Tech Tuesdays: The Emerging Trends to Know + Klarna’s New Platform
Here are the latest tech trends to know this week.
Technology Trends
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In a recently released Mastercard Signals report titled, “Emerging Technology Trends for 2024,” the company’s insights experts explored tech trends across artificial intelligence, computational power and data technologies that will be shaping the face of commerce in the next three to five years.
Particularly, the retail and footwear sectors are poised to experience significant transformations due to changes in how consumers shop and interact with brands as well as how businesses operate.
Ken Moore, chief innovation officer at Mastercard, views these emerging tech trends with a promising outlook for the retail industry and higher levels of engagement and connectivity between consumers and brands.
Businesses must adapt to new opportunities and technologies to remain relevant or risk being out of touch. However, Moore foresees the reality of how slow or limited adoption of new tech rollouts can be a challenge when underwhelming user experiences, interoperability within existing systems or bad timing could come into play.
The trend of AI-powered shopping assistants would streamline the process for consumers, help populate relevant products and speed up checkout. Last year, Mastercard company, Dynamic Yield, launched “Shopping Muse,” which combines conversational, colloquial text recognition to create smart, personalized recommendations to help shoppers on their journey from product searches to sales. Other companies engaging in this trend which will likely surface within the next year include Shopify, Instacart, Mercari, Carrefour and Walmart.
Other trends include mixed reality wearables as experiences that merge the physical and digital world where spatial computing comes into play, advances in smart network tech to power “smart cities” with connected experiences at major consumer destinations such as main street shopping or transport hubs and standards for “responsible companies” as consumers look to spend money with brands that align with their values and businesses who want to earn a share of their wallet through consumer trust and regulation compliance.
Challenging the Status Quo
In the fintech space, Klarna’s latest initiative is a website aimed “at setting new standards for transparency and responsibility in the credit and lending industry,” the company said, adding that the “Wikipink” site will challenge the status quo “by revealing comprehensive data on its services, including repayment rates, late fee rates and consumer age demographics, highlighting its commitment to fair and sustainable credit solutions.”
As the site launches, Klarna said it teamed up with The Harris Poll to get a read on how shoppers use credit cards while addressing misconceptions in the industry.
Klarna said as credit card debt hits new highs, interest rates on cards have soared to 36 percent. In its poll of consumers, Klarna found that 41 percent of U.S. shoppers who use credit cards “are revolving month-to-month, with approximately one-quarter of credit card users (23 percent) saying they have paid their credit card late and incurred a late fee or had a credit card payment go into debt collection over the last year.”
This compares to 31 percent of Klarna’s “Pay in 4” users who pay their bills early and just 4 percent who have been hit with late fees. “Klarna’s global default rate stands at less than 1 percent, significantly lower than the delinquency rates associated with credit cards, and 99 percent of payments are repaid,” the company said.
U.S. consumers who are saddled with massive credit card debt may not have themselves to blame. David Sykes, chief commercial officer at Klarna, said, “We still see too many of the traditional banks and credit card companies pushing products on consumers with exorbitant interest rates, hidden fees and revolving debt.”
“It is very clear that the traditional credit card model does not work in the favor of the vast majority of customers,” Sykes said. “Wikipink is not just a showcase of Klarna’s achievements, but a call to action for the entire financial industry to prioritize consumer well-being. By sharing our data and practices openly, we aim to inspire a shift toward more ethical, transparent and consumer-friendly credit options.”
Q&A with Logility
Roger Mayerson, senior vice president and industry principal of apparel and soft goods at AI supply chain planning software company Logility, sees this post-pandemic period as challenging for retailers and brands from an inventory management and forecasting perspective.
Mayerson said a shift in consumer purchasing behavior, new channels of distribution and changes in online shopping preferences make the old forecasting model obsolete. In today’s Tech Tuesdays column, Mayerson discusses these challenges and how AI-powered technology can make forecasting easier and more accurate while transforming the supply chain.
FN: From an inventory management and forecasting perspective, what are the challenges facing apparel retailers and brands?
Roger Mayerson: The biggest challenge by far has been the unreliability of historical sales to create a good representation of future sales. The traditional way of forecasting, by relying on the past two to five years’ worth of historical sales data to build a statistical forecast, doesn’t work in a market that is facing constant disruptions. Brands are finding that the sales data from 2020 to 2022 is producing low-quality forecasts and they need to find a better way to build their demand plans.
There has also been an increase in the number of products being managed in the portfolio and the number of channels being used.
This proliferation of complexity is stressing traditional inventory planning processes and tools. It’s not just the continuing shift to e-commerce, but also within e-commerce, there has been a change in buying behaviors. For example, for many consumers delivery date has become more important than price.
FN: How are new technologies such as AI, predictive AI and generative AI helping to transform traditional forecasting and inventory management?
R.M.: With AI first forecasting, the forecaster or demand planner needs to shift how they work. Understanding business trends, and customer shifts and explaining outlier data to the AI tools is more important now than being a statistical genius or data scientist.
Baseline results are more accurate and planner input or overrides can easily be measured to determine when to aid AI and when to step away.
Artificial intelligence is having a profound effect on the supply chain planning space right now. Leveraging the full spectrum of AI in an integrated platform is allowing brand owners to focus on forecast value added activities, take advantage of demand sensing and demand shaping opportunities, while simultaneously reducing their inventory levels without sacrificing customer satisfaction. It’s truly an exciting time to be in the supply chain space.
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