What you can learn from FANG about personalization and performance

What you can learn from FANG about personalization and performance

Personalization isn’t just a powerful tool for big players like Facebook, Amazon, Netflix, and Google (aka FANG). It’s a powerful way to create unique experiences and increase your chances of success in the future. Advances in technology have made it possible for developers and marketing departments to gain insight into behavior to deliver personalized experiences that are specifically targeted to the needs and expectations of individual customers.

Curious about the impact personalization can have for your business? Research by Infosys reveals that 31 percent of surveyed consumers say they wish their shopping experience was far more personalised than it currently is and 59 percent believe it has a noticeable impact on purchasing. And according to a 2017 report, 44 percent of consumers say that they will likely become repeat buyers after a personalized shopping experience with a particular company. Nearly half of shoppers surveyed have purchased a product that they did not initially intend to buy after receiving a personalized recommendation from a brand.

Digital success: What we can learn from FANG

So, how do the companies of FANG use personalization? Let’s take a look at how these tech behemoths have transformed consumer expectations and have continuously been able to provide people with experiences that keep them coming back for more.

Integrate personalization into the entire experience

Early Amazon implementations were fairly simple, providing additional product listings with "People who bought this item also bought…" underneath your purchase items. Those early examples have now expanded into integrating recommendations across the entire buying experience with algorithms based on a shopper’s previous purchase history, items in their shopping carts, items they’ve rated and liked, and what other customers with similar purchasing patterns have viewed and purchased.

Using advanced artificial intelligence, machine learning, and predictive analytics, Amazon is able to entice visitors not just to shop once, but to return again and again and facilitate new item discovery. In fact, the retail giant estimates that 35 percent of its sales are generated from their recommendation engine.

Use data-driven testing

Similar to Amazon, content discovery driven by a recommendation engine is at the core of Netflix's personalization based on previous viewing history, recommendations for similar shows, and even the time of day you normally watch. For instance, they even personalize landing cards (the images for different shows) — when the company found that 82 percent of a user’s focus is on these cards, they decided to create a system that allowed them to test different images.

The streaming company also runs around 250 A/B tests per year to test different design experiences or mechanisms for finding shows.  Every action you take — whether it’s play, pause, or stop — Netflix is constantly gathering data on your preferences. The ability to put the right content in front of the right person is crucial, but it can backfire. The company has been criticized for targeting thumbnail artwork that some viewers say is based on race. Taking note of not crossing the line from convenient to creepy is crucial when personalizing your digital experience.

Delivering products based on personalization

Facebook's personalization is inherent to its product, with the bulk of content coming from people and interests you have personally chosen to engage with. Your feed itself is pretty straightforward and includes the people and brands you interact with most. This makes ad targeting especially simple, as there is so much data to work with and users may have even liked the product pages themselves.

Similarly, personalization is baked into almost all of Google’s many massive software products — Gmail, Google Maps, Google Calendar, etc. While the company may have reported to have dialed back on personalized search, it’s still very clear that everything from past search history, location, and browsing history is being used to help personalize the user experience. For example, Google will keep track of your upcoming travel reservations or other plans you’ve scheduled in your calendar or inbox and will notify you before the scheduled time if the information is on your phone.

How to deliver the same experiences as big tech

Living up to the standards set by these giants is overwhelming, but don’t fall into the trap of thinking you need to be exactly like them. You should learn from the best — but don’t forget that web experience goes beyond personalization.

Building a great web experience involves creating a healthy balance between performance and personalization. And research shows this goes for everyone — including big companies:

  • Facebook employs load-balancing in order to ensure a fast experience for their users and have run experiments that show their users view more pages and get more value out of the site when it runs faster.

  • Amazon has found that a page load slowdown of one second could cost them $1.6B in sales.

  • Netflix reduced outbound traffic by 43 percent after enabling basic compression, reducing bandwidth cost by millions.

  • Google reports that an extra 0.5 seconds in each search page generation would cause traffic to drop by 20 percent.

Personalization is not something that is coming in the future — it's happening now. Enacting it as part of your overall strategy will keep users happy and nurture your ongoing relationship with them leading to more repeat customers. It will give your audience a better online experience and prompt customers to buy more, increasing your revenue. With users at the center, web performance and personalization work together to keep your business profitable and dynamic.

Curious about how we can help? Learn more about what we do at Instart to help you master personalization without compromising user experience here.