Running an eCommerce store on Adobe Commerce or Magento opens a world of opportunities to create next-generation shopping experiences leveraging the latest innovations. This article looks at cutting-edge strategies to step up your eCommerce game using this popular platform – still the most popular in the world including the Adobe Cloud version and the open source version of Magento.
Artificial intelligence has revolutionized eCommerce by enabling hyper-personalized recommendations to individual customer journeys. Sophisticated AI algorithms analyze behavior patterns, purchase history, and browsing habits to promote precisely tailored products to each shopper. The machine learning and data science behind AI personalization continuously get smarter to serve up items that delight and captivate.
AI takes personalization to the next level in ways no human team ever could. Recommendation engines powered by artificial intelligence have clear advantages:
- Deeper Analysis – AI analyzes exponentially more data points across customer profiles and product catalogs, detecting subtle patterns.
- Faster Processing – Recommendations can be generated in real-time thanks to AI’s quick computational power.
- Continuous Optimization – The machine learning loop constantly fine-tunes results.
- Less Bias – AI has no personal biases, allowing for more objective suggestions.
- Higher Conversions – Hyper-personalized product suggestions convert at higher rates.
According to Statista, 66% of consumers expect a personalized shopping experience. AI optimization helps retailers deliver this tailored engagement that consumers want and are open to product suggestions.
From personalized search results to custom product suggestions and even individualized pricing, AI unveils new ways to personalize each phase of the customer journey. AI-powered personalization should be a centerpiece of any cutting-edge Adobe Commerce or Magento strategy.
AI Implementation Tips
When activating AI-enhanced personalization, keep these tips in mind:
- Start by defining key metrics to optimize such as conversion rate, average order value, and repeat purchase rate. Continuously A/B test to lift these KPIs.
- Analyze which user attributes and behavioral signals best predict desired outcomes. Feed these insights into your AI model.
- Be transparent by letting customers know recommendations are personalized and giving them control to adjust suggestions if desired.
- Combine AI with other data like loyalty profiles, CRM systems, and point-of-sale records to present complete 360 customer views.
Allow Augmented Reality Previews
Augmented reality (AR) previews enable online shoppers to visually preview products in their own space before adding items to their cart. AR technology superimposes digital models over the camera viewfinder on smartphones or other devices. Shoppers can see 3D product visualizations at a real-world scale, gaining a realistic sense of dimensions, textures, and colors.
This immersive augmented experience builds confidence for customers to click “add to cart” knowing items suit their needs, style, and space. AR previews bridge the divide between physical and digital retail, bringing the tangibility of in-store shopping into eCommerce.
We worked with one of our brand partners, Maria Tash, to use AR in their try-on studio to showcase how their jewelry can look on an ear. Since then, their revenue and engagement has gone up significantly.
According to Fortune Business Insights, the global augmented reality market size was valued at USD 42.20 billion in 2020 and is projected to reach USD 1,109.71 billion by 2030. This information, however, encompasses the entire AR market and not just the retail sector. The source can be found here.
Additionally, a study by MarketDigits, reported on GlobeNewswire, projects the Augmented Reality (AR) Shopping Market to reach USD 20.6 billion by 2030, up from USD 3.5 billion in 2023. This reference does not match the specific figures and year (2020) you mentioned for Juniper Research but provides an insight into the growth of the AR shopping market.
Now is the time for forward-thinking merchants to explore AR-powered shopping. Turn website visitors into paying customers by letting them preview their first augmented reality product models.
AR Implementation Guide
When launching AR previews, consider this:
- Educate customers on AR capabilities through icons, cues, and tooltips directly on product pages.
- Reduce friction by auto-triggering AR when camera access is approved rather than adding clicks.
- Focus first on categories with the most returns like furniture, clothing, jewelry, and cosmetics where AR adds the greatest value.
- Craft detailed 3D models, ensuring accuracy regarding scale, appearance, and functionality.
- Offer AR instructions and guidelines so shoppers best leverage the experience.
- Capture user feedback to improve AR functionality continuously.
