New neural network applications are changing the way businesses interact with systems and view technology. The advancement has improved the way decision makers solve problems, and make predictions. This brings increased accuracy and eliminates tediousness when carrying out most business activities.
Many online sales platforms and businesses of all sizes are incorporating this innovative technology to streamline operations and improve customer satisfaction. If you are yet to integrate this in your business, here is everything you need to know about neural networks and some innovative applications to look into.
What is a Neural Network?
You may have heard the term neural network in reference to the human brain. At a general level, neurons in your brain form networks that help with a multitude of functions. These connections help you take into account multiple pieces of information, such as sounds, patterns, colors, and more, in order to take actions and make decisions.
Artificial neural networks follow a similar concept, in that they help you synthesize lots of disparate information, or data, into a single output. But what truly differentiates neural networks is just how much information they are able to process.
To understand the neural network concept, it helps to understand machine learning, as they are interrelated concepts around the organization and processing of information. Machine Learning is a process or paradigm where an algorithm is able to “teach” itself the optimal result based on a set of data. The machine learning algorithm is able to go through the data, find correlations, and generate results on its own.
Deep learning, which is the phrase used when neural networks are utilized, is an evolution of Machine Learning that is able to come up with optimized results based on more complex data that has more variable information. The end result of this technology is that computers can now do more complicated tasks, such as driving a car or giving accurate movie recommendations.
This same deep learning technology can also be applied to help synthesize large amounts of complex data. Take customer help desk data, like surveys, chats, emails, complaints, et cetera. Neural networks can be used to organize and present this data in order for a company to better understand customer behavior, which can be used downstream to help marketers and business leaders predict how that behavior will affect future sales.
Neural Network Applications for eCommerce
Neural networks are continually developing, and more and more business leaders are realizing the potential benefits and uses of these tools. With an increasing proportion of shopping moving online, accurate data collection and organization is more critical than ever. Neural networks have proven their ability to play a large role in how these companies interface, understand, and react to their customer’s needs. Here are a few examples:
Neural Networks for Visual Searches
One of the significant challenges of running an online business is making your store as easy as possible to navigate. One of the ways to increase sales is to make it as easy as possible for users to find what they need. This is usually done via search, where the user needs to type in the right words or phrases to find the product that they need. However what about the cases where they don’t know how to describe what they want?
A tool like Google’s Cloud Vision Product Search allows retailers to build specific searches for products based on images and relies heavily on neural networks to achieve results. This can vastly improve the search experience and other elements of user interaction by helping customers find what they’re looking for without typing the exact right phrase or combination of words into the search bar.
Customer Feedback Analysis
One of the key challenges of any business venture is determining what customers’ wants and the areas that need changes. Customer feedback analysis helps you to identify buyers’ needs and frustrations. This gives you a clear insight into which areas are doing great and which ones need improvement. In return, you can improve customer satisfaction.
Many online shopping platforms provide an easily accessible area for buyers to express their feelings and thoughts on different brands through reviews. You can apply natural language processing to understand customers’ expression through texts and audio. Natural Language Processing (NLP) is a form of data analysis that helps synthesize key pieces of information from large collections of text, such as sentiment or keywords. With the use of deep learning and neural networks, we can now learn even more when it comes to NLP, with the ability to identify topics of conversation, sarcasm detection, or even correlating certain phrases with churn prediction.
Personalized Shopping Experience
Your customers should always be your top priority. You should strive to give them the best shopping experience, one that they cannot find from competitors. Make your website easy-to-understand and navigate. One of the crucial developments that artificial intelligence has is its ability to collect and analyze data to determine every shopper’s needs. By evaluating the buyers’ behavior, it can help you determine what products they love and what products they hate.
Neural networks can use a range of demographic characteristics to segment buyers into groups, based on their histories and preferences and other assorted markers. With this, you can target your products to specific individuals or groups. For example, when an individual searches for one product, they get suggestions on other related products that they might need. This is a common strategy with large storefronts like Amazon that deal with nearly all products. The stores use demographic data to determine what other people in the same area have purchased and suggest them to segmented buyers.
Initially, businesses would predict sales based on seasons and histories. Times have changed, and now they have access to advanced tools to help them forecast business performance based on specific sets of data. You no longer have to follow trends and consumers’ mood to determine the products and services that are likely to be on high demand. Neural networks allow you to gather and evaluate large sets of data to understand the specific features and predict sales based on that.
Final Thoughts on Neural Network Applications
Every business aims to increase sales, improve customer satisfaction, keep retention high, and stay ahead of trends. With the right plan, neural networks can significantly boost your sales effectiveness and retain loyal customers through improved search results, sales predictions and offering buyers personalized shopping experiences. The technology lets you process even more of your data efficiently and effectively. Implemented correctly, this will lead to downstream improvements around critical elements of your customer experience like search, feedback analysis, product recommendation, and more. This, in return, offers automation and efficiency and helps you stay ahead of competitors.
If you are wondering how you can leverage the power of neural networks and other analytics tools to benefit your business, request a demo with Yogi today!