{"id":6490,"date":"2025-05-22T12:20:23","date_gmt":"2025-05-22T12:20:23","guid":{"rendered":"https:\/\/www.inoru.com\/blog\/?p=6490"},"modified":"2025-05-22T12:20:23","modified_gmt":"2025-05-22T12:20:23","slug":"ai-powered-shopping-app-brings-real-time-personalized-recommendations","status":"publish","type":"post","link":"https:\/\/www.inoru.com\/blog\/ai-powered-shopping-app-brings-real-time-personalized-recommendations\/","title":{"rendered":"AI-powered Shopping app Brings Real-Time Personalized Recommendations"},"content":{"rendered":"<p><span data-preserver-spaces=\"true\">The world of online shopping has witnessed revolutionary changes over the past decade. From simple product listings to sophisticated platforms, the evolution has been swift. However, today, we stand at the threshold of another game-changing innovation \u2014 AI-powered shopping apps that bring real-time personalized recommendations directly to users. <\/span><span data-preserver-spaces=\"true\">This article explores how <a href=\"https:\/\/www.inoru.com\/ai-development-services\">AI-powered shopping<\/a> apps <\/span><span data-preserver-spaces=\"true\">are transforming the digital commerce landscape, delivering<\/span><span data-preserver-spaces=\"true\"> highly personalized <\/span><span data-preserver-spaces=\"true\">experiences,<\/span><span data-preserver-spaces=\"true\"> and <\/span><span data-preserver-spaces=\"true\">driving<\/span><span data-preserver-spaces=\"true\"> better engagement and sales.<\/span><\/p>\n<p><span data-preserver-spaces=\"true\">It also highlights how businesses can leverage <\/span><strong><span data-preserver-spaces=\"true\">AI Development Services<\/span><\/strong><span data-preserver-spaces=\"true\"> and <\/span><strong><span data-preserver-spaces=\"true\">Build AI Software Development<\/span><\/strong><span data-preserver-spaces=\"true\"> solutions to create these intelligent applications. Finally, we touch upon the importance of partnering with a dedicated <\/span><strong><span data-preserver-spaces=\"true\">Create AI Software Development Company<\/span><\/strong><span data-preserver-spaces=\"true\"> to harness the full potential of AI-driven commerce.<\/span><\/p>\n<h2><span data-preserver-spaces=\"true\">The Shift from Traditional E-Commerce to AI-Powered Shopping Apps<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">Traditional e-commerce platforms rely heavily on search queries and basic filters, leaving consumers to navigate vast catalogs <\/span><span data-preserver-spaces=\"true\">on their own<\/span><span data-preserver-spaces=\"true\">. While this model works to an extent, it often results in choice paralysis or irrelevant product suggestions, reducing customer satisfaction.<\/span><\/p>\n<p><span data-preserver-spaces=\"true\">Enter AI-powered shopping apps \u2014 they don\u2019t just wait for users to search. Instead, they actively analyze consumer preferences, behaviors, and real-time inputs to curate personalized product recommendations. These apps create an interactive, discovery-based shopping experience that helps users find what they want faster and more intuitively.<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">How AI Enhances Online Shopping<\/span><\/h3>\n<p><span data-preserver-spaces=\"true\">AI technologies such as machine learning, natural language processing, computer vision, and advanced data analytics enable these apps to:<\/span><\/p>\n<ul>\n<li><span data-preserver-spaces=\"true\">Understand user preferences by analyzing browsing history, purchase behavior, and feedback<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Offer real-time recommendations tailored to each user\u2019s unique style, size, and interests<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Use virtual try-on features to help customers visualize products on themselves<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Predict trends and demand by analyzing large datasets across demographics and seasons<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Streamline customer journeys with conversational AI assistants and chatbots<\/span><\/li>\n<\/ul>\n<div class=\"id_bx\">\n<h4>Looking to Upgrade Your Shopping Experience?!<\/h4>\n<p><a class=\"mr_btn\" href=\"https:\/\/calendly.com\/inoru\/15min?\" rel=\"nofollow noopener\" target=\"_blank\">Schedule a Meeting!<\/a><\/p>\n<\/div>\n<p><span data-preserver-spaces=\"true\">The result is a dynamic and immersive shopping environment that blurs the line between digital and physical retail.<\/span><\/p>\n<h2><span data-preserver-spaces=\"true\">Real-Time Personalized Recommendations: The Heart of AI-powered Shopping<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">The most remarkable feature of AI-powered shopping apps is their ability to generate personalized recommendations in real-time. But what exactly makes this possible?