With augmented reality, eCommerce can feel like a real-world shopping experience. Enable shoppers to preview before they buy with immersive AR product views.
Chatbots Provide 24/7 Assistance
Another cutting-edge innovation for Adobe Commerce and Magento merchants is AI-powered chatbots. Intelligent chatbots interact conversationally with website visitors to answer questions, recommend products, encourage purchases, and resolve issues. With sophisticated natural language processing, chatbots comprehend questions and then supply relevant responses. This delivers helpful self-service to shoppers 24/7.
Forrester forecasts that chatbots will influence or generate over $142 billion in retail sales by 2023. These automated assistants streamline shopping in many ways:
- Quicker Answers – Instantly reply to frequently asked questions.
- Expanded Availability – Engage guests anytime without staffing limitations.
- Faster Checkouts – Simplify purchases by integrating chatbots with payment systems.
- Improved Conversions – Guide users along the conversion funnel with personalized suggestions.
- Enhanced Experiences – Delight shoppers with swift, satisfying service.
According to an Oracle study, 80% of brands are already implementing or plan to implement chatbots by 2022. These AI helpers have become integral for top retailers to facilitate seamless omnichannel commerce.
Chatbot Best Practices
Follow these tips when launching chatbots:
- Build a knowledge base of questions, answers, and responses to power natural language interactions. Continuously expand this database.
- Program a defined persona and conversational style. Chatbots should introduce themselves and communicate politely.
- Allow shoppers to opt out and connect to human agents if preferred. Maintain this hybrid approach.
- Test chatbots across browsers and devices to address any compatibility issues.
- Monitor chatbot usage to surface common questions and improve capabilities.
With intelligent chatbots, ecommerce merchants can deliver instant, personalized support. Implement smart virtual assistants to increase sales and optimize CX.
Immerse Shoppers With Interactive 3D Product Imagery
3D model visualization brings products to life on your Adobe Commerce or Magento website product catalog. Interactive 3D images allow customers to manipulate items to view at any angle, expanding on static 2D images. Shoppers can zoom, spin, and adjust 3D visuals like product images on webpages and product pages to scrutinize details with exactness.
This immersive experience enables online buyers to preview aesthetics, ergonomics, and scale before adding an item to their cart. 3D reduces returns from improper sizing while building confidence in quality and appearance.
According to research by The Harris Poll 60 percent of 1,869 U.S. adults who ever shop online are more likely to buy a product if it is shown in 3D or AR. Additionally, many online shoppers felt that it would help them make more confident decisions:
- 66 percent said that 3D/AR visuals would increase their confidence that they’re buying the right product.
- 66 percent said they would be more interested in shopping on a website if it offered 3D/AR images.
- 42 percent say they would pay more for a product if they could see it in 3D/AR.
As 3D maturity increases, interactive models replace static images for improved storytelling and conversions.
Getting Started with 3D
When adopting 3D visualization, follow these best practices:
- Prioritize 3D models for high-consideration categories like furniture, jewelry, eyewear, and clothing.
- Create 3D visuals optimized for web deployment – condensed file sizes with efficient polygons.
- Use smart hotspots on 3D models to showcase features, provide detailed zoom-ins, and prompt calls-to-action.
- Offer shoppers 360-degree product spins for complete visualization.
- Feature 3D front-and-center on pages rather than tucking models away.
- Share and syndicate 3D assets across channels like social ads and email campaigns.
With interactive 3D models, merchants make online shopping more tangible. Immerse customers with new ways to explore products digitally.
Connect Physical and Digital Worlds
Innovative Adobe Commerce and Magento brands connect physical and online environments into unified shopper journeys. Location-based services, mobile apps features, in-store technologies and omnichannel loyalty programs erase lines separating brick-and-mortar stores from ecommerce.
Connected retail powers experiences like:
- Online orders retrieved via curbside pickup or in-store pickup.
- Virtual shopping consultations with in-store associates via video chat.
- In-store digital mirrors to view alternate colors and sizes without changing.
