Digital Transformation in the Retail Industry in 2025

Digital transformation in the retail industry is the process of integrating new technologies into its core business processes to streamline operations and improve the customer experience. With emerging technologies like AI and big data, digital transformation is realigning the DNA of retail organizations to help them stay relevant in a high-velocity, tech-driven market.

In 2025, e-commerce accounts for 23% of all U.S. retail sales, growing at twice the rate of traditional retail. However, the retail revolution isn’t just playing out in shopping carts and click-throughs. It’s unfolding in how enterprise retailers—like Nike, IKEA, and Target—are reengineering pricing models to be algorithmically optimized, responsive in real time, and seamlessly connected across digital and physical channels.

Retail leaders are under increasing pressure to deliver ROI from digital initiatives: According to PwC, 30% of global CEOs have already seen revenue gains from new technologies like generative AI (GenAI), and 45% expect profitability to improve further this year. With the digital transformation market set to hit $3.6 trillion by year-end, the question is no longer whether to invest, but how quickly your strategy can scale.

The next phase of digital transformation is no longer just about isolated technology adoption. It’s about integrated orchestration, where competitive advantage depends on how effectively retailers align people, processes, and platforms.

In this article, we’ll explore the shifting imperatives of enterprise retail, examine the strategic drivers fueling transformation, and show how leaders can cut through complexity to drive ROI, agility, and customer centricity.

What Is Retail Digital Transformation?

Retail digital transformation refers to the strategic application of digital technologies in the retail industry to enhance operational efficiency, improve the customer experience, and drive business growth. Retail digital transformation includes POS systems, personalized online shopping experiences, inventory management optimization, supplier transformation, self-checkout systems, cost optimization, VR showrooms, branded mobile apps, geofencing, and AI-powered product recommendations.

What’s Driving the Demand for Digital Transformation in Retail?

The global retail industry is projected to reach $35.2 trillion in 2025, growing at a compound annual growth rate (CAGR) of 7.68%: a trend fueled by rapid technological advancements and shifting consumer behaviors.

According to the latest data, approximately 2.277 billion people worldwide shop online in 2025, accounting for 33% of the global population. This explosive growth signals a permanent shift in consumer behavior, positioning digital channels as the primary battleground for customer acquisition, retention, and loyalty.

Traditional differentiators (like competitive pricing, store proximity, and product variety) are no longer enough. Today’s consumers expect personalized, frictionless, and omnichannel experiences that span mobile apps, physical storefronts, and emerging social commerce platforms.

Retailers leverage real-time data and behavioral insights to increase purchase frequency, tailor engagement, and retain high-value customers who might otherwise default to digital-first competitors.

Ultimately, the demand for digital transformation in retail stems from its direct impact on revenue growth, operational efficiency, and long-term competitiveness. As consumer expectations evolve faster than legacy systems can adapt, transformation is no longer optional; it’s a prerequisite for survival.

Challenges in the Digital Transformation of the Retail Industry

While digital transformation holds immense promise for enterprise retailers, executing it at scale is often undermined by deeply entrenched system silos, legacy infrastructure, organizational inertia.

These roadblocks extend beyond technology; they reveal fundamental tensions in how retailers integrate systems, manage change, and extract value from digital investments. The challenges include the following:

1. Integration across fragmented systems

Retailers often operate with legacy infrastructures, including outdated ERP systems, standalone CRMs, and inflexible POS systems. Introducing next-gen technologies like automation, AI, or predictive analytics into this fragmented environment creates both technical and strategic complexity. Even a seemingly straightforward POS implementation can become a months-long cross-departmental coordination and vendor mediation exercise.

2. Resistance to change

One of the most persistent barriers to transformation is resistance to change from frontline staff, regional managers, and even executive stakeholders. Whether it’s skepticism toward new tools, fear of redundancy, or uncertainty about changing roles, transformation fatigue is real. Technology investments often go underutilized without clear communication, inclusive planning, and well-designed enablement programs.

3. Data silos and operational blind spots

Retailers generate vast amounts of customer, inventory, and transactional data, but rarely in unified, accessible formats. Inconsistent data taxonomies, isolated systems, and a lack of real-time analytics inhibit personalized engagement, reduce forecasting accuracy, and create blind spots in decision-making.

