Delivering a great buying experience makes all the difference in whether or not a user will convert to a customer. A core part of the eCommerce buying experience is creating an exceptional user journey from initial discovery to purchase. To learn more about accelerating the customer experience, we spoke to Nick Beighton, former CEO of ASOS, about his experience bringing a data-driven approach to online retail. 

Data Attribution as the Foundation for the Customer Experience 

For a brand to be successful, it needs to have agility in its business and technology to scale quickly to improve shopping experiences based on customer needs. At the core of agility for eCommerce companies, digitization is vital on both the front and back end. Nick explains,

“Digitization is really important on the front end, but it’s also important on the back end in terms of how you digitize your processes, how you use data to drive greater personalization, and how you make experiences more efficient, faster, and intuitive.” 

Nick explains that digitizing the front end encompasses creating intuitive and personalized experiences. As customers engage with the digital offer, the experience becomes more customized, from ads to product recommendations. Scaling operational processes on the back end centers on strong data discipline. A key part of this is maintaining a large catalog of product attributes, which encompasses everything from physical characteristics such as size, color, and material to brand and product descriptions.

“Digitizing the back end can only be done at scale through strong data attribution, strong control of your product master files, and the attributes within it. To attribute that data correctly, you can then turn your customer care from a cost center, to a profit center, by using the data to add on more sales and think differently about that interaction with the consumer.”

By starting with strong data attribution, eCommerce companies can better connect marketing and SEO investments to the entire customer experience.

Investing in Product Catalog Data at ASOS

Nick applied a data-focused approach to scaling ASOS by first focusing on the search journey on the ASOS website. A core area that the ASOS team investigated was the differing conversion rate between customers who used the search bar to find a product and customers who used the website navigation: customers who used the search bar had double the conversion rate. As a result, the team explored how to maximize the search journey. One discovery was how product attribute data impacts the customer search journey.

“We realized that the search journey didn’t have all the right data attributes to serve the most relevant search. So if you’re searching for men’s shoes, you might end up with women’s shoes too. We had to clean up the data on our main website to improve the search journey, and the recommendations served to the customers. That was one of the early ways we started investing in data attribution and product catalogs through the journey.”

Nick spearheaded an ML team that maximized product attribution data, and the investment proved successful. By improving product catalog data, conversion moved from 2% to over 7% on average and quadrupled the number of major SKUs added to the site. Nick explains,

“Data attributes and attribution of product information was critical to maintaining and improving that conversion while simultaneously adding more and more products.” 

Investing in product attributes proved instrumental at ASOS. The team connected robust product catalog data to maximize ROI and focus on conversion and customer experience. By building strong AI operational processes, the ASOS team optimized how they served customers. 

How eCommerce Companies Can Get Started with a Data-Driven Approach

How do eCommerce companies get started with having strong data discipline? What are some of the best ways to implement these practices across an organization? Nick explains the critical areas for teams to focus on are investing in data attribution early, experimentation, and establishing product goals:

1. Invest in data attribution: Strong product data attribution is at the core of improving the customer journey. ML teams can address long-tail product and content issues by investing in data attribution.  
2. Experiment to get started: Don’t limit experimentation with tech solutions that only have strong business cases and ROI. You may not know what experiment will give you an exponential return, so it’s essential to have multiple experiments and tests in parallel and review the data to understand the impact.
3. Align on product goals: Investing in product catalog data and tying the data attribution goals to product performance metrics is crucial to transforming the business. By working closely with product teams, teams working in eCommerce can provide a direct correlation with internal metrics. 

Nick emphasizes the importance of data discipline is all about creating the best end experience for the customer,

“A customer will rarely say, ‘I love your data attribution,’ right? She will say, ‘I feel the site gets me and gives me all the things I want when I’m searching for it.’ That’s the consumer mindset goal, and how to achieve it is through digitalization and data discipline.” 

At Scale, we believe investing in data is the key to unlocking success for eCommerce companies. If you’re interested in learning more about boosting your business’s conversion, speak to our team today.