How Netflix defined email marketing for streaming platforms

5 email marketing learnings from the Netflix model

Netflix is committed to email marketing because this marketing technique is far from dead, and still highly relevant. Okay, boring and unimaginative emails can easily end up in people’s junk mail folder. But Netflix wants to create a hype around its content. Not only by using email’s best practices, but also by incessantly testing unique and innovative ways to get top results from this marketing channel.

Netflix uses email marketing to welcome (registration process) users to the streaming platform. After that, Netflix segments users into groups and provides content recommendations and relevant updates based on their preferences.

Learning 1 | Extensive data-driven personalisation

If you are a Netflix subscriber, you're probably familiar with the phrase "We just added a movie that you're likely to like" or "top suggestions for you". Netflix uses the information they have about your viewing habits to personalise the emails they send you. That’s why your best friend’s top suggestions might look totally different. Netflix is a data-driven company: Joris Evers, the former director of global communications once said “There are 33 million different versions of Netflix.” Netflix keeps track of the completion level for each series or film you watch, and the do that for every user coupled with your account. When you’ve watched 70% of a movie or series, they know that you are interested in that content (if you’ve only watched 20%, you probably weren’t).

Based on this, users are assigned personas. Do you watch a lot of sci-fi? Expect to get more suggestions related to that genre. As data is key at Netflix, it goes way beyond that: also your region, your search history and the moments when you fast forward or pause what you watch will influence the user personas. That in-depth personalisation is reflected in the emails you receive.

With the extensive data about the users on their platform, Netflix hyper-personalises its emails. For example, you sometimes receive an email asking you to continue watching a film or series that’s already over 50% of its viewing time on your profile. When Netflix notices that you’re watching a bit less, they will invite you via email to check out some suggestions (taking into account your viewing history). This form of nudging makes it more likely you’ll get back to watching. Compelling content visuals and the characteristic red color of the Netflix logo on large buttons are specifically designed to make you interact faster. Netflix also addresses people with emails that highlight certain shows. Some users might mistake these emails for spam. To prevent this from happening, Netflix uses an innovative combo of data personalisation and interactive email techniques. For example, they use animated GIFs in their emails to make new content stand out in your mailbox.

Learning 2 | Create a sense of belonging

Trends play a leading role in the marketing of Netflix. The popularity of a series or film can generate new subscribers and spark renewed interest among existing users. Netflix wants to capitalise on "Have you heard of that series?" and they want to emphasize that. Netflix is masterful in creating subject lines that really engage users, which truly boosts the opening rate of their emails.

Since about a year, you can see a Top 10 for trending content on the platform per country. This list is reflected in their emails: "This is the top 10 of your country at the moment". As this list is constantly changing, Netflix sends this type of email to their subscribers on a monthly basis.

Netflix performs about 250 A/B tests per year to determine via machine learning (technique used to analyze large data sets) which emails work best. It’s a method that many email marketing programs, such as Hubspot, offer to send the best email option to a specific user segment. Accurate segmentation is crucial here, because the more specific the segmentation, the better the A/B test will work and the more relevant your email will be to the user. It allows us to determine if changes to the email improve conversion rates. Customers choose all kinds of different paths based on their different unique backgrounds and this is where machine learning comes in. If you want to personalize your campaign to be more convenient for an individual customer, without looking endlessly at data spreadsheets, machine learning can help you create better segmentation here. An example of a machine learning tool is optimizely and many CRM platforms have built-in tools to do this automatically.

Learning 4 | Holiday-related content

Many email marketing companies have a content calendar on which they build their email marketing. In that sense, Netflix and other OTT platforms have less luxury. There are only two periods in a year that really play on a specific type of content: Halloween and Christmas. On those two occasions, you can bet your bottom dollar that you’ll find inspirational emails with horror-themed series for Halloween and Christmas film suggestions in your inbox.

Learning 5 | And the competition subtly copies…

Because Netflix was the first real OTT platform, they actually inspired other platforms to adopt their marketing strategy. Disney + is a good example of a fairly new player that uses many of the same methods for their emails. See if you recognize this pattern?

• One-time welcome email and registration

• Top suggestions (usually with a newly released series or movie in the spotlight at the top) or an overview of what’s new (in Disney+’s case)

• For you

• Continue watching or watch again

• Holiday-related content

Conclusion

Netflix has a flexible set of emails that they send out to their subscribers on a regular basis. These are highly personalised, using subscriber data drawn from the platform. And ultimately, every streaming platform is focusing strongly on user re-engagement today, driven by a smart use of personalisation. People have to keep watching to renew their subscription and keep business profitable. It's not just about watching movies and series anymore, it's about data ...