How AI-driven Analytics Can Improve Your Revenue

As we move further into the new decade, the world of technology seems to be bracing itself for more disruptions and transformations. Perhaps the most significant among the current array of technologies that could majorly reshape the way we work and do business in the future is Artificial Intelligence. In a 2018 report, the IT advisory giant Gartner predicted that the business value created by AI would surge to $3.9 Trillion by 2022. The report also states that innovative approaches to enhance customer experiences would become the defining aspect of business growth over this period. Therefore, enterprises that successfully integrate AI analytics to drive customer growth and retention are bound to have an edge in the future. 

Taken together, AI-driven analytics and Machine Learning can impel substantial qualitative change for businesses. Eager to capitalize on their potential, major corporations are increasingly investing in AI solutions, while SMEs lag due to a lack of vision and budget constraints. Nonetheless, we believe that small and medium businesses must embrace AI to secure their future and fuel growth in the information age. Let's take a closer look at what AI analytics is all about. 

AI analytics

Search-driven analytics, the most popular analytical approach until the emergence of AI, works by creating a repository of indexed business data that can be accessed using a single search bar. Using this information, employees can make better and faster decisions. 

Improving on this, AI-driven analytics takes more leaps forward. It presents employees with the insights they need but often do not know how to search for. Which is to say, AI helps find answers to questions that lie outside the scope of search-driven analytics and problems that have not yet been identified. It intelligently collects and processes billions of data points and synthesizes them into personalized insights and visualizations. And here's the best part: integrated with the possibilities of machine learning, AI analytics can keep Learning and improve all by itself. Or put, the more a user searches, the better the AI analytics becomes tailored to their needs.

Now let's explore how you can deploy AI-driven analytics to improve your business revenue:

Improves customer experience:

As mentioned earlier, AI-driven analytics will most successfully increase customer growth and retention in its initial years. Augmented analytics can parse vast troves of data, including past buying history, preferences, credit scores, etc., to generate insights and allow businesses to offer a highly personalized form of customer engagement. Its capacity for predictive analytics will help enterprises identify the customers most likely to buy their product, provide customized offers and optimize the efficiency of the entire sales process.

Automates the data mining process:

AI-driven analytics helps eliminate a considerable portion of the precise data extraction and cleaning processes, which data analysts would take weeks to complete. Thereby, it accelerates the process, swiftly prepares data for processing, and deploys machine learning algorithms to glean insights that would previously have been unimaginable. 

These features can massively improve an organization's automation and decision-making capabilities. It can help reduce costs and risks and enhance revenue by aiding micro-targeting, segmentation, and marketing processes. According to this Gartner report, decision automation is expected to grow to 16 percent of the global AI-derived business value by 2022, from a mere 2 percent in 2018. 

Reduce labor costs through virtual agents:

A growing number of businesses today rely on a range of AI-driven virtual agents, including chatbots and Robo advisors, to take over simple requests and tasks, which might previously have been outsourced to call centers. This way, they can lighten the workload and allow their human counterparts to focus on more complex problems. 

Virtual agents can also help with calendaring, planning, scheduling, and other administrative tasks, thereby freeing employees for jobs that can generate a higher value. This way, they develop more excellent business value, reduce human assistants, and improve revenue. Even though virtual agents accounted for 46% of global AI-derived business value in 2018, they are expected to drop 20% by 2022 as more AI tools mature.

Furthermore, businesses can also avail the services of simple cognitive AI-driven APIs that enable speech and vision analytics, text to speech translation, etc. These are easy to integrate and can markedly improve agility. However, determining the AI solutions best fit your business depends on your company's requirements, resources, and budget. More advanced tools allow for greater customization but necessitate the presence of a skilled workforce to navigate them. 

At Cogent inCIghts, we provide you the most comprehensive and customized analytics solutions that combine AI, ML, Deep Learning, and top-draw talent to deliver actionable insights that will help your business grow exponentially. To know more, you can get in touch with us at social.listening@cogentinfo.com.