Hello everyone, my name is Shuvo Habib and I welcome you to my article on web optimization using one of the most popular A/B testing tools called Adobe Target. Adobe Target is designed to make testing and adopting a culture of optimization straightforward and scalable. If you get familiar with any of the A/B testing tools, you’ll be comfortable to work with other A/B testing tools too. Most of the A/B testing tools like VWO, Optimizely, Monetate, and Adobe Target share a plethora of common features.
What is A/B testing ?
Before diving deep into Adobe Target implementation, let me ask you, are you sure what’s A/B testing? Don’t worry, I’m here to explain.
A/B testing (sometimes called split testing) is comparing two versions of a web page to see which one performs better. This is a fantastic method for figuring out the best online promotional and marketing strategies for your business. You compare two web pages by showing the two variants (let’s call them A and B) to similar visitors at the same time. The one that gives a better conversion rate, wins!
If ‘A’ is the control version, I mean the version that’s the current website’s page, we create version ‘B’ or maybe more at Adobe target aka A/B testing tools.
Deep dive into Adobe Target
Some of the major topics I’d love to cover in my article series is conversion optimization, start to finish creation of A/B testing, experience targeting, designing activities/coding activities in the visual experience composer and the form-based experience composer. After completing this article series, you’ll be able to better understand what testing and targeting are, be comfortable navigating through Target’s interface,
Adobe Experience Cloud
The Adobe Experience Cloud is an integrated set of solutions to help marketers differentiate their brands and engage their customers. End goal is to engage more customers and generate more revenues. It includes Adobe Experience Manager, Adobe Target, Adobe Campaign, Adobe Social, and Adobe Primetime, helping brands manage, personalize, campaigns and customer journeys. Amongst them, today, we’ll be discussing Adobe Target. For that, we need to select Target from Marketing cloud and move forward.
How Adobe Target works
Each time a visitor requests a Target-enabled page, a first-party cookie is set in the customer’s browser to set a unique visitor ID, afterward the page makes a call to Target either via the target.js file or an mbox on your page. Then it calculates response and content is displayed based on the rules of your activity or campaign. As traffic increases, the percentages should become more equal.
Enough Basics! Let’s jump, how it’s all done in Adobe Target.
Let’s launch, Target from here to get the list of experiments/activities already created or create, modify new activity. You can see list of your previously created activities, if any.
Creating Activity is straight forward. Just clicking the button in the right “Create Activity” takes you there. As we’re building A/B test, we’ll select A/B test. There is two way of building your activity, either using the Visual Experience Composer or the Form-based Experience Composer.
Through Visual Experience composer, variation can be build both visually (Direct editing in the panel or Drag n Drop)and by coding (HTML, CSS, JS and/or jQuery). If you select Form, then the only option open for you will be building the variation by coding.
For this tutorial, I’ll be writing about Visual Experience composer and in the next one of this series I’ll be writing about Form based Experience Composer.
Well. let’s select the “Visual Experience composer”. We need to enter the activity url, which is where we’d like to do A/B test. Click next in the top for next step. As we build our activity creation the workflow will walk you through the following steps. Create, Target and Goal and Settings.
Yo! We’re very close to the point of creating the experiment.By clicking on the “Untitled Activity” you can rename the activity. Meanwhile, you can see your website is ready to be editable. Using Visual Editor you can click on the element and change the contents, color, background, font size and do a lot of things.
I prefer creating A/B test by coding. By using Visual Editor, you don’t have the full control. Coding does give you that. You can do everything that is possible by writing HTML, CSS and JS. If your website has jQuery library installed, you can use that too. You can make API call by using ajax method and go more further. When you work for Client/Optimization Manager/UX Researcher, they have different and mostly complex idea, which can only be implemented by implementing custom Coding.
How to insert code in Adobe Target?
You can code in your preferred code editor or directly code in Adobe Target’s integrated code editor. By clicking on the top bar that’s saying “Modifications” opens the default code editor in the right. The default editor looks like below,
Like the example given, you need to select “Custom Code” and write down all your code on the editor. Make sure, you wrap all your code within a script tag.
<script>console.log(‘Variation 1 is running’)</script>
Let’s jump on the settings tab. Settings consists of Page Delivery, Properties, Audience and other thing. You can access all these just by clicking on the setting icon.
All the names are doing exactly what the names are referring to. These are pretty straight forward. Page delivery and Audience are the most important part here. Let me shed some light on it.
By clicking on the page delivery, you’ll get options of adding url conditions. These url conditions let Adobe Target know in which urls the A/B testing Experiment is going to run.
Audience, is your Targeting Audience. You can target Audience for your experiment based on user’s location, device, browser etc.
I’ll cover audiences in greater detail in later articles. Users may manually set the traffic split percentages across all experiences or they may choose to allow Target to automatically allocate traffic using a methodology whose objective is to maximize conversion. To clarify, you never have to include all traffic, meaning 100% in any test you run. If you’re running huge changes on your site a very smart practice is to start this number low like 10% and watch how users interact. Then start increasing based on the reports we’ll be discussing next.
Goal & Settings
Goals also known as metrics are the primary reason, why we’re doing the experiment. In other words, goals will tell us which version of the test has more potential or generating more revenue.
You need to add metric from this page. Below the activity settings in the Reporting Settings section specify the source of success metric data by selecting either Adobe Target or Adobe Analytics if available as a reporting source, then define the goal of your activity. I’ll cover goals in more detail in later articles. For now, just play around the Adobe Target Goal setting, you will learn a lot.
After setting and configuring the goals, you need to save the changes. You can’t just make the Experiment live to all users just doing the setup and coding things. You must QA all the changes that includes, Code QA, Tool Setup QA, and UI QA. For these QA “Activity QA” is very handy. By clicking on it, you’ll get a generated url created by Adobe Target for viewing both the variation and control on your browser, where you can check very functionality is working fine or not. Even you can check whether the Goals are firing perfectly or not.
Activating Your Experiment
After you’ve completed the configuration of your activity and performed the necessary QA, we need to activate it in order for visitors to view the experiences live on your site.
As we’ve activated our experiment, we’ll be starting getting our reports, of our experiment from real user visiting our website based on the audience and traffic allocation we’ve set.
It’d be premature to draw any conclusions just after five minutes, five hours or even five days. So, when exactly is it safe to declare a winner in a test? In the online world the possibilities for testing just about anything are immense. And many experiments are done indeed, the result of which are interpreted following the rules of null-hypothesis testing, “are the results statistically significant?”.
The analyst says: split run (A/B test) with 5,000 observations each and a one-sided test with a reliability of .95. Out of habit.
We’ve now come to the end of this course, diving into Adobe Target. To wrap up, we’ve gone over the basics of conversion optimization that will better fuel your understanding in approaching Adobe Target and its many capabilities.
Still have questions, about Adobe Target ??
Ask me anything in the comment, I’d be very much happy to answer all your queries.