More data is being collected and processed than ever before, revolutionizing the way business works. Companies are using advanced data analytics to gain a competitive advantage in their respective markets and are constantly changing their business models as the technologies used for data analytics evolve. It profoundly affects the economy as we know it, creating ripple effects that change the global economy and even society as a whole.
While the impact of advanced data analytics using machine learning and artificial intelligence is a broad topic, we can at least get a glimpse of how AI and ML-based software has transformed business analytics and what we can expect from AI in terms of future analytics.
With the help of machine learning-based software, companies can process vast amounts of historical and real-time data to make highly accurate forecasts and predictions. In this way, companies can optimize their pricing strategy and supply chain management. They have data-driven pricing recommendations that give them an accurate price range for the products they sell, as well as forecasts that allow them to be better prepared for changes in demand. ML-based pricing tool software has proven to be faster and more accurate than traditional methods, which are more or less a guessing game involving tedious data gathering and price crawling.
This sophisticated software excels not only in speed and accuracy, but also in the perspective of determining optimal price ranges and demand forecasts. Category managers usually take the time to set prices for individual items, which can lead to unwanted side effects such as price cannibalization, as changing the price of one item affects the demand for the other items being sold. In addition, trying to account for product and price elasticity is extremely difficult, and the important question of how to match supply and demand for such products often remains unanswered.
ML-based pricing software can take these factors into account and offer recommendations with a company’s entire product portfolio in mind, meaning their recommendations are truly optimized for the company as a whole. Since artificial intelligence takes over the entire data collection and analysis process (which is a very complex multi-step process), human error can be completely avoided when using advanced analysis software.
We can expect this AI based pricing software to get faster and more advanced with time. The longer companies use these technologies, the more precisely they adapt to the unique goals and needs of each company that uses them. We can also expect the predictive capabilities of ML-based pricing software to continue to advance, enabling businesses to predict consumer demand and other critical factors affecting price optimization, supply chain management and more. A big area of interest in which companies are looking to apply advanced analytics is consumer behavior, so we can expect to see more AI bots talking to ecommerce stores and other AI applications in the way we shop in the future.
The fact is, AI has changed the way we do business analytics. The real question is how companies will adapt to these changes and whether they can adapt quickly enough to survive in this new machine-driven world.