Project URL: http://recommend.ly
Recommend.ly is a social media project aimed to help people / SMEs to manage their Facebook presence better with a bit of automation magic. R.ly helps people discover curated content that they can either post themselves or ask recommend.ly to post on their pages at appropriate times. This is a completly free too.
Recommend.ly notes for Maya Studios / Project Breif
Product Goals
- Integrates itself into daily workflow of SMEs to manage FB Pages – drives payment
- Complements Facebookâs own insights and suggestions for Page engagement
- Demonstrates expertise on FB platform to woo Partners
Access
- Staging URL – stg.recommend.ly
- Live URL – recommend.ly
Press Release for Recommend.ly launch
- http://blog.recommend.ly/press-release-to-announce-the-launch-of-recomme…
- Includes research on Page activity using data set of over 4 million Pages
User Flows / Sitemaps
Two flowcharts include rough sitemap and user flow through website. Treat this as a draft and not necessarily final implementation.
Related product: CScore (ConversationScore)
Measures Page performance based on interactions, shares, virality and activity. Score (out of 100) is calculated daily. Like other scoring metrics (Klout, PeerIndex, etc.), it provides a common playing field to compare Pages and competitors as well as providing an overview of Page performance.
CScore should be treated as a separate product, which is integrated into Pages on Recommend.ly via an internal API. Draft mockups included.
Project Images
Project Files
recommendly_review_research.pptx
recommendly_wireframes.pdf
mindmap.zip- authority_letter_to_maya_studios.pdf