The Netflix team remained undeterred and continued to refine its product, striving to improve its customer’s experience. They soon perfected their distribution network and developed an innovative recommendation engine that suggested movies based on previous purchases.

By 2005 Netflix had four million subscribers and established itself as the market leader in movie rentals. In 2010, the company made a profit of more than $160 million, while Blockbuster filed for bankruptcy. In the same year Netflix shifted focus to online streaming. Recognising the trend of widespread broadband adoption, which presented the technological infrastructure to stream its movies and offer its customers instant gratification. Today Netflix remains the global leader in movie streaming, and has 139 million subscribers in over 190 countries.

Netflix’s story demonstrates that the shift in focus from product-led to experience-led has been prevalent for decades, and if businesses get too comfortable and take their foot off the gas even for a second (Blockbuster) it can spell disaster. It’s the fast-moving businesses that are constantly appraising industry, seeking opportunities to champion change even when the status quo is working fine that continue to win. When Netflix made the switch to streaming, its DVD business was still profitable, and yet it recognised that if it didn’t reinvent itself to fulfil the constantly evolving demands of its consumers and keep up with the technological advancements it would ultimately fail.

Understanding its need to constantly enrich the user experience, Netflix took learning’s from elsewhere in the eCommerce world creating its personalised recommendation engine to suggest films the user may like. This helped to create brand loyalty and most importantly grow trust in the Netflix brand.

Many businesses fail in creating meaningful personalised content because they have the wrong objective front of mind. They start with the solution that they think their customer wants and work backwards. The danger is if you start with the wrong assumption you’re never going to win. Start by asking meaningful questions that will allow you to create a detailed customer journey map guided by the customer themselves. By building personalisation on true customer-insight Netflix can create a detailed customer journey map, which will allow them to understand the idiosyncrasies of its customer. A strong KPI for Netflix could be to minimise abandonment rates. If for example a user stops watching content halfway through, it is important to try to understand why; did they not like it or did someone knock on the front door? To understand this we need to consider the wider behaviour. Did they, for example, start watching something else? Was it late at night and they could have gone to bed? Did they exit Netflix immediately after? By recognising these external metrics we can understand how to activate future personalisation. Should Netflix send an email to remind the user to complete the content? Should they recommend other content similar in theme or update the algorithm to acknowledge that it’s unlikely that this type of content will be appropriate for the user?

The goal in all personalisation is to become relevant in the customer’s life through the delivery of engaging, persuasive, informed targeted content that people can relate to, trust and is culturally relevant. A fundamental aspect of this is understating whom it is you are targeting. This will feed into creating detailed customer personas.

In the ever-evolving feedback loop of personalisation we can use live insights to continually shape and refine personas to identify key trends within demographics which can produce additional revenue-generating opportunities.

By establishing the demographics that are watching particular content, Netflix can use this insight to forecast future audience personas and target businesses for product placement for its original in-house productions. A key consideration when developing personas is past behaviour is the best predictor of future behaviour.

Personalisation profoundly impacts how businesses amplify their brand and demonstrate how it adds value to its customers. Consumers today are not fooled by vanity driven personalisation. Days of when good brand personalisation was an email that mentioned your name at the start of a generic body of content are thankfully a thing of the past. Now customers expect content that is specifically targeted to their needs and interests. All of our email inboxes are bombarded daily with a sea of newsletters, promotional emails and unsolicited offers. And yet email marketing executed well is still one of the strongest methods of activating a call to action. But we can only create this meaningful personalisation by taking the time to understand the consumer’s needs and wants. Once we know that we can provide reasons for the customers to trust us and to meet their unmet needs.

We know that trust is one of the founding pillars of personalisation, customers have invited your brand into their lives, they want to receive content from you; they are interested in what you have to say and recognise that you meet their needs. If however, we break this trust by offering them something that they don’t want we can damage the relationship. It can take years to build a reputation on trust, but just one bad decision to ruin it. By investing time and resource in creating accurate customer personas we’re minimising this risk as the better we know our customers the more informed we can be in our recommendations.

Recognising this, Netflix use email to amplify its messaging around its recommendation engine, identifying content that users may like, have stalled watching or is trending within the persona peer group. Activating persona peer groups is particularly effective as brand awareness and trust are largely dependant on suggestions from other users rather than traditional channels of communication. Even today, the most effective form of marketing is still word of mouth, the challenge is in how to activate and use it; Netflix do this effectively through robust tried and tested personas that are constantly updated. It understands that if Persona A likes XYZ, their peer group profile will also most likely enjoy XYZ. This is because friend groups generally have shared common interests.