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Crowd Analyzer, is an online social media monitoring platform that offers users a variety of tools that monitor people's feelings about their brand through sentiment analysis. This enables companies to generate improved customer insights or understand why a particular campaign failed to achieve its target. Likewise, the service can even be used to uncover people’s sentiments in regard to a competitor’s brand.

Crowd Analyzer supports Arabic sentiment analysis, and can recognize and understand the different dialects.

The company was founded by all of CEO Ahmed Saad, CTO Bahaa Galal, Chief Communications Officer Rooda AlNeama, and CMO Mustafa Othman. Each of the founding, albeit their young age, boast an impressive academic and entrepreneurial careers.

The 4 Musketeers

Ahmed, who holds a bachelor degree in Engineering from Ain Shams University, had already founded an IT services startup 5 years ago and possesses four years of experience in project management and account management in multinational companies such as Arcelormittal and Schindler. Bahaa, a fellow engineering graduate from Ain Shams, had served as CTO to Dare’n’Deal and Wuzzuf, both of which got acquired for a total sum of 20 million Egyptian pounds. Bahaa is the brain behind the platform’s natural language processing algorithm for the platform.

Rooda graduated from Carnegie Mellon University with a Bachelor’s degree in Business Administration, and is currently an MBA Candidate at University of Liverpool majoring in Emerging markets. She’s also founded 2 startups and writes for Sail e-Magazine, an Emirati youth focused publication. Finally, Mustafa is the current Head of Digital Marketing at Dubizzle. He is also a cofounder of ENOVA digital marketing and advertising agency.

This idea for Crowd Analyzer was inspired by a discussion that took place between between Ahmed and Bahaa around big data where Bahaa, who has natural language processing experience, mentioned creating an algorithm that understands Arabic. They took the idea to Startup Weekend Giza and won best demo.

They then evolved the idea and incorporated the social dimension. That decision was made social media’s strong growth in the region in mind, Arabic social media in particular.

“Being interested in social media and empowering brands in the region, the rest of the team came on board.  Mustafa with his background in social media management, and Rooda’s background with her MBA and knowledge of the region.  Understanding the huge influx of information coming from social media is what interested us most in enriching this information so that others find it useful,” explains Ahmed Saad.

Ahmed went on to stress that companies, brands and marketing agencies struggle to better understand customer characteristics and attitudes and normally spend a lot of money on market research in order to gain customer insights, all while people’s opinions and thoughts are publicly available and free on the social web. Obviously though, manually collecting and analyzing all that data is a very hard task. “This created a need for automation tools that can collect, understand and analyze people’s opinions from the social web.”

“Crowd Analyzer API can automatically understand the relevancy of the word, delivering you what you are exactly looking for,” he continued. “You are no longer bombarded with thousands of posts that have the keyword you are looking for, we identify the posts with the meaning of the word you are looking for.”

The team is currently focusing on Arabic and English but the algorithm they built can be easily tailored to any language. They have plans to add more languages such as French and Chinese in the future.

Key Features

In addition to being able to understand Arabic along with different dialects, Crowd Analyzer also includes a location based service, Mappr, which is unique to them and cannot be found in any of the social monitoring platforms. Mappr is a visual interactive Twitter map that displays interesting users and content on a map. You could find nearby Twitter users high follower count and identify influencers, you could search for nearby tweets that contain certain keywords, all tweet from a specific location, tweeted photos from a specific location, and so on.

Ahmad was also keen to highlight the intuitive UI/UX which they created in-house after talking to many clients and made sure it was easy and clear. “Of course, data would mean very little without the enrichment we provide such as location, gender and sentiment, which allows the user to get more from the same information they are getting on social media.”

The Challenges

Ahmed identifies two challenges when it comes to working with the Arabic language: “The challenge with Arabic is that a single word can mean so many different things.  Similarly, distinguishing sentiment in a phrase is difficult depending on how a specific thing is said.  These two challenges in terms of context and sentiment were the first hurdles we needed to tackle to create a unique proposition with our product.  In English,” he continues, “sentiment is easy to detect and companies usually have names that are synonymous with their brand. In Arabic, a brand name can also be a verb, an action, a location or a noun!”

Pricing

After talking to many clients, the team was able to identify that their needs differ depending on their size and the industry the operate in. That’s why they came up with 2 different models:

• For larger organization: a subscription based model that is split into 3 categories depending on their size and needs.
  
• For SMEs and individuals: a pay per mention model that gives them the flexibility they require.
  

Looking forward, the team will keep improving the platform keeping an eye the clients’ interaction and any change in their needs. “Our ongoing commitment in ensuring that social media management is on par with the needs of the clients. This allows us to create a truly dynamic platform. Whether through adding languages, sources of information, and keeping up with new technologies.”

Crowd Analyzer was a finalist at the Startup Demo Competition during ArabNet Beirut 2014 and won 1st place.