In just two years, commerce leaders expect more than half of their revenue to come from digital channels. To maintain profitability, retailers must continue to scale revenue drivers while optimizing costs.
Mobile shopping now accounts for over 70% of global e-commerce traffic.
Practices that help retailers bring in new revenue and maintain loyalty include:
Operations that erode profit margins and should be optimized include:
Loyalty is no longer just about points and discounts. It’s about creating a personalized experience that makes customers feel valued at every touchpoint. Today’s loyalty programs are evolving into holistic ecosystems that reward engagement, advocacy, and emotional connection—not just transactions. The most successful retailers use data to understand their customers and deliver relevant, timely, and meaningful experiences that drive ongoing loyalty.
The Evolution of the Loyalty Model:
Personalized product recommendations can contribute up to 25-30% of total online revenue. Omnichannel customers tend to spend 30-50% more than single-channel shoppers.
Operational inefficiencies quietly erode profitability, creating avoidable costs and hindering customer satisfaction. For retailers, identifying and addressing inefficiencies is critical to unlocking sustainable growth. By leveraging AI-driven automation, cost-to-serve analytics, and streamlined resource management, organizations can optimize operations to reduce costs and enhance performance across the value chain.
Inefficiency in operations often manifests in ways that drain resources and lower margins. Returns management, for example, is an area where poor processes can lead to inflated labor costs and missed resale opportunities. Ineffective handling delays restocking and increases the risk of fraudulent returns, problems that AI-powered tools can help mitigate by identifying patterns and flagging suspicious behaviors. Publicis Sapient research highlights that AI can proactively prevent fraud by analyzing purchase and return data to screen for high-risk items and suspicious behaviors, making returns policies both fairer and more cost-effective.
Similarly, without intelligent routing, orders may be shipped from non-optimal locations, leading to order fulfillment errors, slow delivery times, and dissatisfied customers. On the inventory side, relying on manual forecasting frequently results in stock imbalances—either excess stock that ties up capital or stockouts that result in missed sales opportunities. These inefficiencies can feel like small cracks in the system, but collectively, they represent a significant drag on profitability.
As supply chains grow more volatile due to global challenges, including geopolitical tensions and natural disasters, AI’s role in mitigating these inefficiencies is becoming increasingly essential.
To overcome these inefficiencies, retailers need a clearer understanding of their operational costs, which is where cost-to-serve analytics come into play. This data-driven approach offers visibility into the actual costs associated with serving customers across different regions and channels.
For inventory management, AI-powered forecasting tools in platforms like Salesforce Data Cloud enable precise demand predictions, helping retailers maintain optimal stock levels while avoiding overstocking or stockouts. Delivery costs, particularly for the last mile, can also be reduced by using regional demand and inventory data to adjust delivery promises in real time, ensuring that fulfillment remains cost-effective. For instance, demand-forecasting tools have demonstrated the potential of AI to optimize inventory and ensure the right products are in the right channels at the right time, reducing costs and increasing efficiency.
Beyond operational efficiencies, these analytics also enable retailers to segment customers by profitability, using tools like Tableau to focus their efforts on high-value customers and develop strategies that maximize returns. This kind of actionable insight highlights the immense potential of cost-to-serve analytics in driving both efficiency and profitability. Yet, as Salesforce’s State of the AI Connected Customer report indicates, building trust through transparent AI applications is vital, as only 42% of customers currently trust businesses to use AI responsibly, down from 58% in 2023.
Automation is another critical lever for optimizing operations, but its value lies not in replacing human expertise but in amplifying it. Retailers can start by identifying repetitive, high-cost processes and implementing automation solutions to handle these tasks, freeing employees to focus on more strategic areas. Order fulfillment, for example, can be significantly improved with AI-driven tools that dynamically adjust shipping and inventory decisions in real time, ensuring the most cost-effective outcomes.
In customer service, AI-powered chatbots, like Agentforce, can instantly resolve routine inquiries, reducing response times and easing the burden on support teams. These service agents not only enhance efficiency but also offer 24/7 service, addressing customer needs without delay and building loyalty through responsiveness.