4. Skills gaps and capacity constraints

Even when transformation is prioritized at the highest level, many retailers lack the internal capability to execute their digital strategy effectively. Scarcity of technical expertise, combined with resource strain across departments, often necessitates partnering with a digital transformation consulting company to accelerate planning, integration, and governance.

5. Difficulty proving ROI

Retail transformation strategies can stall when not tied to clear key performance indicators (KPIs). Without robust frameworks to track adoption, usage patterns, or business impact, transformation efforts risk being seen as cost centers rather than strategic drivers of growth and efficiency.

Benefits of Digital Transformation in the Retail Industry

Retail digital transformation isn’t just about adopting tools—it’s about creating meaningful value across the enterprise. Here are some core benefits that directly impact performance, loyalty, and long-term growth.

1. Customer-centric innovation

Digital transformation enables brands to deliver deeply personalized experiences at scale. With the help of AI, machine learning, and advanced analytics, retailers can segment customers, interpret behavior patterns, and launch timely, tailored promotions, boosting both engagement and customer retention.

For instance, Target, the seventh-largest U.S. retailer, uses predictive analytics to anticipate customer needs based on prior in-store behavior. This enhances the customer experience and enables mass personalization, driving repeat purchases and deeper brand loyalty.

2. Operational agility

From real-time inventory visibility to automated order fulfilment, digital transformation accelerates retail operations while enhancing precision, scalability, and responsiveness. Cloud-based platforms, robotics, and integrated supply chain systems help reduce lead times, prevent stockouts, and adapt quickly to supply and demand fluctuations.

According to McKinsey,  leading logistics players are already seeing performance improvements of 10–20% in the short term, and 20–40% within two to four years, by using digital tools across planning, execution, and settlement—the financial and administrative closeout of logistics transactions, including freight billing, invoice reconciliation, and payment processing.

3. Data-driven decision-making

Digital transformation enables retailers to turn fragmented data into a strategic asset. By integrating sales, inventory, and customer data into unified platforms, businesses gain real-time visibility and predictive insights into everything from variations in supply and demand to marketing campaign performance.

In a 2024 Forester survey, 93% of business leaders (including those in retail) stated that improved data sharing and integration are critical to revenue growth. Retailers that successfully unify their data not only enable faster, more informed decisions, but they also outperform their peers. According to the IHL Group, “profit winner” retailers (those growing profits by 15% or more) are adopting predictive analytics at three times the rate of their competitors and deploying it in pricing and promotions at a 400% higher rate.

4. Competitive differentiation

Retailers leveraging digital tools can deliver a seamless omnichannel customer experience—connecting e-commerce, mobile apps, in-store touchpoints, and service channels into a unified journey. This omnichannel strength is now a competitive baseline..

According to Zendesk’s 2023 CX Trends Report:

• 71% of customers want a conversational experience that flows across channels.
• 70% expect every brand interaction to reflect the full context from past engagements.
• 69% are more loyal to brands that offer consistent, personalized experiences across both online and offline channels.

Automation and self-service tools like chatbots and in-app guidance reduce service costs and empower customers to resolve issues independently, improving satisfaction and long-term loyalty.

Examples of Retail Digital Transformation

Retail digital transformation isn’t just a technology trend; it’s a strategic imperative reshaping how enterprise retailers operate, compete, and grow. But successful transformation doesn’t come from tool adoption alone. It stems from clearly defined goals, cross-functional alignment, and sustained execution across people, processes, and platforms.

The following real-world case studies go beyond surface descriptions. Each example explores:

• A retailer’s transformation goal
• The challenges they faced
• The digital strategy they employed
• The measurable business impact
• How a digital adoption platform like Whatfix DAP could accelerate similar outcomes

1. Target: Scaling AI-powered personalization through modern POS integration

Target’s digital transformation journey demonstrated how a legacy retailer can turn transactional systems into engines of strategic growth. By rethinking its point-of-sale (POS) infrastructure not as a backend utility but as a customer intelligence hub, Target unlocked the ability to personalize at scale, blending data, speed, and service in real time.

