 2011

Update:

A few days after this post, Netflix decided to abandon its recently announced streaming-only strategy and instead retain its original combined Streaming + DVD business. All I can say is that correlation is not causation.

The following analysis is my opinion only and contains a set of assumptions which may or may not be accurate. Do not use this for investments or financial decision-making. All the analysis is based on public information only, as stated in my Policy.

Netflix Cost Structure Analysis

  • What is the impact of Netflix’s decision to focus on Streaming–Only on their cost structure?
  • Will the decrease in the cost structure offset any loss in subscriptions of customers who wanted DVD as an option?

I have attempted to estimate the Netflix cost structure 2 scenarios: (1) If Netflix had continued the blended (combined streaming + DVD) options, and (2) Streaming-only Option. Netflix has provided guidance that they expect 24 million subscribers in Q3 2011 with 12 M subscribers for both DVD & streaming, 9.8M for streaming only and 2.2 M for DVD only.

Assuming the same ratio Blended, Streaming-Only and DVD -Only users, I have estimated the Cost/ Subscription/ Month at different r user subscription numbers for the Blended scenario. In addition, I have also made estimates for the cost structure for the Streaming-Only scenario.


Key Takeaways:

  • Looking at the above graph, the blended business will have the same Cost/ Subscription/ Month at 24M users as the Streaming-Only business at 17M users  –  $11.8 per subscription per month). So of the 12 M users who are subscribing to both streaming and DVD, at least 7.2M will need to convert to Streaming-only in order to retain the same Cost/ Subscription/ Month.
  • However, Netflix has mentioned that they will maintain the same operating margins. Therefore, for the pricing of the Streaming- Only business to be at $8, the number of subscribers has to be close to 30M, which means they have to acquire an additional 6 M customers over and above their current base. Alternatively, they will have to either increase prices or come up with premium pricing tiers.


Below is the cost breakdown estimates for the scenario with 24M subscribers as forecast by Netflix for Q3.


Assumptions

NOTE: I have made many assumptions since the 10-K does not break out costs very granularly. These assumptions may or may not be accurate enough. If readers can come up with better assumptions, do let me know in the Comments section and I will rework the numbers.

  1. I have used the 2010 Netflix 10-K as the basis for many cost items, since the 2011 Netflix 10-K will only be available at year end.
  2. It is expected that streaming content acquisition is going to cost a lot more going forward.  Assumption:Content acquisition costs = $1.6 B / year. Source: http://www.trefis.com/stock/nflx/articles/73421/the-failed-netflix-starz-deal-highlights-the-rising-costs-of-netflixs-growth/2011-09-06
  3. I’ve assumed that DVD content acquisition cost in the blended scenario is one-tenth of the Streaming content acquisition costs. This is under the assumption that Netflix is not going to invest much in DVD content acquisition.
  4. DVD operational costs: I used the 2010 Netflix 10-K as the basis, in which I assumed that DVD operational cost is 55% of total subscription costs. This comes to $ 634 million total or $ 3.58 per subscriber per month. Assumed the same cost per subscriber per month for DVD operations going forward as well. .
  5. Streaming operational costs: Assumed 50 cents per user per month to cover credit card and cost of streaming.
  6. Fulfillment cost: based on 2010 10-K, fulfillment cost = $1.15 per subscription per month. The same value is assumed.
  7. Assumed 10% increase in Technology, Marketing,  G&A over 2010.

I’d appreciate reader feedback on the following:

  • Has streaming hit the mainstream for family viewing or is it still the domain of singles watching movies/ shows on their laptops and iPads?
  • Following Netflix’s announcement that it is abandoning the Streaming-Only strategy, I am guessing that they may have determined that they cannot retain the requisite number of subscribers to make Streaming-Only a viable option.What do you think?

Email as the Ultimate Deal Aggregator

September 6, 2011

Almost everyone has an email id that receives deals, mailers, discount coupons, and ‘mass’ emails. Wouldn’t it be useful if email could aggregate deals, recommend related products, filter out deals that do not meet requirements and even unsubscribe to less relevant deals?

 

How would this work?

This would work by integrating email with a deal aggregation engine in the backend.

  • First, a separate tab is provided for deals. This tab will contain functionality built specifically for deals. Putting deals in a separate tab will also reduce Inbox clutter.
  • Users are asked for their preferences and targeting information such as Categories of interest, Gender, Location, Favorite merchants, Price preferences (by product category) and so on. Based on this, the deal aggregation engine would find all deals that match the user’s criteria. For example, if  the user provides “Spa Services” as an area of interest, the deal aggregation engine would fetch Spa related deals from Groupon, Living Social and other daily deal services.
  • Apart from daily deals, the email aggregator would find coupons for the user’s areas of interest. For example, if I indicated “Babies/ Children” as a category of interest, it would sign me up for Babies R Us or Target’s Baby coupons. For “Books”, it would sign me up for Barnes & Noble or Amazon coupons. I could also specify individual retailers that I like to shop at, say New York & Company, and the deal finder would crawl for their coupons and push them into my Inbox.

