Artificial intelligence is the current buzzword in the digital world and everyone is trying to figure out how to leverage this new tech, as well as determine its true meaning. The retail industry is no exception, and although it was lagging behind others, such as the finance or telecommunications sectors, it’s catching up fast as the entry barriers for new technologies are fairly low in this area. The market is highly competitive, and every new advantage quickly pays off for the provider and the retailer. In today's guest article from Shopware Technology Partner Nosto, experts for personalization, you can learn how AI is already put to good use in ecommerce and how you can benefit from using it in your own online shop.
How machine learning algorithms work
When it comes to ecommerce, artificial intelligence is often used in the form of machine learning. Machine Learning is a subset of AI in computer science. At a high level, algorithms are used to find patterns in data sets, which are then used to build a model. This model then solves the desired task based on new data that the algorithm has not seen before.
If we take a closer look, Machine Learning algorithms learn by trying to reduce errors. For example, let’s look at a task that tries to identify the presence of a face. The dataset has labeled images, and on the first pass of the machine learning algorithm, the results would typically be random, and might have an accuracy of 50%. From these results, the algorithm will then try to tweak the model parameters to achieve a better result, and this loop is performed multiple times. The choice of algorithm will affect how quickly the patterns are found, and thus the error rate reduces.
Leading online retailers are leveraging the power of machine learning improve the shopping experience for their customers. By deploying a personalization strategy which allows merchants to deliver the best experience to each of their customers through the use of ecommerce-specific data and machine learning algorithms, they can predict and automatically deliver the most relevant shopping experiences in real-time. This increases customer engagement and maximizes revenue potential. How? They use automated product recommendations, which are generated based on a user’s browsing history and interaction throughout the site and the predictions made from this data by the machine learning algorithms. By implementing the value of machine learning, leading brands have seen an average increase in conversion of 15%.
High data quality an important prerequisite for AI
Ecommerce businesses can therefore use predictive analyses via machine learning to create highly tailored customer journeys. For this to work well, the machine learning algorithms must be trained on the right data. Merchants should collect all data points and keep them updated to guarantee a high quality standard. Once you have evaluated the data, you can use AI-driven tools on the main pages of your online store, where AI can make the highest impact, such as the home page or checkout. After that, focus on other areas of the store.
Find out more about AI & Machine Learning and how they will transform retail in the series: Demystifying AI: The On-Demand Training Series.