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Hello! Thank you for reading this article. This time I'll be writing about "personalization." Over the past several years, you hear personal-related terms a lot, right? Maybe because I'm an only child, my personal space is on the narrow side. AT Field deployed.
1. What Is Personalization?
"Personalization" means serving up content differently for each customer in order to appropriately meet customer needs. It analyzes data such as purchase behavior and browsing history to maximize the user experience. Representative elements that form the basis of personalization include demographics (demographic attributes), context (background information), and behavior.
Similarly, a term you hear a lot lately is "customization." The goal of "drawing users' interest" is shared, but the path to getting there differs. Customization is something carried out by the customer/user. Making the settings screen your preferred one, or adjusting layout, content, functions, and so on — that's customization. A familiar example is social media features. Making your own posts visible only to specific people, hiding posts you don't want to see, notifying by person or by page, and so on. Similar, yet different.
2. Concrete Examples
Concrete examples of personalization include the following.
■ Amazon The most familiar is the great master Amazon. The recommendation "recommended for you" is one example. Based on purchase and browsing history, it suggests things that suit the user's tastes.
■ Airbnb Airbnb personalizes the content it provides based on users' in-app behavior data. Based on information like past itineraries and sightseeing preferences, it suggests lodging and experience events that match the user's tastes. Not only that — it also suggests restaurants and sightseeing spots near the travel destination, tailored to individual preferences!
■ Starbucks Coffee Starbucks's app is built so it can offer personalized special coupons based on the customer data the app already holds. It records which coffees you order most, what times you drink them most, which stores you frequent, and so on. For example, if a user who usually buys decaf drinks walks near a store, a "decaf-product coupon" is pushed to the app; meanwhile, a user who doesn't usually buy sweets is shown a "one free sweet" coupon.
■ Nike Fitness App Nike's fitness app, rather than offering generic training content, provides content matched to the user's individual level. First, the user sets an exercise goal. After that, the app records the user's fitness progress and, based on that, suggests the optimal training content for the user to reach the goal. It's like training alongside a personal trainer!
3. Finally
Personalization, which suggests/provides things suited to each individual, is very convenient, isn't it! I too tend to end up buying things when Amazon recommends them to me. However, as I wrote about in the previous GDPR piece, care is needed in handling personal information. The information that can be collected may change going forward. Thank you for reading this time as well!