Retail's Quantum Leap: Tips for Retailers Grappling With the Accelerated Digital Shift
According to new data from IBM’s U.S. Retail Index, the e-commerce sector has been fast-tracked by five years due to the lifestyle-altering nature of the pandemic. Stay-at-home orders, store closures, and general pandemic-induced hesitancy from shoppers with regard to public places have shifted the balance towards digital shopping at the expense of the in-store experience.
In a survey of 1,000 U.S. consumers we conducted in August 2020, a quarter of respondents said that they were doing more than 90 percent of their shopping online, and less than 30 percent of shoppers said that they were comfortable going to stores. The impact of the pandemic on commerce has added another layer of pressure on the retail sector beyond what some would call the "Retailpocalypse," which had already been chipping away at brick-and-mortar in recent years, and it's unlikely that our newly ingrained shopping habits will revert back entirely after the pandemic passes. Retailers should view some of the current shifts as potentially permanent (at least to some degree), and plan accordingly.
Understanding an Evolving Online Audience
One key factor to consider is that e-commerce is gaining new audiences, including older generations of shoppers who may be less computer savvy and are joining the ranks out of necessity. Consumers aged 65-plus have been dubbed the fastest-growing audience segment in e-commerce, having spent a total of $1,615 online between January 2020 and October 2020, a 49 percent year-over-year increase, according to NPD Group’s Checkout Tracking. With unique challenges and opportunities growing, retailers must keep up on the latest techniques for better engagement with new and returning shoppers seeking in-store-like experiences online.
Qubit has been studying shopper behavior throughout the pandemic and comparing recent trends with prior years to identify how brands and consumers can best interact in today's digital shopping environment. Our data science team analyzed more than 3 billion shopper sessions across 1 million products from 100 retailers. We also interviewed over 300 e-commerce and merchandising professionals to find the most pressing digital merchandising challenges today. Through the analysis, we gleaned several interesting takeaways to help retailers guide their e-commerce personalization strategies in 2021, year two of the global pandemic.
The insights below are designed to help retailers recalibrate their long-term digital experiences in the new retail landscape, including how to manage shoppers' shrinking attention spans, prioritize limited screen real estate despite an overabundance of inventory, and properly leverage product recommendations to power the shopping journey.
Prioritizing Thousands of SKUs on the Digital Storefront
In the study, we analyzed data from 100 medium to large retailers, ranging from general merchandisers to brands in the fashion, beauty, and luxury sectors. On average, these retailers had 13,000 products to manage online. It's almost hard to fathom the volume of data from views, pricing, purchases, inventory, sell-thru, returns, and so much more, that this many products generates on a continuous basis. It’s imperative to prioritize products to drive optimal results, but how? Most of the e-commerce teams we interviewed looked for opportunities in their catalog in four main ways:
- spotting top-performing products by revenue;
- identifying high-traffic, high-conversion products;
- troubleshooting high-traffic, low-conversion products; and
- looking for opportunities in low-traffic, high-conversion products.
But as our focus groups concluded, these ways of narrowing focus don't always show the full picture of customer behavior. As a result, opportunities may be left on the table. Consumers may only click through one or two pages on the retailer's site before moving on, a finding also confirmed by our research.
Hero Products Are Relevant to Only 16% of Visitors
Another direction that some e-commerce teams may choose is to focus almost exclusively on the core products that their brand is known for, or "hero products." However, our research found that despite being aggressively promoted by retailers, hero products are not relevant to a large majority of shoppers landing on an e-commerce site. In fact, only 16 percent of shoppers are actually in the market for hero products. Furthermore, 70 percent of revenue actually comes from long-tail products that are not actively merchandised. Qubit estimates that if customer preference was taken into account, homepage relevance would jump more than three-fold — from 16 percent up to 42 percent.
Seemingly, long-tail products should remain a priority for retailers today, as they adjust to the longer-term digital shift and make decisions about what products to lead with. The question is: How do e-commerce teams use this takeaway to address the initial challenge of having too many products to monitor?
Not All Product Recommendations Engines Are Equally Effective
The good news is that automation tools continue to advance to support e-commerce. We just have to keep track of the latest and greatest tools. For example, product recommendations have been around for years. Historically, product recommendation engines have been designed to identify correlations between shoppers and products. As a result, most shoppers are shown similar product options that don't factor in their individual preferences. However, more recently, advanced product recommendation engines have emerged. These newer engines, such as Google Recommendations AI, explore customer-to-product relationships, powered by sequential deep learning. This more advanced recommendations method can better scale on retail sites and offer visitors the most relevant product selection during the moments when this matters most.
For retailers, ensuring that they leverage more sophisticated product recommendations engines can result in a significant edge over the competition and a way to automatically prioritize the catalog to connect shoppers with those long-tail products that had not been selected to be actively merchandised. Automation tools and artificial intelligence can also offer e-commerce professionals feedback loops that enable them to look at how their products are doing, as well as a path to scale and prioritize all the product and customer data and leverage it to dynamically serve the right products to the right visitors.
The shift to digital is a change that was predicted by many industry experts, but not at a moment's notice, a la an episode of the popular late '80s TV show, "Quantum Leap." While the transition was undoubtedly rough, it's important to think about what this jump ahead means in terms of keeping up with the technology tools and automation options in planning for 2021 and beyond. Retailers that are tech-savvy and value digital-first strategies are bound to lead the charge in the newly recalibrated shopping era.
Tracey Ryan O'Connor is the chief revenue officer at Qubit, an online resource that seeks to power the next generation of product recommendations, badging and insights to build exceptional customer experiences.
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As the chief revenue officer at Qubit, Tracey Ryan O’Connor leads all commercial parts of the business, including global sales, marketing and customer teams. O'Connor previously served as Qubit's VP of North America and Global Head of Sales, where she was responsible for managing the U.S. business development team and overseeing Qubit’s strategic accounts in the company's growing fashion, beauty and retail brand portfolio. Prior to joining Qubit, O’Connor held sales and marketing positions at Reflektion, Neustar and Oracle.