Is your business ready for the domination of artificial intelligence within your market? More likely than not, this process has already begun, and machine learning-based software is both enhancing and changing the companies who accept these advanced analytics technologies into their business models.
Artificial Intelligence and Big Data is Changing Businesses
More data is being collected and processed than ever before, and it is revolutionizing how businesses work. Companies are using advanced data analytics ( https://searchbusinessanalytics.techtarget.com/definition/advanced-analytics) to gain a competitive edge in their respective markets, continuously reshaping their business models as the technologies used to analyze data evolves. This has serious implications on business as we know it, creating a ripple effect which is changing the global economy, and even society in general.
Though the implications of advanced data analytics using machine learning and artificial intelligence is a broad subject on its own, we can at least take a look at how AI and ML-based software is already changing business analytics currently, and what we may expect from AI regarding analytics in the future.
AI and Machine Learning in Business Analytics
Using ML-based software, companies are able to process massive amounts of both historical and real-time data to make highly accurate predictions and forecasts. This allows businesses to optimize their pricing strategy and supply chain management. They have data-driven pricing recommendations providing them accurate price ranges for their products being sold, as well as forecasts allowing them to better prepare for changes in demand. ML-based pricing tool software has been proven to be both faster and more accurate than traditional methods, which were more-or-less and educated guessing game involving tedious data collection and price crawling (https://competera.net/solutions/by-need/price-crawling-software).
Not only is this advanced software superior in regards to speed and accuracy, but also in terms of the perspective from which it determines optimal price ranges and demand predictions. Typically, category managers would take the time to price items individually, which can lead to unwanted side effects such as price cannibalization, as changing the price of one item affects the demand for others being sold. Additionally, trying to consider the elasticity of products and their prices is extremely difficult, and important questions regarding how to match the supply and demand of such products often went unanswered.
ML-based pricing software can consider these factors, and offer recommendations considering a company’s entire product portfolio, meaning their recommendations are truly optimized for the business as a whole. Additionally, as artificial intelligence takes over the entire process of data collection and analysis (which on its own is a very complex process involving multiple steps), human error can be avoided entirely when using advanced analytics software.
The Future Potential of AI in Analytics
As it stands, this advanced software is allowing companies to have a more flexible strategy. On the other hand, businesses are practically being forced to adapt to the rapidly changing market, which in itself has become more fast-paced and flexible because of artificial intelligence. Whether businesses using AI (such as these) changed the market, or the market required the change of business analytics beforehand is a question of whether the chicken or the egg came first. Either way, businesses stand to benefit more than they do to suffer from being pushed towards changing their business models to accommodate advanced ML-based analytics technologies. We can expect these AI-powered pricing software to become even faster and more advanced over time. More specifically, the longer businesses use these technologies, the more fine-tuned they will become to the unique objectives and needs of each company utilizing them. We can also expect the forecasting abilities of ML-based pricing software to become more advanced, allowing businesses to predict consumer demand and other important factors which affect price optimization, supply chain management, and more. One large area of interest which businesses are eager to apply advanced analytics is regarding consumer behavior, so we can expect to be chatting with more AI bots on eCommerce stores, and seeing other applications of AI in the way we shop in the future.
The fact of the matter is, artificial intelligence has already changed how we conduct business analytics. The real question is how businesses will adapt to these changes, and if they can adapt quickly enough to survive in this new, machine-driven world.