Did you know that 422 million people across the world speak Arabic and its different dialects? That’s true. Arabic is the 5th most popular language globally, behind English, Mandarin, Hindi, and Spanish.
There are 3 commonly used forms of the Arabic language:
- Quranic or classical Arabic
- Standard (modern) Arabic
- Colloquial Arabic
However, it is estimated that there are over 30 different dialects of the Arabic language in the world.
In a recent podcast, Dr. James Piecowye and Paul Kelly discuss the concepts of Audience Intelligence. They also tackle audience surveillance and sentiment in the same context. Insights from their discussion will help us understand the evolving Arabic customer intelligence.
What is Audience Intelligence, and Why Does it Matter?
Audience Intelligence is the practice of obtaining and understanding valuable audience data and insights from multiple data points. It is an innovative approach to marketing and governance.
Analysis of this data can help individuals, governments, and brands plan and execute informed strategies based on near-accurate real-time data.
The internet is the most significant data point known to mankind yet. It is reported that we create a whopping 2.5 quintillion bytes of data every day. Google alone processes over 20 Petabytes of data daily, which includes roughly 3.5 billion searches.
People share 306 billion emails and over 500 million tweets every day.
Audience Intelligence tools like ‘Sila’ collect and analyse data from several online sources. They achieve this through not only social listening but also use other various sources of digital data and. analysis technology like Natural Language Processing (NLP) to provide ambient, unadulterated feedback.
‘Sila’ understands the 21+ major Arabic dialects spoken globally. It can process with near-accurate results:
- 94.8% Arabic sentiment
- 89.6% emotion
- Demography
- Audience segmentation
- Affinities
- Personality, among several other valuable insights
The Evolving Arabic Audience Intelligence
First, why would one care about Arabic Audience Intelligence?
Well, for starters Arabic is very popular. Secondly, GCC boasts a combined GDP of approximately $3.464 trillion. Imagine the commercial perks of growing your business across the Gulf!
We’ve established that Arabic is among the most spoken languages of the world. Unfortunately, it also remains the most undeserved language about audience intelligence. Analyzing data shared in Arabic comes with tons of challenges. This is because of the significant evolution of the language over time.
To better understand the evolution of Arabic audience intelligence. We must first understand the history and widespread forms of the Arabic language. Different dialects of Arabic are spoken across the Middle East, Northern Africa, Central and Western Asia, and some parts of China.
These different forms of the Arabic language make it difficult even for the most sophisticated AI tools to analyze data shared in the language accurately. The technology could struggle to pick on tone, meaning, and context to deliver un-distorted analysis.
For instance, ‘Aamiya’, slang or colloquial Arabic which is often used in ordinary conversations comes in many forms. The dialect varies from country to country, and sometimes town to town.
In our latest podcast series; Paul observes that there are several Arabic dialects within the same country, like Saudi Arabia, for example. Dr. James makes an interesting observation. He recounts that his students in Dubai communicate the same thing using ‘totally different words’ with their cousins in Abu Dhabi. The distance between the two cities is merely about 150 kilometers apart.
Get this – there’re over 11 words for “Love” in Arabic, each denoting the different stages of falling in love.
There are at least, 100 words for Camel in Arabic.
Now you understand how complex Arabic can sound, especially to a non-native. Of the 100% of Arabic content shared, only 30% is in Modern Standard Arabic (e.g., 70% is in dialect). This poses an exciting challenge when it comes to understanding context.
Arabic is an ancient language believed to have evolved millenniums ago. The language is quite unique that in fact, some of its sounds don’t exist in other languages.
Audience intelligence aims to understand what a target audience feels without asking them. One would think that you’d get accurate data asking a person what they felt or thought about a product or message. However, Paul clarifies that people don’t always speak the truth in formal interviews.
Audience intelligence tools can now pick up on sentiments, verbal and non-verbal cues Thanks to AI. A deeper analysis of sentiment in conversations and social media posts is also critical. It helps brands understand what people feel about their products or message.
