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Recommendation-Organizing Apps

Clean the Sky - Positive Eco Trends & Breakthroughs

The 'Liist' App Organizes Notes, Maps and Photos

— September 23, 2019 — Tech
Getting recommendations from friends and family on where to visit or go when heading out on a trip is commonplace but can quickly become overwhelming, so the 'Liist' app is positioned as a way to keep everything organized.

The app works by taking notes, maps and photos into account, and intuitively organizing the information into a streamlined list that can be easily accessed. This enables users to actually keep up with all of the great recommendations that they receive without having to constantly cycle through their entire device when trying to recall where the information is.

The 'Liist' app is also focused on a peer-to-peer functionality that lets users control exactly who sees their lists instead of allowing their entire network to constantly have access.
Trend Themes
1. Peer-to-peer Recommendation Apps - An opportunity for businesses to develop apps that facilitate peer-to-peer recommendations and allow users to easily organize and access information.
2. Streamlined Information Management - The potential for businesses to create apps that automatically organize various types of information, such as notes, maps, and photos, into a single, easily accessible list.
3. Selective Sharing Functionality - A potential disruptive innovation opportunity for app developers to create platforms that give users control over who sees their lists and recommendations.
Industry Implications
1. Travel and Tourism - In the travel and tourism industry, there is room for disruptive innovation by developing recommendation-organizing apps specifically designed for travelers.
2. Hospitality - The hospitality industry can benefit from creating apps that help guests organize recommendations for local attractions, restaurants, and activities.
3. Technology and Software - The technology and software industry can seize the opportunity to create advanced recommendation-organizing apps that utilize artificial intelligence and machine learning algorithms to provide personalized suggestions to users.
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