Consumers today are increasingly on the hunt for discounts and deals, seeking out less-expensive items and reigning in their disposable cash as high inflation rates persist.
Add to that the rapidly shifting shopping trends (thanks to influencers and social media), and fashion retailers are presented with a unique challenge: what’s the most effective strategy for capturing and retaining cost-conscious shoppers who are more selective than ever about where and how they spend their money?
For online fashion retailers to thrive in this demanding climate, they need to begin by meeting budget-conscious shoppers where they’re currently at. The best place for merchandisers to start is by taking a look at the current shopping experience on their site.
Are customers experiencing constant friction at checkout, leading to a high bounce rate? How relevant are the recommendation pods and product categories? What does your data say?
Let’s explore how smart product discovery tactics can not only attract and retain today’s budget-savvy consumers, but ultimately increase critical business KPIs.
Today's budget-savvy consumers demand more. They seek genuine value, personalized experiences, and seamless shopping journeys that cater to their financial constraints. Placing recommendation pods at key points in your customer’s journey not only transforms their experience to a personalized adventure, but it also creates cross-sell and upsell opportunities to increase average order value (AOV).
It’s also incredibly convenient for customers, particularly those who are working within a set budget. In fact, over 75% of consumers say they have purchased more than intended because of the convenience factor. They came for the navy socks on sale but left with a matching blue sweatsuit, too.
By presenting relevant suggestions at the right moments — whether it’s capturing initial interest on the homepage, enhancing the browsing experience on product pages, preventing abandonment at checkout, or encouraging repeat business post-purchase — you can significantly boost engagement and conversions. Thoughtful and well-placed recommendations not only help shoppers find what they need but also introduce them to new products, enhancing their overall satisfaction and loyalty to your brand.
This strategically placed recommendation pod on Birkenstock’s homepage presents products that could be attractive for the consumer, based on previous browsing history.
Even when on a budget, consumers want to feel understood by brands. As part of a hyper-personalized product discovery experience, one way to do this is by presenting highly curated Collections, or personalized landing pages.
Traditionally, this has been a time-consuming, difficult task for ecommerce teams to handle. It might require the merchandiser to manually curate a selection of products, requiring a deep understanding of their catalog.
But thanks to a new AI feature in Constructor known as AI-Generated Collections, the heavy lifting is done.
All merchandisers have to do is enter their Collections dashboard and describe the types of product, occasions, or styles they want shown on the landing page. This can be as simple as prompting “summer dresses under $30." Then, AI will generate items based on the prompt. Merchandisers can edit the AI-generated list as they see fit before pushing it live. Once live on-site, Constructor personalizes the products according to user-level attractiveness.
This feature of Collections has many benefits for merchandisers, including:
But most importantly, it allows merchandisers to provide a 1:1 customer experience site-wide and at scale — even for the most budget-conscious crowd.
Yesterday, beauty influencers were touting a luxurious, magical mist sold in a recyclable canister. Today, it’s been deemed about as good as a bottle of mineral water –– no longer special enough to be at the top of a bestseller page. Instead, the hype is all around a less costly dupe sold at drugstores.
Merchandisers have to ask themselves an important question: how quickly can their ecommerce experience and platform adapt to the constant rise and fall of demand? This process happens faster than most can blink. What was once a steady sell-out product might be today’s social-busted trend.
Trend forecasting will always be tricky, and sometimes the terminology that shoppers use when searching your site can make it even more complicated. Pair these factors with consumers on a tight budget, and you have the makings of a difficult time providing a top-tier product discovery experience.
But you don’t have to call it quits, especially if you rely on the right ecommerce tech stack.
For instance, when the TikTok “Lumber Jane” trend popularized baggy fleece pants and the like, a major fashion retailer recognized these searches on their site were serving no results, despite having the exact pants.
Using Attribute Enrichment, the fashion brand was able to enrich product data at the speed of social media. The GenAI-based tool picked up on search and shopping trends and auto-populated “LumberJane” as a searchable product attribute on relevant clothing items like the baggy fleece pants.
Shopping assistants powered by AI can provide instant support to shoppers, answering questions about products, prices, and availability. These tools can also guide shoppers to the best options that fit their complex needs.
For budget-conscious shoppers, quick and accurate information can be a deciding factor in making a purchase.
Let’s say a shopper heading to a summer wedding in a humid climate needs help finding the perfect attire to impress and endure. They ask, “What can I wear to a wedding in the summer heat?” The ASA recommendations are easy to navigate, make sense contextually, are personalized, and span various in-stock products and categories (dresses, shoes, hats, etc.) to promote bundling, and ultimately, increase AOV.
AI Shopping Assistant (ASA) can act as a style assistant, suggesting and showing items aligned to a shopper’s needs, tastes, and intent.
When this Gen-AI powered solution is paired with a holistic suite of AI-native product discovery tools, there’s no limit to what can be achieved — both for your customer experience and your bottom line.
A sure-fire way to keep even the most budget-tight customers satisfied and coming back for more? Make it all about them. In fact, over 70% of shoppers expect personalization from a shopping experience.
Recommend personalized products that align with the shoppers’ preferences and budget by implementing AI-native algorithms to analyze browsing history, past purchases, and search behavior. This online data can be synced with offline data to inform the omnichannel customer journey, ensuring that you provide an on-brand, customer-centric experience across web, app, and in-store.
For example, if a user frequently browses for discounted or clearance items, merchandisers can configure their site to prioritize showing budget-friendly options and ongoing sales. These product suggestions can appear across recommendation pods, landing pages, category pages, and other key areas of the site, as well as be integrated into email recommendations.
Dynamic content that adapts to the user’s profile makes the shopping experience more engaging. Personalized banners, targeted promotions, and relevant product suggestions ensure that customers see the most pertinent information as soon as they land on the site. This reduces the time spent searching for deals and increases satisfaction and customer loyalty.
Capturing and retaining the attention of low-budget shoppers is an art that transcends economic fluctuations. These savvy consumers are always on the hunt for great deals and value-packed products, making it imperative for online retailers to swiftly adapt to their needs.
Whether the economy is booming or facing a downturn, the ability to cater to cost-conscious shoppers can significantly boost your brand's appeal and loyalty. When armed with the right technology, merchandisers can turn financial challenges into opportunities, and ensure their brand thrives amidst economic uncertainty.