Induced by password sharing and credentials theft, account sharing is a fraud typology seen in high volume across every content streaming service available today. 

Though it’s only in recent months that one streaming service, Netflix, missed growth targets in part due to account sharing to a degree that has forced their hand on cracking down on the “friendly” version of the practice (intentionally sharing accounts with a user the account owner knows). 

For a company that has historically welcomed account sharing, (as it meant better validation of their content and cheap advertising of the service), Netflix is now in a balancing act where, amidst strong competition, it must attract new users to the platform at an attractive enough price point that backs into healthy margins, while simultaneously maximizing revenue streams coming from existing users. 

This inflection point poses a challenge to the company and is one every company will reach once their account sharing fraud costs eat far enough into the margins per user. 

Though if the right approach is taken to capture rich behavioral data on its users and their devices, companies facing account sharing pains can formulate pricing and feature policies that insulate their businesses in the long run. 

In this post, we’ll outline the impacts of account sharing fraud on Netflix, and ways behavioral data acquisition would aid efforts to recoup revenue lost from the practice.

What users get from a Netflix account

Today, any Netflix user is allowed five different profiles on their individual account in nearly all regions around the world Netflix serves.

These profiles can be accessed through the same username and password, and represent different “friends and family” members on an account, reflecting their individual preferences, watch patterns, and suggested content.

Every profile on the account has access to the entire Netflix content library and depending on the amount paid per month, Netflix sets varying limits on the number of concurrent streams and content downloads per account (done by tracking multiple devices on a single account).

Impacts of Netflix account sharing

While historically Netflix has encouraged sharing account passwords between people of the same “household” (a term used ambiguously from a legal standpoint), this kind of credential sharing is technically a service violation of Netflix’s terms of service and user agreements. 

Recent performance metrics shed light on why Netflix is taking a more aggressive stance on cracking down on password sharing, even if shared with a family member or friend.

From Netflix’s Q1,22 letter to shareholders:

“Our revenue growth has slowed considerably as our results and forecast below show. Streaming is winning over linear, as we predicted, and Netflix titles are very popular globally. However, our relatively high household penetration – when including the large number of households sharing accounts – combined with competition, is creating revenue growth headwinds.

…in addition to our 222m paying households, we estimate that Netflix is being shared with over100m additional households, including over 30m in the UCAN region. Account sharing as a percentage of our paying membership hasn’t changed much over the years, but, coupled with the first factor, means it’s harder to grow membership in many markets – an issue that was obscured by our COVID growth.” 

Key performance metrics:

• Saw a loss of 35% of the total market cap 3 days after posting a shareholder letter on 4/19/22 (over $59B in market cap loss)
  
• Saw a decrease in YoY revenue growth from the previous quarter (9.8% from 16%)
  
• Saw a decrease in global streaming paid memberships from the previous quarter (loss of ~200,000)
  
• Saw it’s first quarterly subscriber loss in a decade 
  
• Est. 100M households using the service without paying for membership

Clearly, there are other factors contributing to Netflix’s recent performance in both the stock market and internally as a company. Though in Netflix’s own statement, the impacts of account sharing at their scale severely impede their ability to attain revenue and user acquisition targets. 

Since Netflix content is operationally expensive to deliver, account sharing on Netflix at its current rate further fractions the revenue acquired per user relative to service delivery cost. Now the company is forced to either push a lower service price to reduce the sharing frequency or push a higher service price to recoup lost revenue from sharing.

It has already implemented regional experiments to test the waters with a reduced price approach, charging fees in Chile, Costa Rica, and Peru for adding members to a profile or transferring a profile to a separate account.

Guiding policy with behavioral data

For Netflix, and any other company experiencing account sharing fraud eating into unit margins, starting with a proper data foundation provides the ability to identify and segment multiple users and devices under a single account. 

With fine-grained behavioral data, companies like Netflix can, from the onset of the user lifecycle at creation, all the way through their service usage, build the proper heuristics to detect account sharing and react with an appropriate policy.

Behavioral data like keystroke dynamics, clustering algorithms applied on timing vectors, device motion and magnetometer tracking not only help determine devices used commonly on a particular profile under a single account but further, help identify different people using the same device under those accounts. 

At this level of granularity, policies aimed at curtailing account sharing or applying certain revenue strategies become flexible and easy to implement. Some examples include:

Build internal “Owner / Sharer” profiles

Behavioral data can be used to identify the individual and device associated with opening the account initially, or the individual and device used to input the payment method. Feature privileges/locks can be applied based on the profile.

Granular ad display

Using the same profiles, Netflix can choose to show ads specifically to “sharer” profiles, or to certain users on certain devices deemed not the “owner”. This would allow Netflix to recoup revenue loss from account sharing by subsidizing costs from ad payments while still allowing users to share accounts. 

Refined recommendations

By using behavioral data to understand if a different user is using the same device/account, Netflix can provide tailored content recommendations on application upstart, reducing the time it takes for a user to start content or time to see an ad.

Tightened security for non “owner profiles”

Someone who gets a Netflix password from an owner might share that password with another person. This 3rd-degree sharing can be prevented by prompting the owner device with a security notification if a 3rd-degree device attempts to input even correct credentials to get into an account.

Data is the key to detecting sharing

There is no silver bullet to consensual account sharing, and its impacts on companies like Netflix are undeniable. But with the proper behavioral data gathered on users, segmenting users into devices and people becomes possible.

It is through this granular level of segmentation that companies like Netflix and others can flexibly apply UX friction to discourage practices that hurt their bottom line or apply supplementary monetization strategies to users with varying risks of churn.

Behavioral data unlock more possibilities than just raising or lowering service prices and crossing fingers after. For Netflix, proper application of behavioral data can mean the difference between planning strategies for long-term performance or losing its footing by reacting to the competition and seeing the benefits from account sharing that they used to.