Sole searching: how footwear brands can use data and AI to stay one step ahead
Fashion trends are coming and going at an increasingly rapid pace —and this is most apparent when it comes to footwear. From chunky loafers to high-heeled sneakers to mesh flats, the “in” shoe is ever-changing. Thanks in part to TikTok, fast-paced micro-trend cycles keep brands and shoppers alike on their toes. It’s never been more critical for footwear brands to remain one step ahead.
Brands across the retail industry face an ever more challenging marketing landscape. Consumers do not follow a linear path to purchase, making it tricky to reach shoppers where they are. And the convenience of shopping from online marketplaces often outweighs the practicality of buying certain items—like shoes—in-store.
To stay competitive and deliver exceptional experiences at every customer touchpoint, footwear brands must up their digital marketing, taking a more sophisticated approach that leverages data and AI.
Enhanced customer journey mapping for personalisation
The non-linear purchase funnel in the footwear industry requires brands to provide a seamless customer experience across multiple touchpoints, pre- and post-purchase. By analyzing customer data, brands can understand the various touchpoints where customers interact with their brand, such as social media, website visits, or email campaigns. With generative AI-powered dashboards and reporting, you can analyze browsing behaviour, purchase history, and preferences, and segment your audience to deliver tailored messages.
This information allows you to build highly personalised marketing campaigns, with timely creative and messaging that resonates with your target audience, at the right stage of the customer journey.
Take a running shoe brand, for example. Using AI to identify customers who have recently purchased running gear, the brand could target them with personalised recommendations for complementary products like socks or fitness trackers. This level of personalisation makes shoppers feel seen, enhancing their experience, increasing engagement, and building loyalty.
Predictive analytics for reducing returns
When it comes to shoes, a (near) perfect fit is nearly always essential to shoppers, and can be difficult to determine through a screen. So, unsurprisingly, returns pose a significant challenge for footwear brands. According to June 2024 data, at 16%, shoes are the second-most returned category of e-commerce purchases, creating a double-sided dilemma for both revenue and customer satisfaction.
While charging for returns is an option to discourage (albeit one that likely won’t win favor with customers), a better solution is to get in front of returns altogether. The challenge is understanding which valuable products to advertise first to customers, and to advertise products that boost margin and decrease returns, but not at the cost of revenue. AI poses a solution.
Using predictive analytics, you can identify customers who are more likely to return their purchases and why. For instance, analysing historical data on returns allows you to identify patterns and factors that contribute to returns, such as sizing issues or product descriptions. And by centralising data from various sources, such as sales, stock, margin, and returns, you can use AI to calculate data-driven scores for each product. These scores can be used to help prioritise advertising efforts, ensuring that marketing budgets are allocated to products that drive revenue while minimising returns.
These insights can be used to optimise products and their digital presentation, tailor your marketing efforts to promote products that have a lower return rate and target shoppers with the greatest potential lifetime value.
Optimized media spend allocation
Finally, by building a media measurement dashboard that integrates the data from across your campaigns, you can gain a holistic view of your overall marketing performance. This is critical to be able to optimise media spend and allocate budgets to the most effective channels and campaigns.
Generative AI-powered dashboards take data analysis to the next level by providing real-time insights and actionable recommendations. These dashboards can process vast amounts of data and generate meaningful insights that help you make informed decisions. They can identify trends, patterns, and correlations in customer data, allowing you to adjust your campaigns in real time to maximise performance.
These shoes rule
As footwear styles go from hot to not faster than you can lace up a knee-high boot, customers still remain relatively loyal to brands. Fit, fashion, and brand trust are top drivers for consumers, and many aren’t interested in opting for dupes.
What will turn shoe shoppers away? A poor buying experience, lacking the right size in stock, and price—all factors that can be mitigated by having a solid data and AI foundation in place. By effectively integrating and using these tools in your media and marketing approach, you can create personalised marketing campaigns and customer communications, implement dynamic pricing strategies to capture in-market shoppers and deliver a seamless multichannel customer experience that won’t end in a return.