<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">Data Collection and User Profiling<\/span><\/h3>\n<p><span data-preserver-spaces=\"true\">AI-powered apps collect vast amounts of data from user interactions, including:<\/span><\/p>\n<ul>\n<li><span data-preserver-spaces=\"true\">Search and click patterns<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Time spent on product pages<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Purchase history<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Social media preferences<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Uploaded photos or selfies for style analysis<\/span><\/li>\n<\/ul>\n<p><span data-preserver-spaces=\"true\">This data is processed using sophisticated algorithms to build detailed user profiles that capture style preferences, size, brand affinities, and <\/span><span data-preserver-spaces=\"true\">even<\/span><span data-preserver-spaces=\"true\"> mood-based choices.<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">Advanced Machine Learning Algorithms<\/span><\/h3>\n<p><span data-preserver-spaces=\"true\">Machine learning models analyze user profiles and product metadata to find patterns and similarities. They compare current user behavior with historical data from millions of other users to predict what products the shopper <\/span><span data-preserver-spaces=\"true\">is likely to<\/span><span data-preserver-spaces=\"true\"> prefer next.<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">Diffusion and Generative Models for Visual Recommendations<\/span><\/h3>\n<p><span data-preserver-spaces=\"true\">Some apps use diffusion-based AI models that generate new images or simulate how an outfit or accessory would look on the user. <\/span><span data-preserver-spaces=\"true\">This<\/span><span data-preserver-spaces=\"true\"> goes beyond simple catalog browsing \u2014 it lets users visualize themselves wearing a product before buying, boosting confidence and reducing returns.<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">Instantaneous Feedback Loop<\/span><\/h3>\n<p><span data-preserver-spaces=\"true\">Real-time personalization requires continuous feedback processing. As users engage with recommendations \u2014 liking, disliking, or purchasing products \u2014 the AI instantly updates its model to refine future suggestions.<\/span><\/p>\n<h2><span data-preserver-spaces=\"true\">Benefits of Real-Time Personalized Recommendations in Shopping Apps<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">Personalized recommendations have proven benefits for both consumers and businesses.<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">For Consumers:<\/span><\/h3>\n<ul>\n<li><strong><span data-preserver-spaces=\"true\">Enhanced Shopping Experience<\/span><\/strong><span data-preserver-spaces=\"true\">: Consumers get relevant suggestions, making the shopping journey enjoyable and less overwhelming.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Time Savings<\/span><\/strong><span data-preserver-spaces=\"true\">: The AI filters through millions of products <\/span><span data-preserver-spaces=\"true\">instantly<\/span><span data-preserver-spaces=\"true\"> to find options that fit the user\u2019s taste.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Confidence in Purchase<\/span><\/strong><span data-preserver-spaces=\"true\">: Virtual try-on features and tailored recommendations reduce uncertainty.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Discovery of New Products<\/span><\/strong><span data-preserver-spaces=\"true\">: Users find brands or styles they might never have searched for but align perfectly with their preferences.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">For Businesses:<\/span><\/h3>\n<ul>\n<li><strong><span data-preserver-spaces=\"true\">Increased Conversion Rates<\/span><\/strong><span data-preserver-spaces=\"true\">: Personalized suggestions lead to higher engagement and purchases.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Better Customer Retention<\/span><\/strong><span data-preserver-spaces=\"true\">: Tailored experiences build loyalty and repeat business.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Reduced Return Rates<\/span><\/strong><span data-preserver-spaces=\"true\">: Virtual try-ons and accurate fit recommendations help ensure satisfaction.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Actionable Insights<\/span><\/strong><span data-preserver-spaces=\"true\">: AI analytics provide insights into consumer trends and preferences to inform marketing and inventory decisions.<\/span><\/li>\n<\/ul>\n<h2><span data-preserver-spaces=\"true\">Building AI-powered Shopping Apps: The Role of AI Development Services<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">Creating an AI-powered shopping app that delivers real-time personalized recommendations requires a blend of expertise across AI, software development, and domain knowledge in retail and consumer behavior. <\/span><span data-preserver-spaces=\"true\">This<\/span><span data-preserver-spaces=\"true\"> is where specialized <\/span><strong><span data-preserver-spaces=\"true\">AI Development Services<\/span><\/strong><span data-preserver-spaces=\"true\"> come into play.