Dynamic pricing is another area where automation shines, with tools like Salesforce Einstein enabling retailers to adjust prices in real time, ensuring competitiveness while protecting margins. Transparency remains key to ensuring customer acceptance of these AI-driven processes, as 73% of consumers believe it’s important to know when they’re interacting with an AI agent.
By integrating these tools thoughtfully, retailers can not only reduce costs but also deliver better experiences to customers. Transparency and human oversight remain essential in ensuring that automation aligns with customer expectations. Retailers who embrace AI and automation in this way often see double-digit efficiency gains, paving the way for scalable and sustainable profitability.
Use of AI and automation in commerce increases average order value (AOV) by 10-15%. 71% of customers feel increasingly protective of their personal information.
An efficient and cost-effective fulfillment process is the cornerstone of every retail organization. But as shopping continues to shift to digital channels, many retailers find their fulfillment costs are rising.
Improving delivery options and performance could mean the difference between winning a customer for life and losing them. Tools like shipping rules and an intelligent routing engine can change available stock visible online and find the shortest route to delivery for customers. Last-mile fulfillment is also an important consideration. Solutions like Walmart GoLocal provide not only the software to deliver the package but also services to find drivers and third-party contractors. Amazon Buy with Prime also gives retailers and brands the ability to leverage their Prime services and customer base to provide premium delivery services. (These are both Salesforce Commerce Cloud Partner ISV solutions.)
Nearly all retailers can generate significant efficiency gains in the area of both fulfillment and returns by refining their supply chain. In many cases, making small changes can generate significant returns.
The broad availability of ChatGPT and other AI-powered solutions has completely changed the landscape of product search and comparison. A customer can now skip Google and head to ChatGPT for product recommendations. Or, if a brand is utilizing Agentforce, they can draw the customers directly to their site for the same analysis. Companies that don’t consider implementing similar technologies on their sites risk losing out to the competition.
These shifts also affect the connection between digital and physical channels. Brick-and-mortar retail must also change as a result of shifting customer behaviors, and retailers must adjust their physical footprint to accommodate these changes.
In today’s landscape, retailers must focus on having effective stores that cater to digital-first shoppers. This may mean downsizing to smaller stores and creating dark stores, micro-warehouses, or designated click-and-collect locations to aid with distribution or reformatting store layouts to better accommodate in-store pickups.
More people than ever before are dropping the “e” from e-commerce. Store and online experiences are blending, and commerce is moving to a channel-driven approach where customers can shop anywhere and from any channel. Enabling multiple channels, including social and technologies that enable e-commerce shopping in the store, will be key. Endless aisles and self-checkouts are rising in popularity with customers, and companies like POQ (a Salesforce Commerce Partner) are jumping in to fill this niche. Retailers can create self-checkout experiences in apps so that customers can scan in-store and either have a courier bring it to them or ship it to their house.
Salesforce’s acquisition of PredictSpring marks a significant step in its expansion into the clienteling and point-of-sale (POS) market at a time when customers are increasingly expecting seamless, omnichannel experiences. PredictSpring’s platform is designed to provide mobile POS, clienteling, inventory and order management tools, helping retailers create more integrated shopping experiences across various touchpoints—whether online, in-store or mobile. As retailers look to deliver more personalized, concierge-like services, empowering employees with data about customer purchase histories from across all channels, including social media, becomes essential.
What makes this acquisition particularly exciting is the timing: AI agents are now playing a pivotal role in creating efficiencies within retail operations. By leveraging AI, retailers can streamline processes, delivering real-time, personalized experiences for customers while optimizing back-end systems. This powerful combination of AI and the PredictSpring platform can allow Salesforce to bridge the gap between different shopping environments, ensuring a smooth, connected experience that customers expect and making it easier for retailers to thrive in an increasingly competitive market.
Retailers can address these issues at the operational level by investing in four key areas of supply chain optimization. These core changes will help retailers become agile, predictive, and responsive while maintaining a laser focus on costs.
