We look at different approaches to personalization, explaining two main trends: rules-based and automated with the pros and cons of each.
TL;DR: A recent study by Evergage Inc. revealed that only 30% of the surveyed companies are satisfied with the personalization efforts of their marketing teams. This shows that marketers need to step up their game and with this article we help them do so. We look at different approaches to personalization, explaining the two main trends: rules-based and automated with the pros and cons of each. Additionally, we show you how to apply both and which one might be the right choice for you.
Everyone is talking about personalization but… Often when you hear the word, it is used as this incredibly broad term, encompassing everything! Like marketing magic, that increases everything from conversion rates and leads to sales. Well, that is of course not how things really work.
It is a hard-to-define concept as it means something different to everyone but to give a broad definition: personalization is showing targeted content to different segments of your audience to enhance their experience and increase your conversion rate. The ways of doing so can be explained through a spectrum of different methods, with rules-based and automated personalization as the two ends of this spectrum.
This spectrum also contains methods such as contextual segments, behavioral targeting, integrated 1st and 3rd party audiences, frequency and recency, 1–1 content attributes, and recommended content. But to be honest with you, while these may be presented as different personalization methods at times, they actually all fall under rules-based and automated (algorithm-based) personalization, which are the focus of this article.
It is important to keep in mind that the goal of both methods is the same, and the difference lies in the way of getting there. Now, let’s take a look at each of these approaches, define what they are, analyze their pros and cons, and help you figure out which might be the better option for you!
Rules-based personalization is when you manually create certain rules to target different segments of your audience, deciding on which content to show to whom and when. These rules encompass things such as location, weather, time, device type to referral source, abandoned cart, whether the visitor is a new or recurring user etc. The possibilities are nearly endless.
This is a manual process where you decide on the audience segments and create different versions of your page for each segment. On top, you set up rules to define which page variation will be triggered. It can be considered similar to A/B testing in the sense that it is a process of trial and error as you test different options and keep on tinkering and improving.
With rules-based personalization there is certainly a learning curve. As you start discovering new possibilities, you come up with new ideas and learn what really affects conversion. This will take some time and effort at first, but once you are on a roll it gets much easier and much faster.
Additionally, you could and you should keep on trying various options, this is the only way to know what works best in your specific case. Gotta keep on testing on your way to good, better, and best!
Automated personalization is personalization through machine learning algorithms, where each variation is automatically crafted for the individual visitor of the website. Decisions are made based on the existing metadata, as well as demographics and past behavior. The quality of these algorithms heavily relies on the amount of data you can provide. The more individual use cases you feed it with, the better they get at crafting an individual experience.
While the advancements in AI and machine learning will bring along new possibilities, today’s understanding of automated personalization is quite limited. It mostly refers to recommendation engines, used particularly in e-commerce.
When it comes to automated personalization there are three big names that need to be dropped: Amazon Netflix and YouTube, who are doing this at a very large scale with high levels of efficiency. However when looking at an Industry Report published by Amazon, one can see that even they acknowledge the hardships of automated personalization in the current day. Various methods that are either computationally expensive, or have scalability issues, possible fixes with the downside of lower quality recommendations and so on.
So for the time being automated personalization is not exactly within reach for many. That is with the exception of (big enough) e-commerce sites, where product recommendations have become the new standard.
Say you are a travel agency wanting to implement personalization on your website. What can you do?
The second example will be from the industry where personalization is implemented the most: Online Retail! Say you have a website selling clothes from different brands; for men, women, and kids. You could definitely use some personalization here, so you don’t end up showing summer dresses to a man shopping for sports gear.
Unfortunately, the answer is that there is no single answer. What you choose, what is best, depends heavily on your goals, resources (time, knowledge, money), and target audience.
However, there are a few indicators that can help you find an approach that is right for you.
First of all, ask yourself what you want to achieve with personalization. What are your goals? Then go through this checklist:
If your answers to these questions were mostly ‘yes’, you should opt for rules-based personalization.
Rules-based personalization is easier to start with as it’s easy to implement, it’s less costly and requires less data. Starting with this method, you can gain an idea of the possible benefits of personalization. This will also be a period of trial and error as you test different variations, while gaining a more indepth understanding of both — your visitors and customers as well as the value of personalization.
Later (if you have enough data and big enough pockets) you could implement automation on top of your existing personalization efforts. But while automated personalization has its benefits, it is probably not a good idea to make that your first step towards personalization. It requires heavy investment (time, effort, money, knowledge) right from the start. But don’t feel discouraged. Thanks to machine learning, automated personalization will become less costly and more accessible in the next years. Get a head start by learning the basics through rules-based personalization.
In short: With personalization, it’s better to test the waters first and dip your toe before jumping straight in.
Starting with rules-based personalization we are discovering more possibilities each day and regularly adding new rules to our tool. At Unless, we are also working on small automations but since we know about the importance of staying in control (something that current AI-based solutions often lack), everything can be adjusted by you.
With our automation efforts we mostly focus on personalization based on sentiment, language, and content, not so much on testing design. Leave usa comment if you have any questions.
A special thanks to Ecesu Erol for her input on this article.