Tharawat (Pronounced as Sher-aa-wat)
The Tharawat Family Business Forum [TFBF], an independent membership association platform, is specifically developed to fuel the growth of family businesses in MENA [Middle East and North Africa] region.
In 2016, Thawarat launched its 1st knowledge and innovation hub for family businesses in the MENA region.
With regular interaction taking place with over 700 family business members, across the Middle East and North Africa region, the platform is built on four fundamental principles in helping family businesses manage challenge.
- Networking amongst family businesses (peer-to-peer exchange)
- Encouraging members to share challenges
- Engaging with experts
- Creating and Sharing relevant content with the regional and global business community
Tharawat Case Study Challenges
With a vast communication platform as this, Thawarat’s current engagement model lacked certain aspects, which they found to be crucial and relevant for overall growth.
Lack of personalization, though there is an overall relevance, the platform lacked that personalized touch to make the platform relevant to individuals on a daily/weekly basis.
Found it difficult to define and quantify benefits of individuals
Existing framework was not providing enough scope to scale, improve insight, and create meaningful impact on each individual – leading to a Catch 22 situation
Not able to attract sponsors
Requirement and Features
To build a powerful mobile app, which offers:
- Personalized content [news] based on topic of interests from worldwide
- Ability to choose their network and engage with them without having the need to go through Tharawat
- Framework for Ad Hoc meetings & ability to identify each individual by their ‘current location’
- Personal preferences and interest from business perspective
- Receive updates from Tharawat based on their topic of interests
- Listing of events, conferences and webinars
Our approach and solution
Considering the scale of the platform, and the specific requirements, we implemented certain methodologies to tackle the challenge and accomplish the tasks.
Getting personalized content for users was one of the challenges. We scraped articles from various sources and then we tagged it to deliver them only to the relevant users. This relevancy tracking was quite challenging, which also turned out to be a computing-heavy process. In order to accomplish this, we used task batching system called Spark.
At the initial release of the app, there will be human intervention for publishing content to users for error correction and analysis.