Here is why email is the ideal deal aggregation platform:

  • Most deal notifications happen via email subscriptions. By integrating email with deal aggregation, users do not have to take the trouble to subscribe to individual deals. They would have to indicate their preferences just one time and their email based aggregator will do the rest.
  • Email can help reduce user deal fatigue. Even though email tends to get cluttered with mass mailers, deals and coupons, it is the right medium to organize deals in such a way as to get users only the deals they want.

Google+ vs Facebook: Initial Thoughts

July 4, 2011

After taking the tour and going over the demo, here is an initial take on whether Google+ is a threat to Facebook.

Google+ addresses some key gaps in Facebook very elegantly and intuitively.

Circles is an excellent concept and addresses a key issue that people face on Facebook.  My Facebook network is an amalgam of all the other networks in my life – casual friends, close friends, family, cousins, work colleagues and acquaintances. Most people interact differently with the various networks in their lives, but Facebook does not do a very good job of facilitating this online. I have to say that Facebook’s “Friends Lists” is somewhat clunky and not very well implemented.

Google Circles is a very elegant approach to segmenting my friends and interacting differently with them, just like in real life. Its implementation intuitively makes sense.

Hangouts addresses another Facebook gap. Many a time have I felt that I’d like to interact with some of my friends more closely instead of only responding to their status updates or watching their photos. Many of my friends are scattered all over the world and I’d like to have the opportunity to hang out with them again. And Google’s Hangout, with its excellent video service seems like a great way to do this.

But there are switching costs in moving from Facebook to Google+

By itself, it does not seem likely that people will move over to Google+ from Facebook, even though Circles and Hangouts are excellent features. The big factor that will prevent switching is the Network effect. Many people have at least 100 friends on Facebook and it is going to be hard to move with all one’s friends to Google Plus.

Another major switching cost is that people have a lot of photos on Facebook. Of course, if Google were to introduce a photo transfer feature to enable people to port their photos over from Facebook it will make it easier. People also belong to many groups on Facebook but I am not sure that this is a major blocker, because people are usually passive members of groups and tend to forget about their groups soon after joining.

It would also be interesting to see whether Google+ has a feature to let people port over their friends and content such as photos or wall posts. This might reduce some switching costs.

Facebook can (and likely will) replicate Circles and Hangouts:

Even though Circles and Hangouts are intuitive features that address key gaps in Facebook, Facebook ought to be able to replicate these so that people do not have an incentive to switch. I expect that they will come up with a way to let people do what Circles enables them to, which is to segment their friends and present different updates, photos and views of themselves to their different friends’ circles. Similarly, I expect Facebook will provide sophisticated video chat capabilities to match Hangouts.

Fundamentally, Facebook is a great product and more importantly, has a hard-to-replicate ecosystem. It only has to address its gaps and make sure there are not many incentives to switch.

Integration with Google products could be the Game-changer

However, there is one factor that could get people to start using Google+ at scale. How well Google+ is integrated with popular products such as Gmail, Search or Android could be the game changer.

And this is where I’d like to actually get an invite and check out for myself how well Google Plus is integrated with Search, Gmail and Android. I plan to have an updated post after I tinker with Google Plus. Watch this space.


How Should Recommendation Engines Deal With Multi-user Accounts?

June 12, 2011

I’ve lately been thinking about how recommendation engines handle situations where a single account has multiple users with widely divergent preferences. For example, my family has a single Netflix account, but my husband and I have very different preferences. He likes “Back to the Future” and Alfred Hitchcock movies. I, on the other hand, like “Maid in Manhattan”, “Price & Prejudice” and “The Mummy”. Won’t this confuse recommendation engines?  

 

An obvious solution is to base recommendations on categories. If someone has a preference for a romantic comedy such as ‘Maid in Manhattan”, show them another in the same category such as “My Best Friend’s Wedding”. This way, there are recommendations for the different users based on their categories of interest.

However, the disadvantage of only relying on recommendations within categories is that it does not leverage the richness you can get by having recommendations across categories. For example, people who prefer crime thrillers such as “The Bone Collector” may also like action movies such as “Terminator” and comedies such as “There’s something about Mary” Providing recommendations across categories provides many more choices and will delight users.  

The problem is that basing these recommendations on data from multi-user accounts can confuse the recommendation engine. For example, based on preferences within my account, the engine could come up with “Maid In Manhattan” for someone who liked “Back to the Future”. But this would not work for a single user account owned by a woman who only liked “Maid In Manhattan”.      

