AI and text analysis is being incorporated into every aspect of life. On social media, entertainment, work, marketing, and sports, automation is becoming more “human.” The result is less time spent doing tedious tasks and more energy to focus on developing ideas and drafting new strategies. The following are examples of where AI and text analysis is creating an impact.
Real Estate
AI-driven market research and text analysis are making it easier to find and sell properties/ There is a significant amount of data to analyze before making a real estate investment, including the potential value of the property, market in the area, KPIs, and characteristics of the property. Getting the data together isn’t difficult, but the challenge is analyzing it to inform investment decisions.
Property managers are discovering the benefits of AI in calculating assets, finding information about a property’s environmental footprint, and updating portfolios. An AI algorithm predicts future market value by looking at recent numbers and considering other factors such as changing prices in the area, crime rates, transportation, and schools.
The number of data points required for analyzing property can be overwhelming. AI technology organizes the information, sorts of relevant points, analyze the data, and updates existing information. AI also assists in creating in-depth property analysis for clients. It also makes property management easier with automatic updates on when things should be repaired, tenant information, and price trends.
Real estate agencies and sites use chatbots to directly interact with potential buyers and sellers and collect useful information. For instance, if a visitor to a website or a social media page clicks on a link, they can immediately interact with a chatbot that answers questions and requests email addresses or Whatsapp numbers of potential buyers and sellers.
Market Research
The amount of consumer data available online is a boon to market research. However, given the sheer enormity of social media updates and reviews, gathering and analyzing this information creates a significant challenge. AI-driven market research tools take unstructured user-generated content and create actionable data.
AI and text analysis tools perform sentiment analysis, evaluating social media updates and reviews for emotional coloring, tone, and word choice. Machine learning associates certain words and phrases with emotions and gives each text a rating from very positive to very negative and in-between. These ratings are combined and compared to provide an overview of how consumers feel about a product or brand.
The advantage of AI and text analysis is that it deals with direct feedback from customers rather than second-hand data from financial reports or company-generated resources. The main focus is the customer, and information about their preferences is the most relevant information. Market forecasts attempt to predict what consumers will want. Text analytics allows customers to customers to say they want directly to companies.
Workplace
AI in the workplace is at its early stages but is poised to grow rapidly. According to a Deloitte survey, 41% of businesses replied they are using automation extensively throughout their operations. Some examples of these tasks are ones that involve simple decisions, such as customer service chatbots that respond to specific queries according to set FAQ responses.
In many cases, these automated tasks are not meant to replace the workforce. Still, they eliminate routine tasks so employees can spend their energy on tasks that require complex thinking or intricate decision making. For instance, a loan agency may use automated tools to calculate simple loans, but those that involve multiple factors are still dealt with by humans.
Sentiment analysis is also used in the workplace to gauge how employees feel about their jobs, areas where they may need assistance, and where their morale is at its highest and lowest point. Public company chats and forums can yield user-generated data that can be evaluated by the human resource department using sentiment analysis tools. Besides, responses to memos can uncover between the lines how employees really feel about a new policy or launch.
Sports
Given the affection for numbers and statistics in sports, it is a natural area for AI to flourish. The success of data-driven strategies was seen in the 20 game-winning streak of Oakland Athletics in 2002 as depicted in the film Moneyball. The team applied data-driven strategies to players’ individual statistics and, through analytical tools, positioned each player according to his attributes. The result was an overwhelming success against rivals who had much larger budgets.
AI is tremendously useful in scouting and recruitment. Statistics about players, such as the number of home runs or other performance data, can be calculated with AI tools to measure potential. AI also monitors training regimens and can personalize a diet, workout, and practice schedule suited to each player. AI uses performance indicators to evaluate how players are improving and where they need to improve.
AI and Text Analysis Are Everywhere
Smart AI technology is powering everything from the chatbot at a favorite website, communications at work, real estate investors’ calculations, and even draft picks for a favorite team. These tools aim to complete tasks more quickly and efficiently and offload monotonous jobs to automation to concentrate on the main task. Since automation saves money and time, it is being adopted rapidly and will continue to create value.