How to Use Personalization to Enhance Your Existing Optimization Program

We know an A/B test can lead to powerful insights. However, the information gained from traditional A/B tests tends to be focused on what’s best for the majority of users – not every individual user. That’s where personalization comes in. Personalization enables you to leverage the specific wants and needs of each individual user on […]

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We know an A/B test can lead to powerful insights. However, the information gained from traditional A/B tests tends to be focused on what’s best for the majority of users – not every individual user. That’s where personalization comes in.

Personalization enables you to leverage the specific wants and needs of each individual user on your site. This can lead to even more substantial results–higher conversion rates, deeper engagement with your site, and increased revenue.

Many of the traditional testing tools–Adobe Target, Optimizely and Maxymiser–have personalization capabilities available. There has also been an emergence of companies like Dynamic Yield and Evergage, which offer personalization technology as their core focus.

As technology in this space improves, personalization has become a major focus for many Brooks Bell clients. However, the question we’re often asked is not whether to implement personalization alongside existing optimization efforts – rather, its how to do this.

Luckily, there are many ways to do just that. For the purposes of this blog post, we’ve outlined two relatively simple strategies for implementing personalization alongside your existing optimization program.

Strategy 1: Rule-based targeting

Rule based targeting is a personalization technique that’s available on most A/B testing platforms. Instead of targeting all users, you select a specific segment of users to target an experience to: new or returning users; mobile or desktop users; or users in a specific location.

Because these different types of users are interacting with your site differently, you’ll likely see higher returns by personalizing your content to each group.

You can also apply rule-based targeting after running a traditional A/B test, by breaking down your results by those specific user segments. In doing so, you may find that a “winning” homepage experience performed very well among new users, but was flat for returning users.

Though pushing the winning variation live to all users would increase revenue, you might see a bigger increase if you were to push it live to new users only. This gives way to additional opportunities to test different strategies for returning visitors.

Strategy 2: Predictive personalization

Many testing platforms now offer predictive personalization, which works in real time to learn which experiences are ideal for certain types of users.

A predictive personalization “test” runs indefinitely – and adjusts as users’ preferences change over time, showing the optimal experience to each user.

Predictive targeting technology is exciting for many reasons. It accounts for the fact that a winner from a year ago might not be the best option for your users now.  

The technology also makes it easier to figure out the best option for short term website changes, like a holiday promotion–for which A/B testing is not a viable option due to time constraints.

Additionally, having the ability to step back and leave the analysis to the computer – instead of spending the time analyzing data yourself – is a huge benefit to experimentation professionals and the companies they work for.  

There are, of course, potential pitfalls to this form of personalization.

When you run a traditional A/B test with a clear winner across all users, it’s easy to make the decision to build the winning code into your site. However, with predictive personalization, you may have many different versions of a page for different segments of users, and continue relying on the testing tool to deliver the code, never building it into your site.

This can be risky for a few reasons: it can increase load time; and if, over time, other updates are made to your site, those updates could break the experience.

Additionally, you’ll also want to make sure you trust that the machine learning algorithms are actually making the best decisions for your users. To that end, many platforms offer a control experience which segments users randomly. You can then compare metrics from the control against the personalized segments to ensure the algorithm is working optimally.

Personalization offers the opportunity to gain new insights about your users and deliver the most valuable content for each individual. Incorporating personalization into your testing program is certainly worth the investment, with the potential for huge rewards.

At Brooks Bell, our Personalization Jumpstart program enables enterprise optimization teams to incorporate and scale personalization strategies into their existing optimization programs. To learn more about our services, contact us today.

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Walmart is the Latest Retailer to Offer a Personalized Online Shopping Experience

Big news for Walmart – and no, it doesn’t have anything to do with yodeling. Last week, the retail giant announced a major redesign of their website. The new Walmart.com, which is slated to roll out in early May, will feature a cleaner, more modern design, a new color palette, icons, fonts and many other […]

The post Walmart is the Latest Retailer to Offer a Personalized Online Shopping Experience appeared first on Brooks Bell.

Big news for Walmart – and no, it doesn’t have anything to do with yodeling.

Last week, the retail giant announced a major redesign of their website. The new Walmart.com, which is slated to roll out in early May, will feature a cleaner, more modern design, a new color palette, icons, fonts and many other visual changes.

However, the most significant change comes from within: Walmart’s new site will offer a more personalized shopping experience for its customers.

Personalization is the practice of optimizing your online experience based on a customer’s individual behaviors, needs, likes and dislikes. It requires applying behavioral psychology, statistical models and machine learning to thousands of data points. Thanks to new personalization technologies like Dynamic Yield and Evergage (among others), more and more enterprise companies are looking to personalization to increase conversions and drive a better brand experience.

For Walmart, the new site will recommend new, best selling or seasonal products based on the categories a customer has been buying or browsing. It’ll use geo-targeting to show items that are trending in a user’s location. Additionally, customers will be able to see what services or special promotions are available in their specific location.

In rolling out this new experience, Walmart joins the ranks of other online retailers using personalization to drive sales—among them Amazon.com, and niche players like Stitch Fix, Wayfair and Best Buy.

But personalization is not just for retail. In fact, for any enterprise company facing plateauing-results despite already optimizing their digital experiences, personalization can offer a means of winning more business by delivering a hyper-targeted customer experience.

At Brooks Bell, we’re helping enterprise-level companies (including Barnes and Noble, Chick-fil-A, Microsoft and more) improve the performance of their website, and deepen their understanding of their customers.

Our Personalization Jumpstart program enables our clients to build and scale their own personalization strategies, using a unique process that can be implemented in its entirety or a la carte. 

5 Steps to a Personalized Web Experience with Brooks Bell

  1. Align: Brooks Bell’s consultants evaluate the objectives of your users in the context of your company’s goals, success metrics, structure and existing technologies. Then, we develop customized growth plan with advice for execution and implementation.
  2. Discover: Our team of analysts reviews your data resources and identifies gaps in how you collect, store, merge and surface information. Then we develop statistical models, either in-house or by utilizing the tools and technologies you already have.
  3. Build: Personalized experiences built from statistical models only work if they target the right type of customer–and avoid the wrong ones. Once we identify your optimal users and their needs, we work to profile their attributes to gain a true understanding of the people behind your data, and build strategies based on those insights.
  4. Validate: At this stage, we bring in our full-service optimization team to ideate, build, launch, analyze your personalization experience. Our company is rooted in experimentation and our ability to validate our work— whether they are experiences, algorithms or a combination of both—is second to none.
  5. Launch: Finally, we work to scale your personalization efforts, measuring the impact of each test to confirm that as an experience changes, so does the desired outcome from that user interaction.  By doing so, we identify the most simplistic and manageable set of experiences that optimize your return on investment.

If you’re interested in learning more about Personalization Jumpstart or any other Brooks Bell service, contact us today.

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