Analytics and Search Marketing Tips
There is an undeniable feeling of accomplishment when working with the new Optimizely Personalization tool.
It’s exciting to know that the end result of our personalization efforts means that each individual’s customer journey through a website will be adapted to his or her exhibited interests. As a user progresses, more and more targeted, relevant information will be presented, exponentially increasing interactions.
This is the level of targeting that content creators and marketers have only dreamt about, and will love.
This empowers marketers to:
Now that we have covered the why, the rest of the article is intended to give you a high level tour of how Optimizely’s Personalization tool works and provide insight into the skills you will need to possess in order to fully unleash the power of this easy-to-use tool at a large organization. And if I can be so bold, I’m going to suggest that you’ll likely need a set of talented, cross-functional team members.
Here’s the 10,000-foot description for those unfamiliar with Optimizely’s new Personalization product. The tool enables you to:
Before we dive into more specifics on how Optimizely Personalization works, I want to mention there is no need for a massive development staff to make the in-depth experience changes to your site. The implementation requires the installation of a simple snippet, then we can access the Optimizely Personalization tool from a desktop, designing and testing new experiments with the click of a few buttons.
Let’s dive in with how to define an audience. One way to describe what an audience is, might be to imagine that your website could have “ah ha!” moments. Think of yourself observing the progression of a visitor’s journey. For example, at certain points during his visit, you recognize he has:
These user interactions give you insight into how to classify the visit. You can then define an audience as a group of visitors who perform a specific set of actions.
Continuing the example, let’s assume your site sells various ecommerce products, perhaps ranging from books, to music, to gadgets. As your visitor begins to surf and visit various pages, we start to get a feel for his areas of interest.
“Ah ha!” you might think. This visitor is looking at musical categories! In fact, we have detected that he searched for 80’s dance tunes, and has interacted with a review modal to read consumer reviews of a Skipworth & Turner album. This user’s visit might now categorize him into an audience I have defined based on a combination of page level, or even click-level criteria.
Now we can personalize our visitor’s journey.
While I’m not suggesting we change the corporate logo to a rotating disco ball of mirrors, certainly we can select suitable imagery, targeted calls to action and pinpointed content.
A simple example of personalization experience might be to recognize when a set of visitors have added items to their carts, but have not checked out. You could target this audience to receive custom banners, revised or additional page content with an alternate link to the checkout page, or even pop-up reminders if they haven’t started the checkout process yet.
Once we have come up with a set of audiences and we are tracking various behaviors of our visitors, we can design an experience that we think will improve the visitor’s experience. We will want to measure these experiences using key metrics such as visits to micro and macro conversion pages, and of course revenue if we are looking at the entire sales funnel.
When you’re ready to test your customized visitor experiences, Optimizely Personalization has a preview mode that launches your campaigns prior to publishing. You can use this mode to finalize the desired experience.
One helpful best practice we suggest is adding a condition to your audience definition that only your team knows about – such as a cookie setting. You could then publish the campaign, and only your team would see the changes without having to launch the preview. This approach might be useful when not all team members have access to the product.
After your campaign has been published and running for a few days, you can view results to see the overall improvement according to the metrics you defined. You’ll see:
At any point during a campaign, if you alter the experience or want to measure during a specific time period, you can reset the test results and let the campaign run its course.
Each experience is assigned to a percentage of your visitors who qualify, so when viewing results we are comparing against a holdback sample of visitors that did not get the custom treatment.
The concepts discussed so far might seem logical, but the hidden power in Optimizely Personalization is realized by integrating all the skill sets of your team. Here’s the list of team members you might need once you are ready to begin.
I am convinced the team at Optimizely recognized that not every organization has the bandwidth or skills to navigate this product. In anticipation of this, Optimizely introduced a Personalization Accelerate program to bring on qualified testing partners that can work with you side-by-side to design and launch personalization campaigns.
This means that the village of people required to execute your personalization initiative are ready to help you through the discovery, strategy, implementation, planning, production, testing, optimization, and reporting of your personalization campaigns. But if you’re anxious to jump in with your existing team, here is another great read on approaching content strategy for personalized websites.
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Paul is a Google Analytics Consultant at Blast Analytics & Marketing. He has spent 20+ years venturing into the depths of software development, designing and implementing analytic solutions to automate business processes within all sizes of financial services institutions.
Paul's experience spans software development, Business Intelligence design, eCommerce, database design, predictive modeling, and adaptive decision systems. Add Paul to your circles on Google+ Paul Lear has written 8 posts on the Web Analytics Blog.
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