- Smart fitting rooms with tailored clothing recommendations.
- Scan and go mobile checkout to skip in-store lines.
- Universal loyalty rewards and VIP access spanning online and offline.
According to research from Salesforce, 63% of shoppers expect unified retail experiences regardless of channel. Location-based services are especially popular for conveniences like buy online, pickup in-store or location-based product recommendations.
Omnichannel innovation dismantles channel silos to intertwine physical and digital touchpoints. Take advantage by connecting the dots across the retail ecosystem.
When pursuing connected retail strategies:
- Break down internal data silos to aggregate online behavior with offline profiles in a single customer view.
- Allow customers to buy items online and conveniently pick up products in stores via click-and-collect services.
- Share in-store and eCommerce inventory counts in real-time to promise accurate availability across channels.
- Arm in-store associates with clientele apps to access cross-channel order history and offer personalized promotions.
- Unify loyalty programs, coupons, and pricing across channels so perks span the omnichannel journey.
Merge online and offline channels to help brands engage, convert, and fulfill anywhere.
Voice Commerce Opens New Frontiers
Voice-based interfaces bring conversational commerce to life through AI assistants like Amazon Alexa, Google Home and Apple’s Siri. Smart speakers and other voice-first devices allow hands-free shopping and search.
Juniper Research predicted voice commerce sales would exceed $8 billion annually in 2023. Early adopter categories include groceries, electronics, and clothing.
Brands embracing voice commerce can enhance convenience for customers by:
- Enabling product discovery through conversational search queries.
- Suggesting complementary products based on purchase history via voice app skills.
- Providing account balance lookups, loyalty points, order status, and other voice-activated queries.
- Streamlining reorders of favorite items through predictive restocking.
- Offering voice-initiated checkout to expedite purchases.
- Emailing receipts summaries post-order for reference.
As smart speakers and screens proliferate consumer living spaces, retailers must prepare for device-agnostic shopping dominated by voice and visual interfaces.
Voice Commerce Considerations
When exploring voice commerce, keep this advice in mind:
- Submit brand name, product catalog, and example voice interactions to voice assistant platforms so content surfaces during searches.
- Craft a helpful, intuitive voice app integrating Commerce Cloud APIs to enable frictionless voice transactions.
- Monitor voice analytics around queries, clicks, and sales to refine functionality.
- Promote voice capabilities through smart speaker tutorials and incentive programs to drive adoption.
- Continue catering to conventional web and mobile users while testing voice interfaces.
Voice simplifies commerce. Prepare for conversational interactions across platforms as assistants turn talk into sales.
Localize Experiences with Location-Based Marketing
Location-based marketing leverages mobile proximity and geo-fencing to deliver hyper-relevant messaging. By identifying a smartphone user’s geographic coordinates, retailers can serve notifications regarding nearby stores plus contextually relevant offers.
Imagine a customer who browsed hiking boots last week. When passing near an outdoor gear retailer, the shopper receives a discounted offer via smartphone to return and complete the transaction. This timely message catalyzes conversion.
Proximities to brick-and-mortar outlets combined with data regarding interests, searches, and purchase history inform location-based marketing. Consumers grant location access in exchange for discounts, convenience, and personalized recommendations.
Geo-targeting precision empowers retailers to:
- Alert customers to nearby store locations with navigational links.
- Promote localized flash sales based on inventory levels per location.
- Offer timely discounts for previously browsed or purchased items.
- Extend personalized recommendations for complementary products.
- Enable easy buy online, pick up in-store convenience via mobile alerts.
With 87% of US adults allowing apps to access their location, the opportunity abounds for proximity marketing. Part art, part science – location-based tactics boost engagement when messages meet moments.
When launching location-based initiatives:
- Provide value upfront via geo-fencing by offering instant savings versus intrusive ads.
- Identify categories like quick-serve restaurants with high location relevancy for piloting programs to demonstrate ROI.
- Outline a location data retention policy and transparency controls to ease privacy concerns.
- Integrate mapping features into your app and mobile presence to detect nearby stores.
