Retailers are feeling the strain as they struggle to hold on to margins and keep service levels regular. Shoppers want quick, easy experiences, yet stores are coping with labour shortages, rising costs, and uneven stock levels. Findings from Zebra Technologies’ latest Global Shopper Study show how these pressures are pushing retailers to invest more in automation, real-time stock data, and generative AI to cut losses and keep operations moving.
Customer satisfaction has dropped again this 12 months, each online and in physical stores. People still care about speed and convenience, but they’re running out of patience when products aren’t available, when items are locked behind counters, or when checkout takes too long. Higher prices have also made shoppers more sensitive to discounts and deals. For senior retail leaders, these trends make it clear that long-standing store models aren’t maintaining with what customers now expect.
How retailers are attempting to turn technology into value
The study points to a shift toward more connected store operations. Many front line staff say they struggle to get the knowledge they need when speaking with customers. They also say higher tools would make their work less stressful and help them serve people faster. When staff can’t find answers or locate stock, sales slip away.
This is why many retailers are taking a look at technology that may deliver clear and measurable gains. Stock accuracy is high on that list. When stores know what they’ve on shelves and within the back room, they’ll avoid missed sales, plan replenishment more accurately, and make smarter fulfilment selections. A separate study by Zebra and Oxford Economics found that higher inventory processes were linked to up to a 1.8% lift in each revenue growth and profit.
A practical example is now taking shape in lots of stores. Instead of getting staff walk the aisles to check shelves, retailers are using tools like computer vision, RFID, or AI models to spot empty spaces, detect unusual patterns, and send tasks straight to the best employees.
The hurdles slowing adoption
Even with growing interest, retailers face well-known roadblocks. Many still don’t have a single, reliable view of inventory of their channels. When store systems, ecommerce platforms, and supply-chain tools don’t talk to one another, delays and errors creep in, and customers and staff feel the impact.
People and process issues also get in the best way. Staff who don’t receive training or consistent tools struggle to use recent systems. At the identical time, digital teams, supply-chain teams, and store operations don’t at all times agree on how data must be managed or which processes need redesigning. As the study shows, early pilots often stall when organisations haven’t committed enough effort to data quality, integration work, or cross-team alignment.
Still, most decision-makers agree that higher inventory insight and loss prevention can’t wait. Eighty-four percent of retail leaders say real-time inventory sync is now at the highest of their technology priorities. Many also expect to roll out computer vision, RFID, and generative AI in the subsequent five years.
Different regions, different pressures
The study also highlights how store challenges vary around the globe:
- In Asia-Pacific, 84 per cent of associates say AI will help them work more efficiently.
- In Europe, real-time inventory sync has turn out to be a stronger pressure point than pricing or promotions.
- In Latin America, more shoppers say they leave stores without every thing they planned to buy because items aren’t available.
- In North America, 80 per cent of associates say tracking out-of-stock items in real time continues to be hard to manage.
The gaps show that retail strategies need to be flexible. What works in a single region may not work in one other, especially when labour models, supply chains, and store formats differ.
What’s next for retailers
The findings suggest that the industry is shifting from small tests to broader changes in how stores run. Leaders are actually taking a look at automation and AI with a sharper concentrate on results – lower shrinkage, higher stock accuracy, and smoother customer journeys. To get there, they’ll need strong data foundations, clear training plans, and store teams who feel confident with recent tools.
If retailers can strike that balance, they might have the opportunity to construct stores that run more easily, adapt more easily, and meet the day-to-day expectations of shoppers who’ve more selections than ever.
See also: What enterprises can learn from NTT’s approach to customer insight
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