• Goal: Target aimed to enable real-time personalization across online and in-store experiences by modernizing its POS infrastructure and integrating AI-driven analytics.
• Challenge: Target needed to unify fragmented customer data across channels to deliver consistent, tailored experiences. Legacy POS systems created silos between physical and digital touchpoints, making personalization difficult to execute at scale.
• Transformation Strategy: Target implemented a next-generation POS system integrated with cloud-based CRM, ERP, and analytics platforms to address this challenge. These systems collect real-time transactional and behavioral data, enabling the delivery of personalized recommendations, dynamic promotions, and seamless omnichannel interactions. Mobile POS terminals further improve in-store agility and reduce checkout friction. In 2024, Target also launched its Store Companion, a generative AI-powered chatbot for frontline teams that provides real-time guidance and operational insights, boosting productivity and enabling more informed, responsive customer service.
• Business Impact & ROI: This digital transformation enables Target to increase average order values, enhance inventory efficiency, and drive higher customer retention through personalized mass marketing. Customers experience shorter wait times and more relevant, personalized offers across all channels, which improves both overall customer satisfaction and brand loyalty.

How Whatfix Supports POS Implementations

Whatfix supports this by embedding step-by-step walkthroughs and Smart Tips directly within the POS software. These guides are segmented (based on job roles). For example, cashiers may receive instructions on transaction workflows, while managers will have access to information on inventory features. This dynamic in-app training eliminates the need for printed manuals and reduces errors during peak sales hours.

2. IKEA: Bridging digital and physical shopping through immersive AR commerce

IKEA’s digital transformation illustrates how immersive technologies can dissolve the gap between digital browsing and physical decision-making. By embedding augmented reality (AR) into the customer journey, IKEA empowers users to visualize purchases in their real-world environments, removing uncertainty, increasing confidence, and streamlining the path to conversion.

• Goal: IKEA aimed to improve its customers’ online shopping experience and reduce product uncertainty by integrating augmented reality into its customer-facing platforms.
• Challenge: Furniture and home decor purchases are inherently spatial and aesthetic, making it difficult for customers to feel confident when buying online. High return rates and abandoned carts were partially driven by the inability to visualize products in a customer’s home setting.
• Transformation Strategy: In 2017, IKEA became one of the first global retailers to launch an AR-powered app, IKEA Place, built on Apple’s ARKit platform.  The app allows users to project true-to-scale 3D models of furniture into their homes using a smartphone, with 98% scale accuracy. This enabled customers to assess the fit, style, and spatial compatibility of the product before making a purchase. IKEA’s early investment in AR set the industry pace for immersive commerce and showcased how existing 3D product assets could be repurposed for innovation. By tightly integrating AR with its digital catalog and e-commerce flows, IKEA has created a seamless path from discovery to customer conversion, making visualization a core pillar of its digital retail strategy.
• Business Impact & ROI: The AR solution significantly increased digital engagement, reduced return rates, and led to measurable increases in online conversions. In summary, customers feel more confident in their selections, contributing to higher satisfaction and stronger trust in IKEA’s brand and digital channels.

3. Meijer: Driving in-store engagement with geofencing and location-based offers

Meijer’s digital transformation shows how hyperlocal targeting can turn physical retail spaces into dynamic engagement zones. By combining geolocation technology with real-time mobile promotions, the company has reshaped how customers interact with in-store experiences—bridging the digital and physical worlds in ways that increase relevance, responsiveness, and loyalty.

• Goal: Meijer aimed to increase in-store engagement and conversion by delivering personalized, location-specific offers directly to customers’ mobile devices during their shopping journey.
• Challenge: Despite high foot traffic, Meijer found it challenging to influence real-time in-store behavior. Static promotions and shelf signage lacked precision, and the company needed a scalable way to enhance the customer experience with timely, contextual communication.
• Transformation Strategy: Meijer added geofencing technology and indoor navigation capabilities to its mobile app. When users enter specific store zones—such as produce, pharmacy, or checkout—the app dynamically reorders their shopping lists. It triggers relevant offers, virtual coupons, and product information based on in-store location and purchase history. This strategy combines geolocation intelligence, real-time data, and personalized nudges to transform static aisles into context-aware retail experiences.
• Business Impact & ROI: Meijer’s digital transformation strategy has resulted in higher coupon redemption rates, increased mobile app engagement, and improved customer satisfaction. Dynamic list ordering reduces time spent shopping, while location-based offers positively influence basket size and store loyalty.

4. Warby Parker: Scaling personalized try-ons through AI-powered augmented reality

Warby Parker redefined digital convenience by blending facial mapping, machine learning, and augmented reality (AR) to replicate a highly personal in-store experience—virtually. Its virtual try-on feature allows customers to see how glasses will look on their faces in real time, reducing friction in the purchase journey and setting a new benchmark for digital product trials.

