According to Statistica, fashion e-commerce revenue accounted for $110.6 billion in sales in 2020. This despite a 15–20% decline in revenue predicted by McKinsey on account of the pandemic. Coming out of 2021, the growth trend in e-commerce fashion sales is predicted to accelerate, exceeding $150 billion by 2024.
These statistics indicate an increasingly competitive digital space with brands vying for the attention of customers. It highlights the need to find ways to better connect with visitors from the moment they land on a website or mobile app and continue to nurture that relationship through the entire customer journey, and even beyond the initial transaction. Achieving this requires an understanding of what’s important to customers as well as what experiences website visitors are responding to positively or negatively.
The #1 trend influencing fashion CX
A renewed awareness of sustainable fashion is shaping consumer behaviors in significant ways. It’s creating new market segments, influencing supply chains, and holding brands accountable for their societal and environmental impacts. To put this in perspective, it is estimated that 11 million tons of clothing ends up in American landfills each year. As customers are made aware of these and other environmental and social impacts of the fashion industry, it is changing how they shop, what they shop for, and what they expect from the clothing brands they want to associate with.
Some interesting statistics from Levi Strauss (who embarked on a 2017 project to reduce water used in production) indicate that a single pair of Levi jeans uses almost 3,800 liters of water in its life cycle. This includes production, packaging, and washing by the customer. It may not seem important until you learn that Levi Strauss annual sales netted more than $5.7 billion in 2019, dropping to $4.45 billion in 2020. Consider how many $40 pairs of jeans contribute to those sales figures and the impact becomes significant.
As more customers start to realize that they’re the ones contributing to this environmental impact through continual demand for new fashion items, it’s driving a second trend: thrift store shopping, second hand clothing trading, as well as rental which have grown exponentially as customers choose to embrace circular economy principles. This involves actively reusing materials that already exist rather than buying newly made products that have a greater environmental impact. A significant percentage of this market sector operates online and this has only increased as a result of the pandemic. Big clothing brands are even creating nostalgic themed apparel inspired by earlier designs to compete with this rapidly growing sector.
Digital experiences that deliver
Given how much sustainability is a growing influence in the fashion industry, brands need to consider how to connect with customers on these issues in an authentic way. The online shopping experience generates many opportunities to do this throughout the customer journey. This translates to an opportunity to not only introduce visitors to practices that may connect with their own values but also reinforce their decision to do business with the brand. The challenge for brands is trying to identify what information to highlight and at what point in the customer journey. How to display different elements and understanding which have the most impact on progression through the funnel and ultimate sale.
Traditional A/B testing tools struggle to deliver the results needed to consistently improve CX in a way that makes a real business impact. Especially as tests can’t be interrupted or changed midway even if new data or ideas become available. This can be frustrating for an industry such as fashion where customers can be quick to change their preferences and needs. When this is the case, A/B testing tools often show results that are inconclusive or deliver insights after the window to make changes has passed.
By contrast, the ability to experiment with tens of variables in thousands of combinations and generate valuable insights quickly can give fashion brands a distinct competitive advantage in the e-commerce space. This is what AI-driven experience optimization is all about. Finding out which experiences visitors are responding to and what elements though the entire journey and on specific pages are contributing to that uplift. The ability to drill down beyond what’s making the most impact to why it’s having an impact and by how much, gives brands more valuable insights on which to pivot strategies that will deliver on goals.
Experience optimization use cases for fashion
For most fashion retailers the primary goal for their e-commerce website is to drive sales. Most often the primary metric being optimized is conversion rates, followed by secondary metrics such as the average order value (AOV) and add-to-cart rates. While the whole customer journey is critical, the starting points are usually the product listing page (PLP), the product detail page (PDP), and checkout page as these have the potential to have the most direct impact on lift. Here are a few case studies of AI-driven experience optimization in action:
CASE STUDY 1
Primary goal: Increase add-to-cart rate
An outdoor apparel company sought to increase sales by focusing on the add-to-cart rate. The two pages optimized were the product listing page (PLP) and the product detail page (PDP). The optimization served more than 140,000 website visitor experiences based on 2,048 possible combinations. This resulted in an 8.1% increase in add-to-cart during the optimization with the top performing combination producing an impressive 14.9% increase. This was accomplished by identifying the hurdles to conversion within upper funnel pages, increasing the prominence of CTAs and path to funnel progression, and by developing a set of ideas to increase conversion across upper and mid funnel steps.
CASE STUDY 2
Primary goal: Increase revenue from each transaction
A children’s clothing brand sought to generate growth by prioritizing conversions on it’s e-commerce website. The optimization was focussed on the product description page (PDP). 432,068 website visitors were served experiences made up of 40 variables in 1,728 different combinations. This achieved a conversion rate which generated $92,000 in additional sales within a 65-day period. The total value of the top performer uplift was estimated at $6.5 million. The optimization experimented with many elements in the journey including where to show promotional features and focusing on upsell and cross-sell options which drove incremental sales.
CASE STUDY 3
Primary goal: Sales
An e-commerce clothing retailer wanted to drive sales and focused optimization efforts on the product detail page (PDP). Some of the winning changes included moving the product and brand name above the product image, as well as including shipping information in the pricing section and including a product color and size chart just below the product image. These may seem like relatively small changes but they resulted in a revenue impact of $15,300 in just the first 30 days of optimization. During the optimization a total of 32,400 combinations were served to 2.4 million visitors. The top performer impact is estimated at an additional $750,000 in additional sales per month.
These three examples highlight the value that AI-driven experience optimization can bring to the online fashion industry. In a highly competitive market, the ability to improve customer experiences through continual experimentation and personalization, is what will give brands a distinct competitive advantage.
