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reebok cx circle
Customer Experience | Ecommerce | Apparel

How Reebok is challenging itself to become the most personalized sports brand in the world

Katie Leask
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June 8, 2021
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Read Time: 4min

adidas Group’s Marco Fazio and Charmaine Amsler (Senior Manager and Associated Manager of Conversion Optimization, respectively) spoke at our latest CX Circle event on the importance of leveraging AI and data science for eCommerce brands.

Having kickstarted the personalization and A/B testing program at Reebok around 18 months ago, Marco’s team now oversees all of Reebok’s conversion optimization activity on a global scale. 

“Personalization is not easy, and we’ve failed many times,” says Marco. But his advice at the start of the session was this: Don’t stop trying.

“With new technologies such as machine learning, and vendors like Kibo augmenting the capabilities that we have to segment and activate algorithms for our digital experiences, the rules of the game are changing,” he says. “And Reebok is on a mission to become the most personalized sports brand in the world.”

 

Right experience, right customer, right time

Charmaine joined Reebok a couple of months ago and works closely with Marco on personalization and testing efforts.

“With personalization, we’ve been able to see that when you have the right experience, targeted to the right customer, at the right time […], you’re able to have a strong impact on not only the engagement on your site but also your sales and revenue.”

So what has Reebok been focusing on over the last year?

  1. Doubling down on AI: “We’re a pretty small team but we’re also a global team,” says Charmaine. “So, for us, scaling and going quickly is very important.” That’s why they’ve been focusing a lot of attention on automatic insights, which allow them to scale effectively with minimal effort.
  2. Creating a 1:1 journey: Another key focus for Reebok has been making sure their customer journey is as consistent and relevant as possible across all touchpoints of their digital experience.
  3. Leveraging explicit and implicit consumer data: “Being able to tap into different data sources to feed into our machine learning algorithms has also been super crucial for us,” explains Charmaine.

So what do these three focus areas look like in practice? Charmaine talked us through three of Reebok’s key personalization experiments over the last year. Let’s take a look…

Three experience highlights | Reebok x Kibo

Experience 1: 

Homepage carousel using automated personalization with Kibo

reebok cx circle

The challenge: 

  • Reebok have several shopper segment datasets
  • Their homepage content doesn’t cater to all users
  • Segmented experiences are not scalable

“Whenever our consumers – whether a new or returning customer – land on the homepage, we want to make sure they see content that’s relevant to them; content that’s going to make them want to click, go to the different product listing pages, and really encourage that purchase straight from the homepage,” says Charmaine.

However, creating a different carousel for each segment simply wasn’t scalable. “So what we did is create five different variations of the homepage carousel (for classic shoes, premium shoppers, men training and running, women training and running, and kids). Then, we set up an Automated Personalization experience, provided by Kibo Personalization, which allowed the machine learning algorithm to allocate the most relevant homepage carousel to each individual visitor on the site.”

The results

  • 4.2% increase in revenue per session

“By sharing very relevant content upfront on the homepage, we were able to influence the entire journey which converted into a stronger revenue per session,” explains Charmaine.

 

Experience 2: 

Dynamic product page wireframes 

The challenge 

“At Reebok, we want to make sure we share as much information on the products as possible,” says Charmaine. So each product page is filled with:

  • Product reviews
  • Product recommendation carousels
  • Product description
  • Complete the look
  • How to style

“Our goal is to have users get to this page and have the information they need at the top of the page, instead of having to scroll.” And with each user at a different stage of their journey, Reebok tapped into automated personalization again to switch the components to show the most relevant content to the user depending on their buying stage.

reebok cx circle

Results

  • An increase in add-to-cart rate by as much as 5.5%

 

Experience 3:

Data science to power segmented personalization on the homepage 

“Here, we personalized the mini teasers on the homepage,” says Charmaine. “Similar to the carousel, we have mini teasers that showcase different products and different content to help drive the user to relevant pages on the site.”

The team created 13 different variations of mini teasers based on their shopping segments. For example, a returning female visitor interested in training and running was shown a personalized experience – one that showed products and categories more relevant to her needs, making her more likely to engage and click through.

reebok cx circle

The results

  • Increase in click-through-rate (CTR) by as much as 12.2%
  • Increase in revenue-per-visitor (RPV) by as much as 4.4%

Reebok’s key takeaways

“Not every single test is successful,” concludes Charmaine. “We had over 40 tests live last year and not all of them saw such strong results in terms of KPIs. But we recommend testing as much as possible. If you make a change on your site without testing it first, you might not know if that’s actually the right experience or the wrong experience for that specific consumer.”

Even though you might think your test is a failure, it’s a lesson learned that will help guide your strategy moving forward.

So here are the top three lessons that Reebok learned over the past year: 

  1. Having your own data to use as context makes tests more successful: “In order to create the most successful machine learning, it’s best to use data from as many sources as possible.” So use your own user data combined with third-party tools where you can; “This allows the machine to learn faster,” says Charmaine.
  2. Cross-functional and cross-channel collaboration is key: You want to make sure everyone knows what’s being tested at any time, plus what works and what doesn’t. “Sharing those learnings across your business and across teams is super valuable and will allow you to grow faster.” 
  3. Automated personalization helps scale and deliver a higher ROI: If you’re a smaller team that wants to grow, tapping into automated personalization strategies will make it easier for you than doing everything manually yourself. “You’ll have a much lower maintenance cost effort, too.”

 

Read the full case study

If you’re interested to learn more about how Reebok partnered with Kibo to leverage rich customer insights to deliver scalable personalization to its shoppers, read the full case study.

 

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Author

Katie Leask

Katie is Contentsquare’s Global Content Manager. With five years of content experience both agency and client-side, she knows a thing or two about creating content that drives traffic and converts. She enjoys reading, red wine, and going to bed early. She’s also pretty fond of rooftops and is rarely seen without freshly painted nails.