• Goal: The organization aimed to eliminate friction in eyewear selection by enabling customers to try on frames virtually with high realism and accuracy, without needing to visit a physical store.
• Challenge: Eyewear is a highly individualized product, where fit, style, and facial proportions play a critical role in purchase decisions. Traditional e-commerce couldn’t replicate the tactile, reflective nature of trying on glasses, leading to hesitation and higher return rates.
• Transformation Strategy: Warby Parker integrated AR and facial recognition into its mobile app, allowing customers to try on frames virtually in real time. Using Apple’s ARKit and advanced machine learning models, the feature analyzes facial geometry and overlays a true-to-size 3D rendering of each frame onto the user’s live image feed. The tool then automatically adjusts angle, lighting, and proportions, creating a personalized and seamless try-on experience within seconds.
• Business Impact & ROI: This AR-try-on feature drove notable business gains, like  85% higher conversion rates among users of the feature, 41% fewer home try-on kit requests, 22% lower return rates, and 3.2x increase in mobile app downloads post-launch. These outcomes demonstrate how intuitive, AI-driven interfaces enhance purchase confidence, reduce operational costs, and foster stronger digital engagement.

5. ASOS: Reducing returns through virtual fitting and size personalization

ASOS, a global online fashion retailer, has addressed one of e-commerce’s most significant challenges: size uncertainty and high return rates. By combining augmented reality (AR), AI-powered size prediction, and virtual fit visualization, ASOS has created a digital shopping experience that gives customers confidence in product fit without the need for physical try-ons.

• Goal: ASOS aimed to reduce return rates and improve shopper satisfaction by helping customers select the right size and fit before purchasing.
• Challenge: Apparel returns due to poor fit remain a significant source of profit erosion in online retail.  Industry research shows that fit-related returns account for over 77% of all clothing returns. Without the ability to physically try on clothes, customers often resort to ordering multiple sizes—or abandoning purchases altogether—contributing to operational inefficiencies and customer frustration.
• Transformation Strategy: ASOS deployed two key innovations- See My Fit (An AR tool that shows how clothing would look on models with different body shapes and sizes) and Fit Assistant (an AI-powered size recommendation tool that analyzes purchase and return history, product cut, and customer body data to suggest the best-fitting size). Both features are directly integrated into the ASOS mobile app and product pages, providing customers with real-time insights on how items may fit them during the purchase design-making process.
• Business Impact & ROI: ASOS reported measurable improvements across key performance indicators, including reductions in return rates across categories where the Fit Assistant was deployed, customers utilizing these tools had significantly higher order confidence and fewer size-based returns, and time-on-site and checkout completion rates also improved, reinforcing the business case for investment in fit personalization.

6. Walmart: Scaling self-checkout for operational efficiency and customer convenience

Walmart’s digital transformation strategy continues to evolve under its broader vision for Adaptive Retail—a model driven by AI, GenAI, AR, and immersive commerce platforms. Central to this strategy is the widespread deployment of AI-powered self-checkout systems, designed to reduce friction, reallocate labor, and deliver seamless customer experiences across touchpoints.

According to Walmart’s 2024 press release, these systems form part of a broader initiative that includes personalized GenAI platforms, AR-based visualization, and immersive shopping APIs that power personalized, cross-channel retailing at scale.

• Goal: Walmart aimed to modernize its in-store experience by reducing checkout wait times, improving operational efficiency, and integrating personalization, laying the foundation for next-generation digital commerce infrastructure.
• Challenge: Traditional checkout models caused bottlenecks and required high staffing levels. Early self-checkout efforts across the retail industry suffered from usability issues and customer frustration. Walmart needed to redesign this experience with intelligent automation to ensure adoption at scale and minimize disruption.
• Transformation Strategy: Walmart launched its Smart Checkout initiative as part of a larger AI-driven ecosystem that includes AI-powered kiosks with vision sensors and anomaly detection, Scan & Go checkout for smartphone-based transactions, checkout hosts (frontline staff) trained to assist customers and manage customer flow during the transition to self-service., integration with broader personalization tools like the Content Decision Platform and GenAI-powered assistants for real-time, context-aware service, and the AR-powered Retina Platform that supports immersive 3D shopping experiences and is already deployed in 10+ use cases across Walmart U.S. and Sam’s Club. Together, these tools reframed self-checkout not as a payment shortcut but as a gateway to digital-first, highly adaptive retail engagement.
• Business Impact & ROI: As of 2024, Walmart had rolled out AI-powered self-checkout systems in over 500 stores across the United States. The results include shorter wait times, improved staff allocation, and enhanced data collection on customer journeys. These innovations support broader personalization goals and reinforce Walmart’s immersive, adaptive retailing leadership.

