Top 6 Omnichannel Retail Trends to Watch Out For in 2025
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Shoppers today move seamlessly between online stores, mobile apps, social media, and physical shops. Omnichannel retail trends are helping B2C brands meet these expectations by connecting every touchpoint and creating experiences that feel effortless and personalized.
But how? Well, hopping on the latest omnichannel marketing trends, retailers are using AI, AR/VR, and unified commerce platforms to anticipate customer needs, suggest the right products, and provide consistent experiences across all channels. These innovations make shopping easier, more engaging, and more likely to drive repeat business.
Here are six omnichannel retail trends every marketer should know to stay ahead and deliver experiences that truly connect with customers.
6 Omnichannel Retail Trends for Marketers to Keep on Top of
As customer expectations evolve, staying ahead in retail means more than just being present across channels. It’s about creating seamless, personalized journeys that delight shoppers at every touchpoint.
That’s crucial because, according to MoEngage’s 2025 State of Cross-Channel Marketing in Ecommerce & Retail Report, acquiring new customers is the no.1 priority for 48.7% of retail and Ecommerce marketers. And unfortunately, 50.9% of marketers still struggle with cross-channel communication.
Here are 6 key trends that are shaping the future of omnichannel retail marketing, helping brands deliver seamless experiences across every touchpoint.
Omnichannel experience and engagement
A seamless, personalized customer experience has always been a critical factor in omnichannel experiences. Customers need to feel that their journey is connected and interactive, regardless of the channel where it starts.
1. AI-powered conversational commerce
Source: https://www.haptik.ai/blog/conversational-ai-e-commerce-sales/
In conversational commerce, we use multiple touchpoints, such as AI chatbots, messaging apps, and voice assistants, to assist customers with product discovery, checkout, and support—all from within the conversation. In 2025, retailers are moving from basic chatbots to agentic AI systems that can handle complex tasks like product bundling, order modifications, and smart product recommendations.
Why it matters:
AI can analyze browsing habits, app usage, and purchase history to predict what customers will want next. This allows retailers to anticipate needs before customers even realize them and deliver timely, personalized customer experiences. The result? A proactive way to engage customers, meeting their needs before they even ask.
Agentic workflows take this a step further.
These AI-driven processes use your retail tech stack to power real-time automations that make customer interactions seamless across channels.
From sending QR codes for in-store redemptions and recommending products based on past purchases, to triggering follow-up tutorials via email or automated push notifications, these workflows create truly connected, omnichannel journeys. They can even handle tasks like reminding customers of expiring rewards or sending post-purchase care tips, turning chatbots into smart personal assistants for the shopping experience.
Marketing takeaway:
Imagine retargeting a shopper who abandoned a cart online, with a personalized automated text message offer that also works in-store. Or think of using chatbot interactions to dynamically segment audiences for your next seasonal push. When AI combines service data with marketing automation, your omnichannel campaigns can pivot in real time based on what the customer just said or did.
For example, Sephora uses AI to deliver personalized, omnichannel shopping experiences through tools like Virtual Artist and Color Match. These tools let customers try products virtually and get tailored recommendations. Their AI-powered assistants also handle bookings and support across channels like Facebook Messenger, creating a seamless journey from online to in-store.
For marketers, Sephora’s approach is a masterclass in using interaction data from these tools to implement precision targeting. Every try-on, booking, and support chat becomes a signal that can trigger personalized follow-ups across email, app, push notifications, and loyalty programs.
2. Immersive AR/VR shopping experiences
Source: https://bagisto.com/en/virtual-try-on-ar-technology/
Augmented Reality and Virtual Reality are among the most talked-about omnichannel retail trends. Interestingly, a number of retail brands are leveraging augmented and virtual reality tools to enable virtual try-ons and 3D product demos. The goal is to help the customer visualize how a product would look without actually visiting a brick-and-mortar store.
By overlaying digital information onto the real world, these technologies bridge the gap between online and physical shopping.
Why this matters:
Immersive experiences like AR matter because they boost confidence in purchase decisions, which translates into higher conversions and bigger order values. Research shows 71% of shoppers would buy more often if AR were available, and Shopify reports a 94% higher conversion rate for products with AR/3D views.
Marketing takeaway:
For B2C marketers, an AR try-on on social media can lead to an email with wishlisted looks, which leads to an in-store visit where the sales associate already has the wishlisted items ready for the customer. This creates a unified customer purchase journey that blurs the line between campaign and experience, making every touchpoint actionable in your marketing tech stack.
American Eagle demonstrated this during its holiday campaign by introducing an AR virtual try-on on Snapchat. Named Try-on Haul Lens, the experience received millions of views and drove strong traffic from the AR Lens to their Ecommerce pages, proving AR’s ability to act as both an engagement driver and a powerful conversion tool in an omnichannel journey.
The lesson here is that AR content provides interaction data, like which styles were tried on, which clicks led to purchases, and for how long customers engaged. You can feed that data into your CRM to re-engage customers with highly relevant offers, run localized store promotions, or adjust designs for the strongest performing channels.
