With the COVID-19 pandemic shifting customer behavior and causing disruptions across retail businesses, ecommerce and the retail industry, AI technology is revolutionizing how brands and retailers manage their retail operations. As on-premise channels such as hotels, bars, restaurants, and airports suspend operations or close permanently, an estimated US$350 billion is moving into the grocery channel. This surge demands using AI-powered, data-driven solutions to optimize inventory management, merchandising, and replenishment.
Recent research shows that 24 percent of Amazon’s revenue comes from customers who faced out-of-stock items at their local retailers—a figure that has only grown in the wake of shifting customer interactions. Many consumers are now using generative AI, including conversational AI tools like chatbots such as ChatGPT or Gemini, to enhance their customer experience and shopping journeys. Meanwhile, companies across the supply chain are adopting AI algorithms and machine learning algorithms to stay competitive.
Customer demand has surged for essential categories like toilet paper, coffee, and frozen meals, while non-essential items such as sparkling wine and make-up have seen dips. Rapid changes in store layouts and unpredictable shelf movements render traditional data management and real-time data obsolete almost instantly. This calls for real-time, AI-based retail solutions that can provide in-store visibility and agile decision-making.
The rise of BOPIS (Buy Online, Pick Up In-Store) presents both opportunities and challenges. While it improves customer engagement and convenience, it also strains retail operations by depleting shelves and creating gaps that conventional systems struggle to address.
Workforce disruptions have forced retailers to rethink how routine tasks are managed. Deliveries arrive at store doors, but labor shortages complicate replenishment and shelf restocking efforts. AI systems employing computer vision and automation can identify loss prevention issues and help streamline these processes, improving customer satisfaction and reducing revenue loss across all touchpoints.
Traditional agency models, which rent small amounts of in-store time, are inflexible and slow to scale. They lack the ability to rapidly respond to dynamic conditions like new product launches or promotional campaigns. Additionally, agencies prioritize cost reduction over solving retailers’ critical challenges, leading to poor customer segmentation and ineffective execution.
Imagine a service leveraging real-time data and machine learning to deploy the right retail representative at the right store at the right time—providing tailored, end-to-end AI-driven merchandising support and personalized shopping experiences. This is exactly what Trax Dynamic Merchandising offers.
Powered by Trax Flexforce, a skilled on-demand workforce covering 99.2% of US retail outlets, Trax combines artificial intelligence, computer vision, and predictive analytics to address urgent store needs—from audits and restocking to display builds and activations.
This AI-powered approach frees up field reps from manual data management and shelf stocking, allowing them to focus on higher-value activities like relationship-building and marketing campaigns. Whether addressing spikes from product launches or expanding omnichannel coverage, Trax’s solution streamlines operations and drives revenue growth.
Get in touch with us for a demonstration on how Trax’s AI-driven Merchandising can help drive up to 20 percent lift in sales and 25 percent increase in retail presence by doing the right work, at the right store, at the right time.
Give us some info so the right person can get back to you.