7. Target: Expanding customer engagement through its branded mobile app

Target’s branded mobile app has become a cornerstone of its customer engagement strategy, functioning as a personalized shopping hub, loyalty portal, and omnichannel utility. By consolidating multiple services into a single interface, Target has reimagined how digital touchpoints can drive real-time value both online and in-store.

• Goal: Target aimed to deepen digital engagement, grow mobile-based loyalty participation, and deliver integrated shopping experiences that merged browsing, purchasing, and fulfillment across channels.
• Challenge: Retail apps are often plagued by feature sprawl, inconsistent user experiences, and low user retention. To succeed, Target needed an app that was intuitive, purpose-driven, and seamlessly integrated into its broader ecosystem of services, without overwhelming users.
• Transformation Strategy: Target unified its mobile strategy around the Target Circle loyalty program, which anchors personalized deals, rewards, and exclusive promotions. Key features include Order Pickup and Drive Up, which streamline fulfillment and enhance convenience, in-app payments via Wallet,  reducing checkout friction, location-aware services, such as real-time stock checks and dynamic wayfinding, and AI-powered recommendations and behavioral nudges tailored to user preferences and purchase history. These tools provide Target with the data and technology to anticipate customer needs and serve personalized content at the right moment, improving both satisfaction and basket size.
• Business Impact & ROI: 2022 statistics reported that the Target app supported almost 4.3 million daily active users. Moreover, 2024 figures showed that it ranked among the top 8 shopping apps in the U.S., contributing significantly to Target’s e-commerce revenue. During peak periods, nearly 50% of digital sales were driven by Drive Up orders alone. App users consistently demonstrate higher average order values and repeat purchase frequency due to loyalty integration, convenience, and intuitive UX.

8. Zara: Driving cost optimization through data-driven supply chain efficiency

Zara, the flagship brand of Inditex, has long been regarded as a leader in agile retailing. As part of its broader digital transformation strategy, Zara has implemented automation, AI, and real-time analytics across its supply chain. This transformation reinforces Zara’s ability to move fast, operate lean, and respond quickly to evolving consumer demand without sacrificing efficiency or profitability.

• Goal: The retailer aimed to optimize its global supply chain by reducing operational costs, improving fulfillment speed, and enhancing inventory responsiveness at scale.
• Challenge: Fashion retailers face razor-thin margins and intense pressure to balance production, demand, and fulfillment. Zara’s success depended on transforming its historically agile logistics model into a digitally intelligent one that could minimize waste and maximize speed-to-market, even under unpredictable conditions.
• Transformation Strategy: Zara implemented an integrated suite of digital tools, including predictive analytics to forecast demand at SKU and store-cluster levels, automated inventory allocation, dynamically adjusted based on real-time sales, RFID tagging, enabling precise item-level tracking from production to store shelves, and advanced logistics optimization tools that reduce last-mile delivery costs and streamline warehouse operations. By centralizing its digital supply chain data and feeding it into a unified analytics engine, Zara can make high-speed decisions across global inventory flows while minimizing manual intervention.
• Business Impact & ROI: As a result of its digital supply chain overhaul, Zara increased its inventory turnover ratio and reduced holding costs. According to industry benchmarks, retailers leveraging predictive analytics and AI in supply chain operations have achieved 20-30% reductions in inventory holding costs, 15-25% improvements in inventory turnover, 5-20% lower logistics costs, and 5-8% higher service levels. By applying these capabilities, Zara has sustained its ability to replenish fast-moving products in under two weeks, preserving its position as a leader in fast fashion while significantly improving cost efficiency.

9. Sephora: Unifying digital and physical experiences through omnichannel integration

Sephora’s digital transformation exemplifies how retail leaders can create continuity across physical and digital touchpoints. By integrating channels around a unified customer profile, Sephora has established itself as a leader in omnichannel retail. The brand’s app, loyalty program, and in-store systems work in harmony to boost engagement and cross-channel sales, prompting CommerceNext to describe Sephora as “setting the beauty industry’s standard for omnichannel.”