Importance of Sentiment in Audience Intelligence
Does your target audience like your product? What are they saying about your brand? From social media posts, what do people think about your offering? Only an AI-enabled audience intelligence platform can near-accurately answer these questions.
Our audience intelligence technology, Sila, understands sentiments across several Arabic dialects with a 94.7% accuracy.
Our technology can identify consumers’ frustrations with your products or services. We can achieve this by tracking your brand’s mentions and conversations touching on it online. We then process these data to establish valuable insights, including likely future trends.
Our technology guarantees limited dilution of vocabulary and sentiment during translation. We achieve this through machine learning and natural language processing.
Natural language processing is essential because it:
- Identifies personality traits
- Identifies Consumption patterns
- Draws future consumer pattern
Paul reveals that ‘Sila’ perceives sentiment through natural language processing. The technology can crunch massive amounts of data fast, at a relatively high accuracy level. Paul adds that the technology “looks at the context of the words used.”
Context is critical, particularly when most of your data is mined through social listening. Take the Arabic language, for instance, because of the many Arabic dialects spoken in different countries. Anyone would run into the “perception and homogeneity” challenge when analyzing data shared in Arabic. “While the language is Arabic, the way the Arabic language is being used, in different countries is different,” James added.
James laments that it gets more complicated to analyse data in Arabic. This is “because you’ve got the same words with slightly different intonations and spellings. But that might be used in different contexts to say similar things.”
Paul has an even more straightforward and exciting definition of natural language processing. He terms it as the ability to understand what a person says “within the context of a broader conversation.” Sila boasts an Arabic-Native AI-enabled consumer intelligence technology that can understand “sentiments.”
Unlike other tools Sila doesn’t miss out on a lot of data packed with emotions and feelings.
Paul warns that using a standard audience intelligence technology that is not enriched with culture could be missing up to 5 times the data (conversation) being shared.
Find out more about our podcast series.
Is Audience Intelligence Borderline Audience Surveillance?
Dr. James and Paul also touch on the controversial subject of audience surveillance and intelligence. Audience intelligence heavily relies on the collection of data from multiple digital sources. The data is then analyzed to provide meaningful insights into consumer behaviour.
Paul disagrees that collecting consumer information online is borderline surveillance. He further notes that “Surveillance has a nefarious connotation, but not with language because it sort of implies that things are being watched.”
He adds that “Intelligence is about understanding. And I know that also has an infamous thing if we think about CIA or something.”
Audience intelligence is more of surveying, than surveillance. It’s anchored on getting customer feedback without really having to ask them directly. Sila, for instance, employs technology – ‘Sila’, to analyze data from multiple data points.
The technology identifies trends, societal shifts, and breaks down the information to customer opinions and thoughts.
Uses of Audience Intelligence
Audience Intelligence has tons of strategic uses in business and governance. Here are some of the popular uses in business.
Identifying Your Audience
Audience intelligence can help you identify your audience and provide valuable customer insights. The insights will inform your marketing strategy and campaigns. The technology picks on your brand’s mentions from social posts.
It does this through social media monitoring and data analysis. It identifies who is talking about your brand, what they are saying, and in what context is your brand being mentioned.
Audience Segmentation
Audience Intelligence clusters audience into:
- How individuals are “interconnected”
- Demography
- Region
- Behavior, among several other types of segmentation
Influencer Identification
Audience intelligence can help brands identify the most influential people within an audience. Businesses can then leverage on these influencers to expand their reach.
Media Planning
Understanding where you can find your audience helps businesses create feasible media budgets. This in turn improves their advertising and PR campaigns.
Social Media Targeting
You can deploy your social media marketing strategies by understanding your potential audience. This will help you to connect with your target audience effectively.
Conclusion
Audience intelligence has made audience identification and targeting easy. Sila remains a committed partner for brands looking to gain insights and penetrate the Arab-speaking world.
Our AI-enabled audience intelligence technology provides an impeccable solution towards understanding Arabic language.
Contact us TODAY to discuss how Sila can open the door to Arabic-speaking audiences for your brand.
