Saudi Arabia faced a swift economic growth and societal transformation under Vision 2030. This offers a unique opportunity to track emerging trends in the region, which will ultimately pave the way for new business and investment possibilities. This paper explores how AI and social media analytics can identify and track trends across sectors such as construction, food and beverage, tourism, technology, and entertainment thereby helping the businesses make informed decisions. By leveraging a tailored AI-driven methodology, we analyzed millions of social media posts each month, classifying discussions and calculating scores to track the trends. The approach not only uncovered the emerging trends but also shows diminishing trends. Our methodology is able to predict the emergence and growth of trends by utilizing social media data. This approach has potential for adaptation in other regions. Ultimately, our findings highlight how ongoing, AI-powered trend analysis can enable more effective, data-informed business and development strategies in an increasingly dynamic environment.

The intersections of marketing with artificial intelligence (AI) technology have opened up fascinating opportunities for marketers of all stripes. Stridently, AI has been making incessant roads into social media marketing, and rightly so. As the number of social media users rises year after year, social media companies are always jostling for capturing revenues. Companies of different hues, big and small, thus have shifted dollars on social media networks for marketing campaigns aimed at driving customer engagement. Why do Marketers need to Embrace AI in Social Media with Open Hands?

First of all, social media have a huge impact on our lives. With more than 2.5 billion users worldwide, this is not really up for debate. Data extracted from social media is used for all sorts of purposes from building recommender systems for products, to building statistical models that affect voters and elections. Secondly, every field related to data science has its own domain-related peculiarities. For example, econometrics deals a lot with panel data, and transparent statistical model. Natural language processing requires powerful methods for feature selection and cleaning.

First, Let us understand Web Analytics, by definition "Web analytics is the measurement of data, the collection of information, analysis, and reporting of Internet data for the purposes of optimizing and understanding Web usage. Here the web usage refers to the respective business website usage data. What are all the information can be gathered from web usage data? And, how could it be leveraged for business benefits? Let us discuss these questions later in this article.

Now Let us understand social media analytics. Social media analytics is the practice of gathering data from social media websites or networks such as Facebook, Twitter, Google plus, etc. and analyzing those metrics to understand insights to make business decisions. Most often people confuses between web analytics and Social media Analytics, let us have a clear demarcation between these two. Web analytics uses the data collected directly from a particular business website and Social media analytics uses the data collected from social media networks. In general, Web Analytics tells you about your traffic levels, referral sources, bounce rate and user behaviour on your website.

In an earlier blog post on Making the Business Case for Text Analytics, I had spoken of the importance of Social Media Analytics and specifically Text Analytics within the context of Social Media.for Social Media plays a critical role in today's world in understanding, measuring and influencing the real time perception of your company and/or brand. Social Media contains a wealth of information which needs to be analyzed and understood in a broader social and demographic context including, trend identification and receiving feedback from segments beyond what the traditional marketer or customer service center is accustomed to for receiving feedback. Given the sheer volume of data and the large number of users talking (posting, tweeting, etc.) about any given topic, visualization can be used very effectively in Social Media Analytics to effectively sort through the clutter and make sense of what is being said. Visualization enabled Analytics can be used to identify the trends and key influencers that may not otherwise evident.