• Goal: Sephora aimed to unify customer interactions across digital and physical channels by building a centralized, data-driven ecosystem that supports personalization, loyalty, and consistent brand engagement.
• Challenge: Retail fragmentation had led to siloed data and inconsistent shopper experiences. Sephora needed to integrate systems for loyalty, inventory, and customer data to ensure that shoppers can transition effortlessly through platforms—whether browsing online, testing products in-store, or accessing support through the app.
• Transformation Strategy: Sephora executed a full-stack omnichannel integration strategy that included centralized CRM and CDP platforms to unify shopper profiles across channels, mobile-first loyalty program (Beauty Insider) integrated with in-store kiosks and apps, real-time inventory visibility shared across e-commerce and physical locations, enabling customers to check stock before visiting stores or placing orders, in-store digital try-on tools powered by AR, synced with mobile browsing history and past purchases, and AI-driven recommendations, personalized across channels via push notifications, product pages, and in-store kiosks.
• Business Impact & ROI: Sephora reports that engaged omnichannel shoppers spend 2.5 times more per transaction than single-channel users and exhibit greater loyalty and repeat purchases—results that CommerceNext attributes in part to unified customer profiles. Additional industry insights from Adobe reveal that customer-centric retailers experience approximately 1.4 times higher retention rates and 1.8 times faster repeat purchase rates.

These examples (from Target’s AI-powered POS overhaul to Sephora’s omnichannel intelligence) demonstrate how enterprise leaders are no longer experimenting with digital transformation; they are scaling it. What sets leaders apart is not just their technology stack, but how strategically they align digital tools with customer experience, operational agility, and measurable business impact.

Whether the goal is personalization, efficiency, or innovation, these case studies demonstrate that transformation succeeds when anchored in outcomes and accelerated by digital adoption platforms like Whatfix, which close the gap between systems and people.

Digital Transformation Trends in Retail

As we move through 2025, retail leaders face a convergence of cost pressures, rising consumer expectations, and accelerated innovation cycles. To succeed, CTOs (Chief Transformation Officers) must distinguish between short-term performance enablers and long-term transformation imperatives.

Below are five of the most strategically significant digital trends shaping enterprise retail this year (each elevated by its business relevance and investment priority).

1. Predictive and prescriptive analytics

• Investment priority: High
• Strategic relevance: Demand forecasting, merchandising precision, inventory agility

Data-driven foresight has become indispensable in retail, enabling companies to anticipate demand shifts, personalize experiences, and optimize inventory decisions at scale.

Retailers are doubling down on big data and advanced analytics to improve forecasting accuracy, minimize overstocking, and optimize the customer journey. Predictive models help anticipate supply and demand at the SKU and store-cluster levels, while prescriptive analytics enable real-time decision-making, from dynamic pricing to localized assortments.

Walmart and Zara are utilizing analytics engines that integrate sales, promotions, and supply chain data to drive responsive operations. The result: higher inventory turnover, fewer stockouts, and a higher return on investment (ROI) on merchandising decisions.

2. Omnichannel integration

• Investment priority: High
• Strategic relevance: Revenue growth, customer lifetime value, loyalty

Seamless customer journeys across channels are now mandatory—not optional—with brands investing heavily to unify commerce, service, and fulfillment touchpoints.

Omnichannel isn’t just about having an app and a website; it’s about synchronizing customer data, inventory visibility, and fulfillment workflows across every touchpoint. Retailers with robust omnichannel programs report significantly higher repeat purchase rates and revenue per user.

Home Depot, for example, links its click-and-collect service with in-app features such as real-time inventory checks, indoor wayfinding tools, and personalized promotions, bridging digital discovery with in-store convenience.

3. AI-enabled IoT and store automation

• Investment priority: Medium
• Strategic relevance: Operational efficiency, theft prevention, in-store analytics

Retailers are increasingly embedding sensors and connected devices into physical stores to streamline operations, reduce shrinkage, and digitize frontline workflows.

Smart, connected devices are transforming how large-format retailers manage security, workflows, and store environments. From RFID-tagged inventory to computer vision cameras, AI-enabled IoT tools offer real-time visibility, predictive alerts, and continuous optimization without manual oversight.

U.S. retailers lost approximately $121.6 billion to theft in 2023, equivalent to $333 million per day, underscoring the growing importance of automated loss prevention. RFID and geofencing technologies now help retailers track product movement, deter shoplifting, and trigger alerts during suspicious activity.