Data-driven decision making
Retailers today are using real-time insights and AI-powered analytics to make decisions that are faster, smarter, and more focused on the customer. By connecting data from every touchpoint, brands can predict what shoppers want, adjust campaigns on the fly, and deliver a smooth, consistent experience across all channels.
3. Real-time insights for agile marketing strategies
Real-time analytics give brands an instant look at customer behavior, from the products they’re browsing to what ends up in their cart and what finally makes them buy. This data comes from different sources, like website clicks, app activity, in-store sensors, and even social media interactions.
With these insights coming in live, marketers can quickly adjust their strategies, boost what’s working, and fix what’s not before it affects sales.
Why this matters:
Real-time analytics matter because customer preferences can shift in seconds, and every interaction is a chance to deliver exactly what they want in the moment. When retailers respond instantly with personalized experiences, it drives satisfaction, loyalty, and higher sales.
Marketing takeaway:
Imagine noticing a sudden spike in interest for a product in-store, then immediately launching a push notification or social ad to leverage it. Or adjusting an email offer based on inventory changes. The more touchpoints you can connect in your data stream (Ecommerce, social, app, and POS), the more effective unified campaigns you can create that bridge physical stores with digital channels.
Amazon is a great example in this case. Its recommendation engine alone contributes 35% of total revenue, powered by real-time analysis of browsing and purchase behavior to personalize homepages, emails, and offers.
This example shows the power of personalization, where every view, click, or in-store interaction can instantly trigger a relevant follow-up on another channel.
4. Multi-touch attribution
Multi-Touch Attribution (MTA) credits every interaction a customer has during their buying journey, both online and in-store. Unlike models that only count the first or last click, MTA spreads the credit across all touchpoints, such as social ads, emails, website visits, in-store interactions, and app activity. This helps retailers see the full picture of what actually drives conversions.
Why this matters:
Today’s shoppers move across multiple touchpoints before making a purchase, with research showing most engage with three to five channels along the way.
This complexity makes traditional attribution models like last-click unreliable, as they ignore upper-funnel and offline interactions, leading to wasted ad spend. Modern attribution solves this by integrating POS data, CRM logs, and digital analytics to give brands a full view of the omnichannel customer journey. With this clarity, retailers can allocate budgets more effectively, understand which channel combinations drive conversions, and create smooth handoffs between online and in-store experiences for a better overall customer experience.
Marketing takeaway:
Instead of arguing over which single channel takes credit, you can prove how email plus mobile push drives repeat purchases, or how social plus in-store sampling boosts conversion. The results are two-pronged — one, campaigns that combine the right media and store-based touchpoints. Secondly, you get measurable proof that online and offline marketing investments are working together.
For example, The Home Depot used multi-touch attribution and saw a 15% lift in sales. By analyzing all touchpoints, they discovered that their mobile app homepage drove conversions 2.5 times more than their website homepage. With this kind of insight, brands can spend budgets smartly, see which channels work best together, and create a seamless experience between online and in-store shopping.
Intelligent channel orchestration
Many brands already use omnichannel marketing, but the next step isn’t adding more channels—it’s making them work together. Customers are tired of irrelevant emails and generic offers, so sending more messages using email marketing software doesn’t mean better results. The future is in AI-powered orchestration, where data and automation choose the best message, channel, and timing for each customer.
That’s the difference between omnichannel vs. multichannel marketing in retail, where every touchpoint fits into one connected conversation with the customer.
5. Predictive send-time and channel optimization
Another of the latest omnichannel retail trends, predictive send-time optimization, uses AI to figure out the best time to send messages to each person. Instead of sending messages at the same time for everyone, it looks at past behavior to learn when someone is most likely to open an email or check a notification.
This way, your message arrives when they’re most likely to see it, making it feel timely and relevant. It’s important because it improves engagement and conversions without adding more messages, so customers get a better experience without feeling spammed.
Why this matters:
Predictive matters because timing can make or break engagement. Even the best offer won’t work if it lands when the customer isn’t paying attention. By sending messages when customers are most likely to notice and act, brands can boost customer engagement metrics, like open rates, click-throughs, and conversions, without flooding inboxes.
It also helps reduce unsubscribes, since customers get messages that feel relevant instead of annoying. In short, predictive timing makes marketing smarter and more respectful of the customer’s time.
Marketing takeaway:
Predictive send-time optimization lets you hit all your retail touchpoints (SMS, app, email, and loyalty alerts) exactly when the customer’s attention is most available. And because it’s AI-powered, you can scale this feature across millions of customers without manual scheduling. That’s why it’s a perfect fit for highly dynamic omnichannel campaigns.
Take the LA-based digital entertainment brand JibJab, for example. They moved away from fixed schedules and started using predictive timing for their messages. As a result, they saw an 82% increase in click-through rates (CTR).
The goal is to thread messages into the customer’s broader journey, so that what they see in one channel supports what they just saw or did in another.
6. Content adaptation across channels
Consumers connect with brands in many different ways, but the content they see shouldn’t feel like the same thing repeated everywhere. Intelligent orchestration tools help by adapting messages to fit the context of each channel.
