Sunil Munshi, Chief Revenue Officer, Denave, 0
How are NexGen omnichannel engagement techniques reshaping the retail industry?
The retail sector is undergoing a serious transformation lately, wherein customers are no longer siloed in physical stores or digital screens and expect seamless, interconnected experience across all touchpoints. Unlike earlier days when retail was just about having transaction, the retail sector today is more about building relationships and fostering long-lasting connections with the customers. For this, retail players must take an omnichannel approach by leveraging cutting-edge technologies like AI, big data, and personalization to create a unified customer journey across all channels – online, offline, mobile, and social.
For instance, imagine a customer browsing a product online, receiving a personalized discount offer in-store based on their online viewing history, and then completing the purchase seamlessly through their mobile app. With personalized recommendations, relevant content, and frictionless shopping across channels, customers feel valued and understood. Seamless omnichannel journeys eliminate hurdles and guide customers towards purchase, boosting conversions, and fostering deeper customer relationships. Furthermore, omnichannel engagement generates rich customer data, enabling retailers to tailor their offerings and marketing strategies for maximum impact.
Throw some light on the key challenges retailers are currently facing while implementing omnichannel engagement.
Breaking down silos within organizations, integrating disparate technologies, and managing vast amounts of data are some of the major hurdles retailers face while integrating NexGen omnichannel engagement strategies. Furthermore, customer expectations are constantly evolving, demanding constant innovation and agility. Thus, prioritizing customers at every touchpoint will be critical for the success of omnichannel marketing in 2024. This means understanding customers’ needs and translating them into actionable insights through powerful data analytics. Also, investing in robust, integrated platforms fosters a seamless customer journey and provides valuable data to optimize experiences.
How can retailers enhance their engagement with customers through personalized communications and hyper-local experiences?
Research from Epsilon shows that brands which personalize communication across channels see a 72 percent increase in engagement and 43 percent rise in conversion rates. Personalization is all about going beyond demographics and understanding individual customer intent, emotions, and context. Breaking down departmental silos through collaboration encourages cross-functional teams to innovate and deliver personalized experiences. Leveraging data also facilitates providing hyper-individualized recommendations, offers and content, further
strengthening customer relationships. AI-powered personalization, hyper-local experiences, and augmented reality (AR) are other few exciting trends. The focus will be on building emotional connections with customers and creating truly memorable brand experiences. For instance, imagine a customer browsing online while feeling stressed. Using facial recognition and sentiment analysis, the platform could offer calming music, recommend self-care products, or suggest relaxing activities in their area.
On the other hand, hyper-local experiences will also be a critical cog in the personalization engine of retail brands, with geofencing and AR emerging as the key enablers in this regard. For example, imagine walking past a coffee shop. Your phone buzzes with an AR display showing a personalized message welcoming you back, highlighting your usual order, and offering a special coupon. In the case of a clothing store, AR mirrors could let you try on clothes virtually, superimposed on your real-time image. These hyper-local, interactive experiences build lasting memories and strengthen brand loyalty among the customers.
While the customer-facing side gets the spotlight, optimizing internal operations is often the engine driving a seamless omnichannel experience. That’s where AI is poised to revolutionize things. AI platforms can analyze audit data across online and offline channels, revealing granular insights into inventory levels, product placement effectiveness, and even customer behavior near specific shelves. This data becomes the bedrock for optimized ordering, preventing stockouts and maximizing shelf space utilization. Furthermore, there are advancements in the use of drones to flit through the aisles, automatically detecting stock discrepancies, misplaced items and expired products.
In terms of visual merchandising, AI will be the artist’s partner and not replacement. AI tools will be leveraged to analyze customer behaviour captured through cameras & sensors, pinpoint effective displays, and highlight areas for improvement. Furthermore, VR simulations will allow retailers to test different visual merchandising layouts before implementation, leading to data-driven but still creatively captivating displays. Additionally, AI-powered systems will generate dynamic planograms that adjust in real-time based on sales data, customer preferences, and even local weather conditions. Think of a platform analyzing real-time sales from all channels, identifying high-performing products and automatically adjusting shelf space accordingly. No more missed opportunities due to outdated plans!
What are some of the key aspects that retails must pay close attention to while adopting these AI-powered solutions?
Despite the massive advantages that AI tools offer, there are some crucial roadblocks retailers need to navigate before they can truly unlock the magic of these fancy algorithms. Data is a complex entity and often requires robust systems to store & analyze the massive quantum for the AI to work its magic. Additionally, since AI systems don’t come cheap, quantifying their ROI can be challenging, especially in the short term. Also, data privacy and bias in algorithms necessitate ethical data practices and transparent decision-making to build trust with customers and employees. Furthermore, integrating AI with existing systems demands careful planning and change management to ensure smooth implementation. For this, employees’ apprehension regarding their job displacement needs to be addressed through effective communication, training, and reskilling programs.
On the other hand, hyper-local experiences will also be a critical cog in the personalization engine of retail brands, with geofencing and AR emerging as the key enablers in this regard. For example, imagine walking past a coffee shop. Your phone buzzes with an AR display showing a personalized message welcoming you back, highlighting your usual order, and offering a special coupon. In the case of a clothing store, AR mirrors could let you try on clothes virtually, superimposed on your real-time image. These hyper-local, interactive experiences build lasting memories and strengthen brand loyalty among the customers.
Despite the massive advantages that AI tools offer, there are some crucial roadblocks retailers need to navigate before they can truly unlock the magic of these fancy algorithms.
While the customer-facing side gets the spotlight, optimizing internal operations is often the engine driving a seamless omnichannel experience. That’s where AI is poised to revolutionize things. AI platforms can analyze audit data across online and offline channels, revealing granular insights into inventory levels, product placement effectiveness, and even customer behavior near specific shelves. This data becomes the bedrock for optimized ordering, preventing stockouts and maximizing shelf space utilization. Furthermore, there are advancements in the use of drones to flit through the aisles, automatically detecting stock discrepancies, misplaced items and expired products.
In terms of visual merchandising, AI will be the artist’s partner and not replacement. AI tools will be leveraged to analyze customer behaviour captured through cameras & sensors, pinpoint effective displays, and highlight areas for improvement. Furthermore, VR simulations will allow retailers to test different visual merchandising layouts before implementation, leading to data-driven but still creatively captivating displays. Additionally, AI-powered systems will generate dynamic planograms that adjust in real-time based on sales data, customer preferences, and even local weather conditions. Think of a platform analyzing real-time sales from all channels, identifying high-performing products and automatically adjusting shelf space accordingly. No more missed opportunities due to outdated plans!
What are some of the key aspects that retails must pay close attention to while adopting these AI-powered solutions?
Despite the massive advantages that AI tools offer, there are some crucial roadblocks retailers need to navigate before they can truly unlock the magic of these fancy algorithms. Data is a complex entity and often requires robust systems to store & analyze the massive quantum for the AI to work its magic. Additionally, since AI systems don’t come cheap, quantifying their ROI can be challenging, especially in the short term. Also, data privacy and bias in algorithms necessitate ethical data practices and transparent decision-making to build trust with customers and employees. Furthermore, integrating AI with existing systems demands careful planning and change management to ensure smooth implementation. For this, employees’ apprehension regarding their job displacement needs to be addressed through effective communication, training, and reskilling programs.