How to solve this problem?

Thumbs Down/ Thumbs Up: Letting users give the thumbs down or thumbs up to recommendations or categories of recommendations could allow the engine to give richer recommendations based on multiple categories while allowing some users to filter out irrelevant categories. In the above case, the woman with the single user account can give a Thumbs Down to “Back in the Future” (and its category) and never have to see similar recommendations again.        

A better solution is:    

Obtain multi-user information and tailor preferences: It would make sense for recommendation engines to ask if there is more than one user, and obtain the preferences of each user. This way, it can tailor recommendations for individual users. This way, for my husband, based on his interest in Alfred Hitchcock movies, it can show screwball comedy recommendations such as “There’s something about Mary”, while it would not do so for me. The UI will have to be adapted accordingly to support this.

In addition, it can also provide ‘linked’ recommendations by identifying patterns where users typically interested in romantic movies tend to have partners interested in action thrillers and sometimes tend to have children interested in Disney movies. Thus,  it can make recommendations for one user based on their partner’s very different preferences.


Linkedin Today: Customizability Would be Even Better

May 22, 2011

So Linkedin has provided what I’ve wanted Facebook to do, ie allow me to access News of interest to me in a separate tab. I am a news junkie and I find this feature pretty useful for the following reasons:

  • It helps me be well informed about my areas of interest without having to visit many sources individually. Most of the major tech news portals that I visit are represented in one place.
  • I have discovered interesting news sources that I previously did not access.
  • I can share news articles of interest with contacts and comment on them. This is another opportunity to ‘interact’ with my contacts. I use this feature in tandem with Twitter and it works pretty well.

 

From Linkedin’s perspective, this feature incentivizes users to visit more, spend more time and engage actively. I find that I spend a lot more time now because of Linkedin Today than I did before.

How Linkedin can make this a more useful feature:

  • I would like to see more customizability and be able to choose my own news sources in addition to the ones Linkedin generates for me. There are other new sources and blogs pertaining to my industry that I have bookmarked in my Google Reader and regularly access but these are not available on Linkedin Today. For example, I can access Techcrunch, Gigaom and Venturebeat amongst a host of others via Linkedin Today. But I also regularly view PPC Hero and Search Engine Watch, which do not show up on my Linkedin Today page.

Bottomline: Linkedin Today helps me discover new news sources, but it also should let me add sites of interest to me so that I have a single source for business and industry news.

  • I would also like to distill content shared by specific contacts or groups of contacts. I may weight or respect certain contacts more than others and consider them thought leaders. In such cases, I’d like the news articles they are reading or recommending to be displayed more prominently.
  •  This is totally unrealistic, but I’ll say it anyway. Most people spend at least 30 minutes on their daily morning commute to work. Wouldn’t be awesome to be fully informed of the news in one’s industry on my commute? So if there were a way to transcribe the written content into audio, then a lot of people could connect their cell phones to a car speaker and get their morning news on the way to work and be upto speed on business news. Just sayin’.     

The New York Times Pay Plan

May 20, 2011

The New York Times’ pay plan is not geared for success, though I’d like to be proven wrong because want to believe that somewhere on the internet there is a pay model for content that can work. But alas, I am skeptical. The WSJ and the Financial Times can do this because they target specialized area that people think will help advance their careers.

Here is my old post on the subject.


What sort of revenue models would work best for Quora?

March 7, 2011

I’ve been experimenting with Quora, a new Q&A and discussion site. Quora’s big differentiator is that it provides high quality responses often by users who are experts in their fields. So what kind of revenue model would be a good fit for such a service?

1.       Highly targeted advertising: The ads would be almost an extension of the information that the users are seeking. Since users show interest in Topics such as Travel, Parenting and so on, the ads can reflect those interests and also specifically target questions that the users are trying to get answered. For example, for “ What is a good off-season time to travel to Switzerland” with answer “April” the best type of ad would be “Hotel in Zurich, Book now for April Deals”.

 

Additionally, the targeting can be based on a user’s history on Quora, aggregating their interests in different topics. For example, an ad could be targeted to users who are parents with interests in technology and travel.

 

2. Allowing advertisers to sponsor answers: For the question above on travel to Switzerland, you could have a tour operator offer an informed and detailed answer while subtly marketing their product. Even for more esoteric questions such as “Do supermarkets use purchasing data to find correlations between different products where one wouldn’t normally think there is a strong correlation” –  retail or pricing consultants could provide an informative answer while pitching their services. Of course, such a response would be called out and labeled as Sponsored. Done right, Sponsored answers will add value and be useful to users, instead of being just a distraction, which is the case with most forms of advertising.