Between AI innovations and changing consumer behaviors, data will be king in 2024. Discover the vital role returns data will play in upcoming retail trends.
While trends and technological innovations can sometimes surprise us, staying on top of retail predictions is still essential for brands and retailers currently elbow-deep in strategy for 2024. The name of the game moving forward? AI-driven decisions, advanced algorithms, and machine learning—and returns data will play a huge role.
One could even argue that because returns is a lagging indicator, it provides the most holistic view of performance. Even when return rates are low, data from these transactions gives us a deeper understanding of consumer behavior, marketing, product performance, supply chains, and so much more.
This kind of granular data allows you to make more informed decisions regarding every aspect of business. Learn about the role of returns analytics in upcoming retail predictions, plus how incorporating returns data into your 2024 strategies can improve net revenue.
Returns Analytics Will Aid Data-Driven Personalized Shopping Journeys
Both retailers and customers benefit when the shopping journey is tailored to individuals. For shoppers, it becomes easier to find their ideal product amidst an abundance of choices. For retailers, this means higher conversion rates and higher customer lifetime value.
According to Think With Google, “People are 40% more likely to spend more than planned when they identify the shopping experience to be highly personalized.”
While this type of personalization may have seemed like a luxury in the past, the rise of AI will likely make these practices standard procedure moving forward. Retailers can harness AI’s advanced algorithms and large language models to analyze massive amounts of data, uncover valuable insights, and develop targeted strategies.
Amazon’s AI-powered recommendation engine is a good example of this. By analyzing vast amounts of data (browsing behavior, demographic information, purchase history, etc.), Amazon can recommend products that are tailored to individuals. This level of personalization boosts customer satisfaction, increases loyalty, and increases sales.
Modern consumers have come to expect personalized product recommendations, individualized offers, and even customized marketing messages. One survey published by Statista found that 62 percent of respondents “stated that a brand would lose their loyalty if it delivered a non-personalized experience. A year earlier, the share stood at 45 percent.”
What’s more, returns data provides valuable insights that can enhance personalized shopping strategies. In the past, retailers may have equated the “sale” with the “finish line” of the buyer's journey. Today, however, we know that post-purchase activity is just as vital.
After a purchase, shoppers may purchase again, leave reviews, or they may return an item for a variety of reasons. For example, while browsing behavior may indicate a shopper will purchase certain products, that doesn’t mean they won’t return them. Not only can returns analytics help us understand their product return reasons, but it can also provide insights that can optimize personalized shopping strategies.
Additionally, comparing returns analytics from behaviors like bracketing can reveal product recommendation opportunities. Imagine many shoppers bracket a garment in multiple colors while maintaining a high keep rate. In this instance, it may be advantageous to recommend an additional color to shoppers who have added a single variation to their cart.
That’s just the beginning. Returns data can help personalize loyalty programs, shopping journeys across different sales channels, and so much more.
Returns Analytics Will Improve Omnichannel Sales and Enhance Multi-Channel Insight
The state of multi-channel sales is evolving, and that’s a good thing. However, it’s difficult to fully grasp net revenue and marketing ROI from individual channels without taking returns data into account.
Customers want seamless, adaptive experiences regardless of whether they’re shopping on a brand's website, social media, or even in-store. And returns analytics can be used to improve experiences and sales across channels in several ways. For example, identifying channel-specific issues is vital for the consumer experience. Whether the issue lies in the product descriptions, returns abuse, images, or even sizing charts, returns analytics helps identify these kinds of channel-specific issues so product returns can be reduced and net profits across channels can grow.
Consumers have even begun using multiple channels at one time. Earlier this year, Shopify said, “50% percent of consumers say videos have helped them figure out what product or brand to buy, and 55% of consumers say they watch videos while shopping in-store.” Clearly, the buying process is more complex than ever before, and retailers need to use data to anticipate consumer needs.
Chris Cantino, of investment and consulting firm Color, told Shopify, “Companies who embrace multiple sales channels will pursue analytics that inform a more holistic view of customer journeys, which may transition from online to offline and back again.”
As multiple sales channels create a more dynamic buying journey with options like BORIS (buy online, return in-store) and BOPIS (buy online, pick up in-store), verifying which channels and touchpoints convert and lead to net revenue is essential. Top-line sales alone aren’t enough to determine whether a sales channel is successful. That’s why incorporating returns analytics is an important aspect of omnichannel sales and marketing strategies.
Consumer Insights from Returns Analytics Will Be Vital for Increased Social Sales
The merging of e-commerce and social media is here to stay. Between social networks offering in-app purchases, influencer marketing, shoppable posts, and in-app storefronts, it’s easier than ever for users to discover new products, new brands, and to make purchases without leaving the platform.
Insider Intelligence said, “Next year, US retail social commerce sales will total $82.82 billion, growing 23.5% YoY, per our forecast.”
The consumer insights from returns data will be particularly beneficial for social sales. It can help inform influencer marketing strategies by identifying individuals with both high and low customer return rates, it can help you understand the performance of certain SKUs or brands, and it can even be used to cross-reference returns data across channels to verify issues.
Open-ended feedback in the form of reviews and return comments is of particular importance in this instance. Analyzing customer feedback from returned social sales can reveal valuable qualitative insights that not only highlight specific issues but also create opportunities for loyalty. When shoppers know that retailers or brands will address their concerns, it creates a connection that can lead to brand advocacy and a greater lifetime value.
Harness Returns Data For Additional Revenue in 2024
The data from your product returns tells an important story about current and prospective customers, your products, marketing, and more. That’s why analyzing this data is so vital. You just need the right analytics tools.
The Returnalyze Intelligent Dashboard provides the detailed information necessary to understand and leverage customer behaviors, optimize product assortment, save on inventory management, and so much more. Essentially, the granular data you’ll gain access to will allow you to identify opportunities that may have otherwise gone unnoticed… and in 2024, you won’t have to do this alone.
A partnership with Returnalyze comes with step-by-step guidance from our expert data analysts. We’ll work with you to leverage returns data in order to identify issues, opportunities, and develop data-driven solutions that increase your net revenue.