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Top apps leverage visual AI, conversational assistants, and metadata-focused creatives to boost discovery and conversions for Black Friday 2025.

As Black Friday approaches on 28 November 2025, leading retail apps are shifting from standalone AI features to comprehensive shopping ecosystems—integrating visual search, conversational agents, and optimised app-store creatives to guide shoppers from inspiration to purchase. Adobe predicts UK online holiday sales will reach significant heights this season, making even minor UX improvements critical.
AI is being seamlessly integrated into discovery, personalisation, and fulfilment. Visual search enables shoppers to find products using images; agentic assistants summarise reviews, plan purchases, and handle reordering; and app metadata, screenshots, and promotional videos clearly communicate the app’s value before installation. Together, these elements reduce friction and expedite the purchasing process.
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Temu showcases visual AI innovation with its Visual Intelligence feature on iOS 26, introduced in a recent update (version 3.97.0). Users can upload images to search for similar products, quickly discovering deals during Black Friday promotions offering up to 90% off.

Source: FoxData
App screenshots highlight promotional banners for “Black Friday Deals Now” alongside categories such as Women’s Fashion and Kitchenware, incorporating gamified elements to enhance engagement. This mobile-first approach addresses concerns about deal authenticity by prioritising transparency in reviews and incentives.
Walmart’s Sparky, a generative AI-powered assistant, exemplifies agentic commerce—managing tasks such as reordering, summarising reviews, and providing tailored recommendations.
App screenshots showcase the “Meet your new AI shopping assistant” interface, with prompts like “First free delivery as fast as one hour” and real-time tracking.

Source: FoxData
For Black Friday, Sparky offers early access for Walmart+ members starting 25 November, emphasising multi-modal inputs (text, images, audio) to integrate seamlessly into daily shopping routines.
Best Buy’s AI Gift Finder uses conversational prompts to recommend products, as seen in screenshots showing queries like “Help me find a unique Christmas gift” suggesting items such as bird feeders or binoculars under £200.

Source: FoxData
This tool, embedded within the app, focuses on discovery beyond standard categories, driving conversions during the festive shopping surge.
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To maximise the impact of these AI features, e-commerce apps are advised to strategically refine their app store metadata.
Title and Subtitle Optimisation: Incorporate AI-specific keywords such as “AI-Powered Shopping” or “Visual Intelligence Deals” in titles to enhance search rankings, while subtitles can highlight benefits like “Seamless Black Friday Finds with Smart Recommendations.”
Description Enhancements: Craft detailed, engaging descriptions that weave in AI narratives, emphasising how features like conversational assistants enhance convenience. Use bullet points to outline user benefits, such as “Upload a photo and find deals instantly,” to appeal to time-pressed shoppers.
Screenshots and Videos: Prioritise visuals that demonstrate AI in action—e.g., before-and-after search results or chatbot interactions. Videos should be concise (15-30 seconds) and focus on resolving pain points, such as effortless gift-finding, to drive downloads.
Keyword Strategy: Research high-volume terms related to Black Friday and AI (e.g., “AI gift finder Black Friday”) and integrate them naturally, avoiding overuse to maintain authenticity and comply with app store guidelines.
For expert support in implementing these optimisations, consider ASOWorld’s ASO Services, which specialise in enhancing app visibility and user acquisition through tailored strategies. Our comprehensive approach can help e-commerce apps stand out in competitive markets by aligning metadata with AI-driven trends.
๐ ASO Case Study: How an E-commerce App Reached Top 1 for ‘Black Friday’ on the App Store
Visual search requires accurate taxonomy; poor matches undermine trust. Conversational agents must avoid overpromising (e.g., instant checkout) unless fully supported. Clear privacy and data usage statements are vital to encourage adoption.
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