Neural Network Applications in E-Commerce: Advantages & Disadvantages

So, in this article, we’ll dive into the definition and applications of neural networks, as well as the primary advantages and disadvantages of using neural networks in the e-commerce business.

Sounds interesting? Let’s dive right in!

What are neural networks?

Computer scientists have long been inspired by the human brain to create their own inventions. Neural networks are one such case.

In the human brain, neural networks are electrical connections made when a human being learns something new. As for artificial neural networks, their names and structures are inspired by the human brain, mimicking the way that biological neurons signal to each other.

As the figure illustrates below, artificial neural networks (ANN), usually simply called neural networks today, consist of an input layer, one or more hidden layers, and an output layer.

Today, neural networks form the base of deep learning and are a subset of machine learning.

Neural network applications in e-commerce business

Nowadays, neural networks are used in different industries with diverse applications, including facial recognition, stock market prediction, sales forecasting, social media, healthcare, weather forecasting, etc.

It is no surprise that the e-commerce industry is also using this technology and here're 4 common applications of neural networks in e-commerce:

1. Advanced site search
2. Personalization of shopping experience
3. Sales forecasting
4. Customer feedback analysis

Although the application of this innovative technology comes with a number of benefits, it also has some significant limitations. So, in the following section, let's clarify the primary advantages and disadvantages of using neural networks in e-commerce businesses.

Advantages and disadvantages of neural networks

3 advantages of neural networks

Advantage #1: The ability to learn by themselves. As the base of deep learning, neural networks are able to perform unsupervised learning and can produce outputs that are not limited to the input provided to them.

Advantage #2: The ability to work with insufficient data and information. Even if the data is incomplete or insufficient, the network can detect the error and still produce the output. That's because the entire output generation is not affected by the corruption of one or more than one neuron.

Advantage #3: The ability of parallel processing. Neural networks are capable of performing multiple tasks at a time without affecting the system performance.

However, neural networks also have some significant disadvantages that cannot be neglected.

3 disadvantages of neural networks

Disadvantage #1: The black box nature and uncertain prediction rates. Scholars often call neural networks "the black box", which points to the best-known disadvantage of neural networks. Simply put, you don't know why or how your neural networks produce a specific output. When a mistake occurs, since the feature is not human interpretable, it can be difficult or even impossible to figure out the cause of the mistake.

Disadvantage #2: Long training processes and limited data efficiency. Neural networks rely on training data to learn and improve their accuracy over time. The training process of neural networks is the focal point of determining the correct prediction of data patterns, however, it can take a long time! In fact, a successful neural network can take weeks or even months to train completely from scratch.

Disadvantage #3: Economically and computationally expensive. As mentioned above, neural networks can take longer to train and develop than traditional algorithms, so they're more computationally expensive. The long duration of development also requires resources (such as human labor) to support, so using neural networks can end up being economically costly for your business.

A better solution?

The advantages of neural networks are appealing, but the disadvantages can be pretty troublesome. So, you might wonder: Is there a better solution that embraces all the advantages while eliminating all the limitations of neural networks?

Yes, there is a more advanced AI and machine learning solution that can do so…. and it is called ClerkCore! ClerkCore differs from older personalization technologies, such as neural networks and collaborative filtering, with a better prediction rate and data efficiency. In addition, with no complicated and long training process, ClerkCore can instantaneously deliver perfect personalization from day one.

As an e-commerce business owner, do you want increased conversions, improved customer satisfaction, enhanced customer retention, and ultimately, more revenue? ClerkCore can help you achieve these! ClerkCore can boost your business growth through more personalized experiences, smarter search results, more relevant product recommendations, more targeted email campaigns, and better customer segmentations. While helping grow your business, ClerkCore also provides superior efficiency and automation, which will save your time and energy.

If you are wondering how you can leverage ClerkCore, a better personalization solution than neural networks, to benefit your e-commerce business, talk to one of our talented experts today!