Up to 45% of shoppers are likely to choose “Buy Now Pay Later” if it’s available.
E-commerce profitability is tied closely to technology—and with good reason. Each example discussed within the supply chain and product catalog relies on technology, in one form or another, to identify opportunities and activate solutions.
The most obvious example of the power of technology can be found in data analysis and, by extension, artificial intelligence (AI) and machine learning (ML). With enough high-quality data, retailers can identify trends that can help anticipate buying patterns, optimize inventory levels, right-size the workforce, and set prices and promotions that maximize revenue. These technologies draw on a vast array of data sources, including past transactions, behavioral data, social media activity, and geographical location, to create algorithms and models that give the organization both a more complete customer profile and greater awareness of the business. AI agents, particularly through platforms like Salesforce Agentforce, can help automate these processes, personalizing customer interactions in real time while continuously improving system efficiencies. AI can also be used to power solutions—from 24/7 customer service chatbots to customized product recommendations—thus helping retailers increase their profitability in the burgeoning digital world.
An equally powerful opportunity lies in robotic processing automation (RPA). Many warehouses are woefully out of date, relying on humans to collect items for digital orders. Through the use of scanners, conveyor belts, robots, automated forklifts, exoskeletons, and drones, the time spent at every stage of the fulfillment process can be significantly reduced. Not having a centralized and automated shipping facility makes it nearly impossible for retailers to achieve the efficiency of other modern e-tailers, all of whom are leveraging the latest in robotics and automation technology to increase efficiency.
With generative AI, a good data strategy is now more important than before. Trust is a key consideration, so having data policies in place for everything from collection to training the AI is crucial to a company’s success. Generative is also creating more data, so organizing your data lake accordingly can give businesses a competitive edge. When training generative, it’s essential to develop policies around which data should be used, which to obfuscate, and how to maintain privacy. Developing good data strategies that answer these questions should be one of the first steps when preparing to implement AI agents and tools like Agentforce.
The deployment of data-enabled tools and robotics requires a level of speed and flexibility far beyond what is supported by many retailers’ current IT operations. Although organizations appear eager to adopt advanced technologies such as AI and ML, their ability to effectively do so—and harness the applications’ full benefits—may necessitate infrastructure upgrades. The cloud holds promise because migrating key business services to cloud-based systems enables near real-time performance monitoring and inventory awareness. Such insights can unlock new levels of efficiency across the value chain, from inventory optimization to product recommendations and customer service. Cloud-based technology also provides the speed and flexibility needed to scale, which is a crucial point as retailers attempt to expand successful pilot programs or test applications throughout the organization. AI agents integrated within the cloud environment can further enhance these capabilities by driving automation and personalization at scale.
Although virtually all organizations recognize the value of technology, many stop short of implementation, largely due to cost concerns. However, technology infrastructure investments are just that—an investment. Increasingly, these capabilities are not just enablers of growth but also key to viability. Fail to keep pace with digital applications, and the entire business will suffer.
Research by Publicis Sapient found that IT infrastructure investments can pay back in two-to-three years while continuing to create long-term value through increased conversion, affinity, and loyalty. Our research estimates an annual cost savings of 17.5 percent through reduced operating costs, increased productivity, and quality.
Although many retailers are experiencing e-commerce profitability today, few are taking a holistic approach to maintaining sustainable growth and retention over time. Here are some thought-starters for retailers as they continue to refine and optimize their e-commerce strategy:
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Publicis Sapient is a digital business transformation company. We partner with global organizations to help them create and sustain competitive advantage in a world that is increasingly digital. We operate through our expert SPEED capabilities: Strategy and Consulting, Product, Experience, Engineering and Data, which combined with our culture of curiosity and deep industry knowledge, enables us to deliver meaningful impact to our clients’ businesses through reimagining the products and experiences their customers truly value. Our agile, data-driven approach equips our clients’ businesses for change, making digital the core of how they think and what they do. Publicis Sapient is the digital business transformation hub of Publicis Groupe with 20,000 people and over 50 offices worldwide. For more information, visit publicissapient.com.
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