<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">What Are AI Development Services?<\/span><\/h3>\n<p><span data-preserver-spaces=\"true\">AI Development Services refer to the professional support offered by AI experts to build, deploy, and maintain AI-powered applications. These services typically include:<\/span><\/p>\n<ul>\n<li><span data-preserver-spaces=\"true\">Consulting on AI strategy and use cases<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Data collection and preparation<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">AI model design and training<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Software integration and deployment<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Continuous monitoring and optimization<\/span><\/li>\n<\/ul>\n<p><span data-preserver-spaces=\"true\">Such services ensure that your AI-powered shopping app functions accurately, and<\/span> <span data-preserver-spaces=\"true\">efficiently, and evolves based on user feedback and market dynamics.<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">Why Outsource AI Development Services?<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Access to experienced AI professionals and domain experts<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Faster development cycles using proven AI frameworks and platforms<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Reduced risk with robust model validation and testing<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Cost efficiency compared to building an in-house AI team from scratch<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Scalability options to support growing user bases and data volumes<\/span><\/li>\n<\/ul>\n<h2><span data-preserver-spaces=\"true\">Steps to Build AI Software Development for Shopping Apps<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">If you\u2019re looking to <\/span><strong><span data-preserver-spaces=\"true\">Build AI Software Development<\/span><\/strong><span data-preserver-spaces=\"true\"> solutions tailored for personalized shopping experiences, consider these key steps:<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">1. Define Business Goals and Use Cases<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Identify core objectives such as increasing conversion, improving user engagement, or reducing returns.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Determine which AI features you want \u2014 e.g., personalized recommendations, virtual try-on, chatbot support.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">2. Gather and Prepare Data<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Collect user interaction data, product metadata, images, and reviews.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Clean and label data to make it usable for training AI models.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">3. Choose AI Models and Algorithms<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Select algorithms suited for recommendation systems such as collaborative filtering, content-based filtering, or hybrid models.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">For virtual try-on, explore generative models or computer vision AI.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">4. Develop the Software Architecture<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Design a modular app architecture with AI components integrated seamlessly.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Plan for real-time processing capabilities and scalability.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">5. Train and Test AI Models<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Train models on historical and current data.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Use A\/B testing to compare AI-driven recommendations against traditional methods.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">6. Deploy and Monitor<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Launch the AI-powered shopping app to target users.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Continuously monitor model performance and user feedback for improvements.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">7. Iterate and Scale<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Update AI models as new data comes in.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Expand AI features to additional product categories or devices.<\/span><\/li>\n<\/ul>\n<h2><span data-preserver-spaces=\"true\">How to Create an AI Software Development Company Focused on Retail Innovation<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">With AI-powered shopping apps gaining traction, many entrepreneurs and businesses <\/span><span data-preserver-spaces=\"true\">are keen<\/span><span data-preserver-spaces=\"true\"> to <\/span><strong><span data-preserver-spaces=\"true\">Create an AI Software Development Company<\/span><\/strong><span data-preserver-spaces=\"true\"> specializing in this niche.