Editor’s note: Monica Laury is a marketing specialist based in New York.
Artificial intelligence streamlines and improves the accuracy of business practices by putting complex information into digestible action plans. The speed at which AI operates helps to maximize revenue and build reliability, while improved accuracy optimizes brand credibility to improve external opportunities. AI integration sets businesses apart from their competitors by creating competitive advantages within various markets, and is key when organizations are pivoting their business practices to meet changing client demands. AI’s data mining abilities are particularly important because it enhances consumer interactions and sales opportunities. Below is a deeper dive into AI technology and its positive impact on modern business, as well as insights into unfiltered consumer interactions collected from data mining efforts.
Basics of AI technology
AI is constantly evolving and there are a multitude of benefits in addition to improved efficiency and accuracy. AI technology recognizes data and information to find solutions to complex problems and to reduce risk. With the assistance of a data strategist, AI is able to adapt, learn and update projected outcomes and solutions based on past experiences and new inputs. It does this by taking complex data, separating out viable information and insights and producing actionable, operational improvements. Technological advancement comes with the demand for more complex solutions, and the increased cognitive abilities of AI make decision-making processes more straightforward. This ultimately saves valuable budget space and meets impending time constraints, which continue to shrink in a fast-paced world.
Benefits of AI mining technology adaptation
Seventy-four percent of individuals participating in a recent survey consider AI to be a major game changer in transforming their respective industries, with data mining solutions among the most impactful services artificial intelligence has to offer. Mining efforts utilize machine learning, which takes complex data sets and mines through the information autonomously to find otherwise hidden insights. Businesses often start their mining efforts by analyzing data from internal company information or consumer purchasing records. The data is used to refine the business’s target market and refine its marketing to reach potential customers in new demographic categories. Data that derives from negative consumer activity such as refunds, returns and digital feedback is also important to gain a full scope of consumer interactions. Understanding pain points in a product or service and mining comprehensive data to support it helps to ultimately improve processes and assist in future focused decision-making and planning.
It is lucrative for companies to step outside of their internal operations and analyze external resources, as well. External data mined from consumer interactions helps to determine patterns and strategies customers use when purchasing products or services. Social media channels are a great place to start, as user sentiment consists of real-time data that is both relevant and consistent. Natural language processing assists with marketing efforts, developing related content on digital platforms for transparent connection with consumers to further grow consumer interaction insights.
Filtering external and internal data into automated enterprise resource planning platforms can improve financial strategies, project planning, risk management and performance management. Monitoring these core elements of business and including mined data from consumer interactions as support allows for more accurate budget projections and stronger financial health. Having the right internal AI implemented within operational strategies makes all the difference when tackling consumer-related challenges.
Monitoring future AI opportunities in business
Heading into a new decade, it is important to remain up-to-date with AI trends and future mining-related initiatives. One of the most anticipated AI improvements is predictive analytics. Predictive analytics will use patterns detected in data and engagement to determine processes prior to the manual decision process. Its predictive nature is cost-effective, reduces the likelihood of error and therefore reduces capital spent on failed initiatives. Predictive analytics will take large data sets mined from consumer patterns and use its analyses to further draw information from the data to create projections in relation to consumer trends. This will give organizations competitive power overall and give them a more in-depth view into consumer demands.
The latest wave of smart devices are also making an impact on data mining and consumer-brand interactions. Companies are better able to extract data related to buying habits to gain a better perspective on consumer behavior. This allows for more streamlined production and relevant product offerings, and creates more accurate forecasting for future operational goals. Utilizing big data from smart devices also helps to improve marketing and advertising of new or current products, creating stronger brand exposure and consumer connection.
Transforming business
These are just a handful of the AI trends and improvements happening in the new year that will continue to transform the business world. Artificial intelligence can impact business for the better when the right strategy, tools and planning are put in place. Be sure to take these ideas into consideration to ready your business for 2020.