Artificial intelligence and machine learning are the most advanced fields of innovative technology. But how can be turned into tangible benefits for your enterprise?
Machine learning grows at an incredible pace, while all major online brands have already launched their in-hoise machine-learning platforms. By using products of these corporations, we start feeling the effect of machine learning – sometimes even if we do not notice it.
Mail services employ machine learning in developing spam detection software. For social media, machine learning can be valuable in automated face recognition and selecting relevant tags. Machine learning enables search engines to define your habits and preferences and then to offer you personalized search results.
Such ways of using machine learning must be interesting and valuable to everybody, but these are not only Internet giants who can benefit from this technology. Any enterprise can apply machine learning to improve performance, enhance processes, and provide customers with higher-quality results.
The only thing that has not changed for data analysis is “garbage in, garbage out” principle. However, today’s machine learning instruments are capable of not just analyzing the available data, but also improving its quality.
Data inaccuracy and redundancy are severe challenges for any organization endeavoring to automate the internal operations. With predictive modeling techniques, machine learning algorithms improve data quality. This said, they engage the information found in order to enhance data input efficiency. Loosely speaking, it means reducing the number of inaccuracies and redundant data. Besides, this technology can automatically carry out these operations, thereby freeing human resources from routine tasks. This way resources can be involved in activities that are more engaging for employees and valuable for the company growth.
Data input is just the first step. Currently, the natural language processing technology is being developed, which is capable of analyzing a text, recognizing its content, and using obtained insights to prepare reports for the executive board and other stakeholders.
Such services as Amazon and Netflix have already been intensely employing these technologies. Customers buy, download, or watch, and then get offered other products that can be interesting or relevant. The more customers consume or purchase, the better the system can determine preferences to make appropriate offers – which will be as good as friends’ recommendations – more often. This is a great tool to use for increasing the customer service quality and, as a consequence, their loyalty.
You don’t have to be engaged in e-commerce on Amazon’s scale to profitably use this technology and reach same-level results. No matter what your activity is – clothing, insurance, SEO – machine learning will enable you to tell the appropriate and ready-to-buy people about your products and services.
There are two possible ways of how it works. First is what Netflix does (see above). In this case all existing customers take note of additional products or services that can be interesting to them. However, the second way – related to segmented market analysis – is by far more worthwhile. Here’s where machine learning enables software to directly contact the most valuable “cold” and “warm” customers via social media or email.
We have given just a few cases describing how machine learning can automate such tasks as data input, report preparation, and market analysis. Moreover, this technology allows for higher performance, speed, and cost-efficiency of operations, as well as reaching results totally unattainable for manual methods.
If you are interested in utilizing this technology, Polygant will help you integrate it into your enterprise. To evaluate the cost and time of development, please fill out the form. Out engineers will contact you shortly.