We all know that personalization has been evolving at crazy speeds for the last few years. It seems every website and company is incorporating it into their systems. So much so that it is hard to find a company that purely focuses on personalization nowadays. This is because it is a very important part of any company that has customers, in other words, it is important for every company. However, for many, the definition of personalization and how it works is still a bit confusing. This article will take you step by step to show you what personalization is, how it came about, and what it can do.

Personalization Technologies

These valuable technologies are meant to anticipate what a user wants or is searching for, and then delivering it to them quickly. The point for businesses is to keep a customer on a certain site so that a purchase can be made or advertising revenue can be maximized.

This causes businesses to mostly use Collaborative Filtering. This technology recognizes patterns in groups of people and learns what they do online. They learn the patterns that a normal webpage visiter makes from loading the page to check out. This allows the system to recommend products to buy or steps to take for what the user is most likely wanting to do.

A second kind of personalization used by businesses are Bayesian Networks. These networks take into account many things about a user and can answer questions. This is great because it learns from the user and can take data that doesn’t seem related and can actually learn from it to offer the user a result.

Thirdly, Rules-Based Engines. These can be considered “dumb personalizers” as they do not learn over time. It has a set of rules to determine what to show the user next, or what to do for the user. It is very simple to use, but lacks sophistication.

Main Stages

Standardization- This is where it all started from. Brick and Mortar stores and old websites are good examples. They wanted to create something for everyone, where the user has to go and find what he or she is looking for. This means no help of finding what is wanted except for the text on links. Whatever the goal is, the user could probably find it on the site, but it might take a long time or prove too difficult. Basically, it is devoid of personalization.

Differentiation- This started to come about once competition started creeping in. This stage is where users can pick the theme or area that they are interested in. This is kind of like a radio station where there are multiple choices and hopefully at least one choice will fit. However, this still left a lot to be desired as hunting around sites was still a chore and took time, although users started closer to their goal in the first place.

Customization- Only a few years ago, this was the main mode of personalization. Sites would let you customize what you look for. Pandora become very popular because listeners could pick the genre that they wanted and continue to teach the site what they wanted to hear. This was great and really did save a lot of time. However, the user still had to actively tell the site what to do and the learning process took too long.

Personalization- This is where we are now. Personalization actively watches what you are doing and other users as well to spot patterns and offer you options and products that they determine you are looking for. This takes out the step of the user having to hunt around a site for what they want.

Evolution

Amazon’s recommendations and Netflix were among the pioneers of bringing personalization online. It was more of a recommendation because it needed time to learn what a user is shopping for and what other shoppers have bought. Nonetheless Netflix and especially Amazon saw the potential and profits started coming in. They used a simple “if a person bought this, then they are probably looking for that” algorithm. Netflix also created a simple algorithm and created a competition with a 1 million dollar prize to whoever could beat it. One year later a company did and became much more efficient by being able to give quality recommendation with a small amount of data.

Then, the age of “Big Data” brought us into the current stage. Personalization services and tools are able to look at users search data, social networking, and basically anywhere else users can deliver data. Google uses this an extreme amount by using personalized ads in gmail and search. The other big news here is that it has moved beyond e-commerce sites and entered any user oriented site.

Noteworthy Examples

Flipora- This website has taken personalization to the next level. It was designed for people who are getting bored online, always visiting the same sites, and not discovering something new. The personalization comes into play by looking at what your social media contacts and like-minded people are engaged in. Every day there are new sites that should fit a user’s interests, and it is constantly learning your patterns and what you search for.

OkCupid- The dating site that has managed to stay online after many have failed uses personalization in a different way. The site is already designed for users to answer a few questions so that potential dates can learn more about the user. The site now uses this information for recommendations of other users, kind of like Google AdSense. This allows users to get results that they are looking for fast, without having to sift through thousands of profiles. It also increases the chance of finding a date that will actually work out. The algorithm matches people from their answers but also makes connections that aren’t obvious to most people. This is the power of having a computer doing some of your thinking.

Personalization is no longer confined to e-commerce sites. Everything from dating sites to web browsers are using it now because it works. Competition means that users have a short attention span and easily leave a site if they can’t find what they want quickly and easily. Personalizing the online experience keeps users on the site longer and creates repeat users. This is why LikeHack saw the need for truly personalized news that is based of off users and algorithms at the same time. However, still only 13% of mobile applications feature personalization, but I bet we can expect it to start growing quickly.If you have any other favorite sites or tools that are good examples of personalization, let us know!

By Idea Parcel Inc. Technology Business Development.