How Champion Improved All Key Metrics by Using Data Insights
YML partnered with Champion to evolve the iconic brand for a new generation. Fueled by product insights and strategy, the work exceeded every key metric.
Written by Michael Agombar
Many times, we see a client’s data collection methods to be lacking, in which case we create analytic tracking plans. These plans outline event names, triggers (when the event is fired), and any parameters associated with the event — like page names, item names, etc.
Luckily for us, our client, Champion, the iconic retail brand, had analytics that were incredibly strong. Every event was properly captured and the naming made it easy for our product team to jump in.
When we jump into analytics, we have a few goals. The first and foremost is to start generating insights. This is where we see individuals and organizations struggle to make the jump: from data collection to valuable data insights.
We first look for funnel analysis rates i.e., adding items to the cart, going all the way to the purchase, and from there we start generating hypotheses around why some steps within the funnel are failing. This process really goes hand-in-hand with what we like to call correlative event insights.
We like to look for a group of events that, when performed together, increase the likelihood of a user taking a high-value action. This, for the Champion example, was using the navigation. We found when people used the navigation, they were more likely to make a purchase.
However, data insights don’t get us all the way. Certainly this set us on the correct path, but unless we action on these insights to a valuable piece of strategy, and action that strategy to process and design, all is for naught.
How Insights Informed Strategy
Looking at both funnel analysis and correlative events, what we are really looking for is a way to generate ROI on improvements made within design and development that flexes on our insights.
Our brief by Champion was to:
- Increase average order value (AOV)
- Increase conversion rates (CVR)
- Reduce bounce rates
- Increase average revenue per user (ARPU)
So when generating a strategy, we look for insights that can flex and improve on these metrics,.
There are a few things we found while creating insights that would help us increase our three metrics above. For the sake of brevity, we won’t go super deep here. One, is that users who engage with the filter function on the site were 3x more likely to convert, and have a much higher AOV; and second is that sessions with higher page views per session are more likely to convert, again, with a much higher AOV.
With these types of insights, a few things happen here: we expand our KPI list to include things such as “Increase pages/session” and “Increase events/session”, but maybe most importantly, is our insights can now start taking the shape of hypothesis and opportunities.
At YML, we like to outline our insights into a three step process:
- Insight
- Hypothesis
- Opportunity
How Strategy Informed Process
This three step process really starts to outline our requirements that design takes and runs with. It should be noted that design requirements are much different than development requirements. As a Product person, I believe it’s my responsibility to give design guided requirements, but allow our world class design team to come up with the solution.
It is not the product managers responsibility to determine the solution, but it’s our responsibility to outline the insights, hypothesis, and opportunity around a certain set of features. We arm our design team with all this information, and work hand-in-hand with designers to ensure that our KPIs are being met within designs. This type of requirement is very different than more technical requirements/user stories we create for development, but that’s another story!
To bring us back to the process we followed on Champion, here is a little outline of how we used our insights to create requirements.
- Insight: Users with a higher page/session count than the average session are much more likely to purchase, and are more likely to have a higher order value than users with a lower page/session count.
- Hypothesis: Creating exploratory and discoverable experiences for the users will allow the users to ‘walk more virtual aisles’ and therefore increase the pages/sessions
- Opportunity: Introduce intelligent and pointed entryways to other product or category pages via the navigation, the homepage, product pages, and category pages.
Once we bring this outline to our design and client team, we can break the opportunity section into ‘firmer’ requirements such as “I want to be able to access another product page to a similar/related item when I am already on a product page”.
This process really gives the entire team the “why are we doing this” answer. It shows that our thinking is rooted in insights, is testable, and tied to a key metric we are trying to move. It allows everyone on the YML/client team to understand what we are trying to accomplish with every design and, most importantly, shows the path of thinking that got us to the designs we share/test.
Impact
Although there is certainly a lot more we could talk about through our process, the fact of the matter is converting data into insights, generating hypotheses based on these insights, and outlining opportunities to move on our hypotheses paid massive dividends for the product.
In order to determine the impact of YML designs, we looked at the past year’s data — with insights into variables such as marketing efforts, page traffic, etc. What we found was nothing short of spectacular.
- Increase average order value of about 17%
- Increase conversion rates by a whopping 3% (note this changed drastically when comparing year over year)
- Reduce bounce rates by 10%
- Increase average revenue per user (ARPU) by 15% (note this changed drastically when comparing year over year)
This success with Champion validates YML’s product management approach — that a product is never really ‘done’ once it’s released. The common thread among the most successful brands is they don’t treat their digital experience like a one-and-done product.
Leading digital-product companies grasp that their product is a constantly evolving experience, and they rely on meticulous product strategy, research and empathy to create both a valuable experience for customers, and ultimately value for the business too.
We have led experimentation and optimization tasks for a variety of clients that have seen continually-improving KPIs with relatively little investment. Continual optimization, experimentation and roadmap development ensures we are always delivering the best experience for users and the business.
About YML
YML is a technology and design agency, and Ad Age’s 2022 Customer Experience Agency of the Year. Headquartered in Silicon Valley, the team includes 500+ engineers, designers, and product strategists.
YML partners with enterprises ranging from The Home Depot, Kaiser Permanente and Albertsons to hyper-growth startups like Polestar and Thrive Market.
Special thanks to Tremis Skeete, Executive Editor at Product Coalition for the valuable input which contributed to the editing of this article.
