As a former soccer player, himself, my husband insisted that we get certain brands to equip our son with gear that would set him up for optimal success. In my husband’s mind, that meant buying PUMA soccer cleats.
So, just a couple of weeks ago, I purchased soccer cleats and a few other items directly from PUMA.com. As a marketer, I had a great experience on the site and thought it would be good to dig in and see what PUMA had done to create that experience for me - and to ensure I purchased directly from them instead of any other site.
The following case study incorporates my experience as a user, as well as background information about PUMA’s journey to optimized SEO with the help of Google Analytics.
About PUMA
As one of the world’s leading brands of sporting apparel, PUMA has established a following of fans comprised of both athletes and casual wearers. The company was founded in 1948 in Germany, but it can trace its roots back to the 1920s (PUMA, 2015).
The brand produces performance products for football, running, cross-training and fitness, and motorsports.Throughout several decades of design, development and sales of footwear, apparel and accessories, PUMA has maintained its commitment making products to support the fastest athletes on the planet. The company, still headquartered in Germany, distributes its products in more than 120 countries and employs more than 10,000 people worldwide (PUMA, 2015).
The Initial Situation
People choose PUMA not only because they’re good-looking, but also responsive, agile and fast. It was only natural that PUMA would want these same traits from its web analytics platform. The PUMA website, like many sites today, serves as not only a major sales and marketing tool, but also as an online storefront.
In 2012, the company wanted to optimize the performance of its website and online store. It set out to design and develop a new website, and based its strategy on SEO best practices and the functionalities of Google Analytics (Google Analytics, 2013).
Web Analytics Requirements:
- Compare the performance of each of its product categories independently
- Understand visitor behavior throughout their PUMA.com experience
- Increase sales in PUMA’s key target geographic areas around the world
(Google Analytics, 2013).
Solution: Getting Started with Google Analytics
To ensure PUMA’s new website and online storefront would attract, engage and convert as many customers as possible, the company partnered with Virginia-based digital agency and Certified Partner of Google Analytics, Viget Labs. This partnership introduced PUMA to Google Analytics and helped them incorporate it into the site plans and development process (Google Analytics, 2013).
Variable Testing
Once the beta version of the site was completed, PUMA did a soft launch with different variations of the site. Google Analytics’ custom variables was used segment visitors based on which test variation they saw. This effort generated valuable data, which PUMA used to compare how variables between the different versions of the site impacted conversion rates, events, click-rates and other important metrics (Google Analytics, 2013).
Customized, Segmented Visibility
One of PUMA’s goals in its web redevelopment project was to gain visibility of each of its product categories independently. To achieve this goal, the company used a combination of Google Analytics’ profiles and custom filters to create a view of all of PUMA.com as a whole, as well as separate views of each PUMA product category on the website (Google Analytics, 2013).
Events to Track Engagement
PUMA also used events in Google Analytics to measure visitor interactions with dynamic page elements.
Audience Segmentation
Because PUMA is a global company, selling to more than 120 countries, one of its major goals was to be able to see how its visitors from different corners of the globe interact with and behave on the site. To achieve this goal, PUMA used Advanced Segments to isolate visitors not only by geographic location, but also by any other demographic (or other) indicator tracked by Google Analytics (Google Analytics, 2013).
This tactic continues today, as users enter the site, they are shown the localized version of PUMA.com according to cookie data and Google’s understanding of where the users are located.
The Results
PUMA credits the data it has generated through Google Analytics - and, therefore, the improvements and iterations the company was able to make to its site - for the following impressive results:
- The amount of time visitors spend interacting with PUMA’s content, such as news, videos, and photos more than doubled.
- A 47% increase in traffic from growing regions such as China and India
- An 84% increase in conversions among mobile users
(Google Analytics, 2013).
The testing PUMA conducted as it launched its new website in 2012 paid off - big time. For example, it discovered that one variation of its header image performed far better than the other options. By committing to the top-performing variation, PUMA ended up increasing online orders by a little over 7%.
On the long-term, getting started with Google Analytics helped PUMA to develop a deep understanding of the importance of web analytics, as well as how to generate the data they needed and how to use it to generate more sales. As a result, people have a better experience and, are more likely to make a purchase. This is a win/win for PUMA its customers (Viget Labs, 2015).
Ongoing Impact & Opportunities for Improvement
Conversion Optimization
Years after PUMA began using Google Analytics, the site clearly has a focus on conversion opportunities. When a visitors arrive to the site, they are greeted with a pop-up box that requests that they subscribe to the PUMA email list.
What’s nice about this is that the brand not only requests your information, but also explains clearly what to expect from subscribing. You’ll get new product announcements, exclusive offers, news and event invitations. For a PUMA fan, this might easily be worth handing over an email address. This is a great and relatively simple way for PUMA to grow its mailing list.
Image: PUMA.com
One area for possible improvement would be implementing event-based calls-to-action and forms. For example, an offer to join the email list could appear in a small box in the lower right corner of the browser window either after the visitor has been on the site for a set amount of time, most often 2-5 seconds, or after the visitor scrolls a certain amount down the page, such as 25% or 50%.
Another opportunity for PUMA to retain its visitors and convert them into customers before they leave the website would be to implement a lightbox CTA that appears as visitors move their cursors off the screen.
Personalized Content
As PUMA collects data about its users, it would be wise to begin personalizing their experiences on the brand’s website. For example, as the company learns more about me, it could begin showing me products that are more and more relevant to me. Instead of showing me the standard home page, it could show me the latest outfits for women or sales on women’s shoes.
While the site is already providing country-specific versions of the website based on user location, PUMA could take it even further. User location data could also be used to market to them in even more personalized ways. For example, users in Arizona in January could see site content promoting PUMA’s products for mild winter weather, while users in Michigan could see PUMA’s best products for even the most extreme winter weather at the same time.
PUMA is a great example of a company trying hard to harness the power of SEO, conversion optimization and Google Analytics. It’s incredibly difficult to stay on top of the constant changes, but PUMA is doing a lot of things right. And that’s really all you can do, right? Try hard to stay at the forefront of technology and opportunity.
Resources
Google Analytics. (2013). “PUMA Kicks Up Order Rate 7% with Insights from Google Analytics and Viget”. GoogleUserContent.com. Retrieved from https://static.googleusercontent.com/media/www.google.com/en/us/analytics/customers/pdfs/puma.pdf
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