A Closer Look At Digital Personalization
The importance of a personalized brand experience is constantly on the minds of marketers, brand managers and designers alike. In particular, a digital approach to personalization, if orchestrated well, provides users with an experience that is specific to their interests and behaviors.
A personalization strategy can range from the use of complex data usage – like that of Amazon and Facebook, which offers recommendations based upon viewing history or a simple approach on a more customer service oriented platform. Delivering a successful personalization strategy can be very tricky if not planned and implemented with the detail that users expect. Many initiatives fall flat and result in increased user drop rates and decreased user satisfaction.
The ideal personalization plan can bring many benefits to both the user and brand it is supporting. Driving higher conversion, the content provided to the user is highly useful and aids in saving the user time in searching for products or information they need. By connecting platforms and algorithms to cookies (or stored data), and aligning it with a user profile – similarities and assumptions can be made to identify what will be the ideal experience for a particular user.
These information gathering methods, seen to some as a privacy issue, are a set of the main tools in the digital marketing and advertising toolbox. Using this data, an ecommerce site, brand or organization can capitalize on an already interested user – or put simply, a ‘hot lead’ – and why not? In a traditional commerce setting, if a customer expresses interest in trying on a shoe – you don’t walk away and ignore them – you go get the shoe and try to sell it to them. The same goes in the digital sphere. You don’t let the customer walk away.
This all seems ideally clear, and we all know the effects of personalization – but how is the information aggregated and how does it really work? Algorithmic data is gathered in one of two ways; via Explicit or Implicit Data.
Explicit data is based on the engagements of a user and found in a few ways. Through the tracking of purchases, filling out a form, liking or sharing products/articles or setting up a new account. These actions, driven by the user are gathered and aggregated into data showing the actual user driven active actions.
Implicit data is usually the more controversial of the two. Using tracking with the aid of beacons or cookies data is gathered about the users more passive movements including geolocation (via Google), searches and overall browsing history. There are many ways to block this type of tracking by a user, however, with the use of multiple devices is usually tracked on at least one device.
Alongside these data driven approaches, another strategy to implement are the personalization needs specific to the brand or business. Apps, interactive interfaces, community building and surveys can be built and delivered to users to better understand their tailored likes, needs and preferences.
Even though digital personalization is seen more as a data driven activity, its important to ‘get personal’ and understand the users that are being engaged – which is put simply, a core of good customer service. Digital doesn’t have to sacrifice this aspect and can deliver by offering users more useful, relevant and conversion inspiring engagement opportunities. As always, testing is crucial to ensuring the right path is taken bringing the right content to the right user.