Major retailers are also now deploying smart shelving systems (often linked to RFID and IoT sensors) to maintain accurate inventory, alert staff to low stock, guide planogram execution, and reduce shrinkage—these systems also power back-end analytics that optimize planogram compliance and product availability at the aisle level.

Beyond security, IoT enables employee workflow automation, from dynamic task routing to temperature-controlled inventory monitoring. Large retailers also use location-aware devices to provide contextual in-store experiences, such as mobile promotions triggered by customer proximity to specific departments.

4. Blockchain for transparency and provenance

• Investment priority: Watchlist
• Strategic relevance: Supply chain trust, fraud prevention, ethical sourcing

As customers and regulators demand greater transparency in supply chain accountability, blockchain is gaining traction as a tool for enhancing traceability, authenticity, and ethical sourcing.

Blockchain adoption in retail remains cautious but strategic. The technology is used to verify product authenticity, enhance traceability, and ensure compliance throughout global supply chains. While still in early adoption stages, several enterprise retailers have demonstrated blockchain’s long-term value.

Brands like Nestle and Walmart have piloted blockchain technology to trace products from source to shelf:

• Nestle partnered with OpenSC to launch a blockchain pilot that enables consumers in New Zealand and the Middle East to trace dairy and palm oil products from farm to warehouse, demonstrating scalable, open transparency.
• Walmart implemented blockchain traceability for leafy greens and other perishables through IBM Food Trust, reducing trace time from days to seconds (increasing both food safety and transparency across its supply chain.

These efforts show how blockchain can future-proof supply chains by creating secure, verifiable records of product origin, handling, and delivery. As regulatory pressure mounts regarding provenance, the role of blockchain in retail is likely to grow significantly.

5. Augmented reality (AR) for immersive commerce

• Investment priority: Medium
• Strategic relevance: Conversion optimization, return reduction, customer engagement

Once seen as a novelty, augmented reality is now a proven driver of conversion, empowering customers to evaluate products more confidently and reducing costly returns.

Augmented reality enhances how customers experience products digitally, particularly in categories like furniture, fashion, and beauty. By enabling shoppers to virtually try on items or visualize products in their physical space, retailers eliminate guesswork and reduce post-purchase dissatisfaction.

As described above, retailers like IKEA, Warby Parker, and ASOS are already seeing measurable benefits from AR-powered experiences. These tools enhance customer engagement, boost confidence in size and fit, and reduce operational costs associated with returns and exchanges.

Crucially, the shift to mobile-native AR and web-integrated 3D assets enables retailers to scale immersive features without specialized hardware, delivering rich, frictionless experiences at minimal cost.

Digital Transformation Clicks Better With Whatfix

Enterprise retailers are investing in modern POS systems, AI-powered ERPs, and connected supply chains. But without widespread end-user adoption (across employees, partners, and customers), these initiatives stall. Retail teams are large, dispersed, and often seasonal. Systems are complex. Training is inconsistent. And change fatigue is real.

That’s why large retailers partner with Whatfix.

Whatfix is a digital adoption platform (DAP) that enables digital transformation leaders and product owners with a suite of tools to accelerate user adoption with in-app guidance, supports users in the flow of work with embedded task support, and to take a data-driven approach to workflow optimization with end-user engagement and event tracking.

Here’s how Whatfix directly addresses the most common digital transformation challenges in retail:

• Seasonal and frontline workforce onboarding: Deliver role-specific, in-app walkthroughs that guide employees step by step—no classroom training or PDF manuals required.
• Inconsistent tech adoption across locations: Use Smart Tips, task lists, and on-screen nudges to reinforce correct processes within any system, from POS to warehouse software.
• Training at scale for fast-changing environments: Automate onboarding and upskilling with self-paced, multilingual flows that update in real time as your tools evolve.
• Customer experience consistency: Ensure store associates follow standardized workflows—regardless of location—by embedding guidance directly into the apps they use every day.
• Visibility into adoption and ROI: Track engagement, drop-offs, and user behavior across your tech stack with Whatfix Analytics—then act on what’s not working.
• Support across platforms: Whatfix integrates with desktop apps, mobile platforms, web portals, and proprietary systems—so your transformation strategy isn’t limited by your tech stack.

Digital transformation in retail is complex. Whatfix simplifies it—not just for IT, but for every employee and customer it touches.