<\/span><\/p>\n<p><span data-preserver-spaces=\"true\">Here\u2019s how you can establish a successful AI software company focused on retail and personalized commerce:<\/span><\/p>\n<h3><span data-preserver-spaces=\"true\">1. Build a Skilled Team<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Recruit AI researchers, data scientists, and software engineers experienced in machine learning, computer vision, and mobile app development.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Include domain experts who understand retail, fashion, and consumer behavior.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">2. Develop Proprietary AI Models<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Invest in R&amp;D to create AI models tailored for shopping personalization, virtual try-ons, and consumer insights.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Stay ahead by innovating on diffusion models, generative AI, and real-time recommendation engines.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">3. Focus on Scalable Solutions<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Architect cloud-native AI platforms that can handle millions of users and products efficiently.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Ensure your solutions integrate with multiple e-commerce platforms and device types.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">4. Partner with Retailers and Brands<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Collaborate with brands and retailers to access product catalogs and customer data.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Offer white-label AI solutions for seamless integration with existing shopping apps.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">5. Prioritize Data Privacy and Ethics<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Implement strong data protection measures in line with global regulations like GDPR.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Build transparency and explainability into AI recommendations to build user trust.<\/span><\/li>\n<\/ul>\n<h3><span data-preserver-spaces=\"true\">6. Offer End-to-End AI Development Services<\/span><\/h3>\n<ul>\n<li><span data-preserver-spaces=\"true\">Provide consulting, development, deployment, and maintenance services.<\/span><\/li>\n<li><span data-preserver-spaces=\"true\">Position yourself as a trusted AI partner for retailers transforming their digital commerce.<\/span><\/li>\n<\/ul>\n<h2><span data-preserver-spaces=\"true\">Real-World Use Cases of AI-powered Shopping Apps with Personalized Recommendations<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">To better understand the impact of AI-powered shopping apps, let\u2019s look at some real-world scenarios and applications:<\/span><\/p>\n<ul>\n<li><strong><span data-preserver-spaces=\"true\">Virtual Try-On for Fashion: <\/span><\/strong><span data-preserver-spaces=\"true\">Shoppers can upload selfies and virtually try on clothes or accessories. The AI-powered app generates realistic images showing how items look to the user, eliminating uncertainty and boosting confidence.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">AI Stylists and Outfit Suggestions: <\/span><\/strong><span data-preserver-spaces=\"true\">Based on a user\u2019s wardrobe data and style preferences, the app recommends complete outfits and new clothing items that match the user\u2019s taste, occasion, and current trends.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Beauty Product Recommendations: <\/span><\/strong><span data-preserver-spaces=\"true\">Using skin tone analysis and preferences, AI apps suggest personalized skincare and makeup products, sometimes with augmented reality try-ons.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Travel Accessories and Style Matching: <\/span><\/strong><span data-preserver-spaces=\"true\">AI shopping apps extend beyond fashion, offering personalized travel essentials, accessories, and gadgets based on user profiles and travel habits.<\/span><\/li>\n<\/ul>\n<h2><span data-preserver-spaces=\"true\">Challenges and Considerations in Building AI-powered Shopping Apps<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">While AI offers incredible opportunities, it also brings challenges that developers and businesses need to address:<\/span><\/p>\n<ol>\n<li><strong><span data-preserver-spaces=\"true\">Data Quality and Quantity: <\/span><\/strong><span data-preserver-spaces=\"true\">AI models require high-quality, diverse data to perform well. Collecting and managing this data while respecting user privacy is critical.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Model Bias and Fairness: <\/span><\/strong><span data-preserver-spaces=\"true\">AI algorithms can inherit biases from training data, leading to unfair or inaccurate recommendations. Responsible AI development and continuous auditing are necessary.