- Analyze clickstream data to pinpoint patterns predicting engagement with location-based messaging.
Blending digital profiles with real-world movement, location-based marketing bridges online experiences into offline environments with relevant interactions.
Inventory Optimization with Predictive Intelligence
Inventory optimization is key for profitable eCommerce. Excess stock ties up working capital while stockouts lead to missed revenue. Predictive inventory management via machine learning provides more precision.
By scrutinizing past demand patterns, pricing fluctuations, seasonal spikes, events impacting sales, and even local weather forecasts, predictive algorithms forecast product demand. This data-driven approach to inventory planning minimizes risk.
AI-enabled inventory management delivers advantages like:
- Reduced overstock situations with lowered carrying costs.
- Fewer stockouts lead to lost sales due to sell-outs.
- Optimization of safety stock levels is needed to buffer variability.
- Increased cash flow by aligning supply with predicted demand.
- Automated order recommendations customized by product.
According to research from McKinsey, predictive inventory techniques can decrease excess stock by 20-50% while lifting item availability.
Look toward data science to transform inventory decisions. Predictive intelligence provides a competitive edge for omnichannel merchants fulfilling across locations and delivery methods.
Inventory Forecasting Models
When implementing predictive inventory tools:
- Build statistical forecasting models by product and location based on historical data.
- Factor in pricing, marketing efforts, seasonality, trends, and external drivers that correlate to sales.
- Continually retrain algorithms on new data to increase predictive accuracy over time.
- Combine predictive analytics with demand sensing incorporating IoT and sensor data for real-time visibility.
- Enable automatic order recommendations but maintain human oversight for final confirmation.
With machine learning-powered inventory optimization, ecommerce merchants can improve profitability while delivering consumer-grade availability.
Intelligent Loyalty Programs for Retail
Loyalty programs incentivize repeat purchases by rewarding customers for frequent shopping and referrals. However, basic programs tracking generic point accruals often need to catch up. Intelligent loyalty platforms fueled by data science create deeper brand allegiance.
Sophisticated solutions build rich customer profiles synthesizing purchase activity, product affinities, marketing interactions, service tickets, browsing behavior, and more. Machine learning algorithms help cluster best buyers. Tiered groups then receive elevated experiences through tailored:
- Product suggestions and personalized search results
- Early access to sales, flash deals, and seasonal exclusives
- Free or discounted shipping promotions
- Birthday and loyalty status perks like bonus wallet funds
- Curated customer appreciation gifts and surprise delights
Real-time triggers monitor activity to deploy incentives precisely when consumer interest spikes to nudge additional purchases. Points earned may also unlock exclusive access to VIP shopping events.
Members feel valued through superior service and preferential treatment. In return, intelligent loyalty programs lift revenue. Offering preferential pricing and experiences to premium customers increases retention by 5x according to Bain & Company research.
Loyalty Program Optimization Approaches
When relaunching loyalty initiatives consider the following advice:
- Shift from antiquated legacy systems to modern cloud-based platforms enabling embedded machine learning for advanced automation.
- Provide tiers like platinum, gold and silver with escalating privileges to incentivize ongoing loyalty.
- Localize rewards by customer based on transaction history and product affinities rather than one-size-fits-all offers.
- Integrate loyalty capabilities across channels – email, SMS, mobile apps, online account dashboards and in-store.
- Test bonus point days, sweepstakes and referral rewards to catalyze engagement.
With AI-powered loyalty programs, brands move beyond points to true personalization. Motivate repeat purchases through data-driven customization and premium perks.
The future of eCommerce lies at the intersection of bits and atoms. As digital and physical worlds collide, retailers must embrace cutting edge innovations to stay ahead. From AI assistants to augmented reality, connected devices, and hyper-personalized experiences, opportunities abound to delight shoppers and drive revenue. By implementing these modern strategies, brands build next-generation Adobe Commerce and Magento stores ready to compete. The possibilities stretch as far as your imagination. Step into tomorrow by beginning your innovation journey today.