For example, an email promotion can be turned into a short in-app notification or a social ad that matches the campaign theme but feels natural for that platform. This keeps the experience consistent without being repetitive, which helps reduce fatigue and keep engagement high.
Why this matters:
For omnichannel retailers, this matters because customers often move between online and offline touchpoints before making a purchase. If the messaging feels either repetitive or disconnected, it creates friction and can lead to drop-offs.
Adapting content to fit the channel keeps the experience smooth and relevant, whether the customer is browsing an app, scrolling social media, or visiting a store. This not only improves engagement but also builds trust and drives higher conversions across the entire journey.
Marketing takeaway:
Content adaptation is the secret to making an omnichannel retail campaign feel like one continuous narrative. A customer who sees a seasonal launch in their Instagram feed could get a more detailed story in email, a special offer in-app, and an in-store sign-up nudge.
Each of these messages would be tailored for that moment of contact, but all of them would somehow feel connected. This approach makes campaigns feel fresh at every touchpoint, while still delivering one unified brand experience.
Emerging Technologies Empowering Retail Omnichannel Trends
As shopping gets more complex and customer expectations rise, technology is key to creating smooth omnichannel experiences. These tools don’t just make things easier—they change how retailers understand, engage, and keep their customers across different channels, forming the backbone of a strong omnichannel retail strategy.
Here are five technologies fueling the next wave of omnichannel retail trends.
1. Artificial Intelligence and Machine Learning
AI and machine learning let systems analyze large amounts of data, spot patterns, and make predictions or decisions on their own. In omnichannel retail, this means powering things like personalized product recommendations, dynamic pricing, and predicting demand so inventory stays on track.
The result is more relevant experiences for customers, delivered at the right time and place. Brands like Amazon and Sephora use AI for personalized recommendations, while grocery stores rely on it to keep inventory updated in real time.
MoEngage, for instance, provides powerful AI capabilities for B2C brands through two engines — Merlin AI and Sherpa AI. Sherpa AI helps you send the right optimized message to the right customer on the right channel at the right time. Meanwhile, Merlin AI is a Generative AI engine that lets you create personalized copy and creatives for your campaigns in no time.
2. Unified commerce platforms
Unified commerce integrates all sales channels, inventory systems, and customer data into a single platform, giving retailers real-time visibility across online and offline touchpoints.
This allows customers to start their journey online and finish it in-store—or vice versa—without friction, making the shopping experience seamless.
Brands like Nike and Target use unified commerce to offer services such as buy online, pick up in-store (BOPIS), ship-from-store, and same-day delivery. For example, Nike aligns its website, app, and mobile notifications so customers receive consistent, timely messages across every channel, improving inventory accuracy, operational efficiency, and overall customer satisfaction.
3. Augmented Reality (AR) and Virtual Reality (VR)
Augmented reality (AR) and virtual reality (VR) are transforming how customers experience products before they buy. AR overlays digital content onto the real world, letting shoppers virtually try on makeup, place furniture in their homes, or preview other products in context.
VR takes it a step further by creating fully immersive environments where customers can explore and interact with products digitally.
4. AI-powered orchestration and contextual automation
AI-powered orchestration and contextual automation take the guesswork out of customer engagement by analyzing behavior, preferences, and past interactions to deliver messages that truly resonate. Instead of sending generic emails or push notifications at fixed times, these systems figure out the best channel, format, and timing for each individual, ensuring that every touchpoint feels personal and relevant.
MoEngage, for example, uses Sherpa AI to monitor and analyze customer actions across web, mobile, and in-app interactions, then dynamically adjusts campaigns based on real-time context. This kind of omnichannel retail software not only increases engagement—sometimes up to four times—but also reduces message fatigue, improves conversion rates, and strengthens long-term customer relationships.
By orchestrating communications in a smart, data-driven way, brands can create seamless experiences that keep customers coming back across all touchpoints.
5. Cross-channel integration and unified customer view
Cross-channel integration and a unified customer view help brands connect all their touchpoints—email, SMS, app notifications, WhatsApp, web push notifications, in-app messages, and more—into a single platform.
By bringing this data together, companies get a complete 360-degree view of each customer, which makes it easier to deliver consistent, personalized experiences no matter where someone interacts with the brand.
MoEngage, for instance, enables retailers to see customer behavior and engagement across channels in one place, acting as a comprehensive omnichannel marketing platform that allows campaigns to be coordinated seamlessly. This unified approach not only speeds up campaign execution but also ensures messages are relevant and timely, reducing redundancy and boosting overall engagement across the customer journey.
MoEngage Powers Personalized Campaigns for Retail Marketers
Emerging technologies like AI, AR/VR, and unified commerce are fueling omnichannel retail trends, helping brands deliver seamless, personalized experiences across every touchpoint. Platforms like MoEngage make it easier for marketers in the retail industry to orchestrate these experiences, giving marketers real-time insights and automation to drive engagement and conversions.
Sign up for a demo today and see how MoEngage can power your omnichannel campaigns.