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Real-Time Performance: <\/span><\/strong><span data-preserver-spaces=\"true\">Delivering real-time recommendations demands optimized algorithms and scalable infrastructure.<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">User Trust and Transparency: <\/span><\/strong><span data-preserver-spaces=\"true\">Users must trust AI-generated suggestions. Providing explainable recommendations and user control over data sharing helps build confidence.<\/span><\/li>\n<\/ol>\n<h2><span data-preserver-spaces=\"true\">The Future of AI-powered Shopping Apps<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">The future promises even more advanced AI shopping experiences:<\/span><\/p>\n<ul>\n<li><strong><span data-preserver-spaces=\"true\">Multi-modal AI<\/span><\/strong><span data-preserver-spaces=\"true\"> that combines text, voice, and visual inputs for seamless interaction<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Cross-device integration<\/span><\/strong><span data-preserver-spaces=\"true\">, allowing users to shop effortlessly across phones, smart TVs, and wearables<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Hyper-personalized commerce<\/span><\/strong><span data-preserver-spaces=\"true\"> powered by AI agents that proactively discover deals and styles<\/span><\/li>\n<li><strong><span data-preserver-spaces=\"true\">Sustainability-focused AI<\/span><\/strong><span data-preserver-spaces=\"true\"> recommending eco-friendly products based on user values<\/span><\/li>\n<\/ul>\n<p><span data-preserver-spaces=\"true\">Businesses ready to embrace these innovations will thrive in the evolving retail ecosystem.<\/span><\/p>\n<h2><span data-preserver-spaces=\"true\">Conclusion<\/span><\/h2>\n<p><span data-preserver-spaces=\"true\">AI-powered shopping apps with real-time personalized recommendations are reshaping the online retail landscape. <\/span><span data-preserver-spaces=\"true\">By leveraging <\/span><span data-preserver-spaces=\"true\">the power of<\/span><span data-preserver-spaces=\"true\"> AI, businesses can deliver engaging, intuitive, and inspiring shopping experiences that delight consumers and boost revenue.<\/span><span data-preserver-spaces=\"true\">To succeed in this space,<\/span><span data-preserver-spaces=\"true\"> partnering with expert <\/span><strong><span data-preserver-spaces=\"true\">AI Development Services<\/span><\/strong><span data-preserver-spaces=\"true\"> is essential.<\/span><span data-preserver-spaces=\"true\"> Whether you want to <\/span><strong><span data-preserver-spaces=\"true\">Build AI Software Development<\/span><\/strong><span data-preserver-spaces=\"true\"> solutions in-house or collaborate with an external team, focusing on quality data, innovative AI models, and scalable software architecture is key.<\/span><\/p>\n<p><span data-preserver-spaces=\"true\">If you aspire to lead this innovation, consider how to <\/span><strong><span data-preserver-spaces=\"true\">Create an <a href=\"https:\/\/www.inoru.com\/ai-development-services\"><em>AI Software Development Company<\/em><\/a><\/span><\/strong><span data-preserver-spaces=\"true\"> that specializes in retail AI, combining technical excellence with deep market understanding. <\/span><span data-preserver-spaces=\"true\">This<\/span><span data-preserver-spaces=\"true\"> is your gateway to shaping the future of AI-driven commerce.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>The world of online shopping has witnessed revolutionary changes over the past decade. From simple product listings to sophisticated platforms, the evolution has been swift. However, today, we stand at the threshold of another game-changing innovation \u2014 AI-powered shopping apps that bring real-time personalized recommendations directly to users. This article explores how AI-powered shopping apps [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":6491,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1491],"tags":[1498],"acf":[],"_links":{"self":[{"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/posts\/6490"}],"collection":[{"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/users\/7"}],"replies":[{"embeddable":true,"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/comments?post=6490"}],"version-history":[{"count":1,"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/posts\/6490\/revisions"}],"predecessor-version":[{"id":6492,"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/posts\/6490\/revisions\/6492"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/media\/6491"}],"wp:attachment":[{"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/media?parent=6490"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/categories?post=6490"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.inoru.com\/blog\/wp-json\/wp\/v2\/tags?post=6490"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}