Some large companies, such as tech firms and large banks, are adopting AI (artificial intelligence) aggressively. As for small and medium-sized businesses, everyone is waiting for the AI technology to evolve and for AI expertise to become widely available. These companies are going to be fast followers, which is a strategy that has worked with information technology.
Yet what drives the AI technology is data, and if you are not collecting data on your clients and customers, then how are you going to adopt AI? Having data on clients, potential clients, performance, and income is what made companies like Booking.com, Rakuten, and Amazon successful. However, it’s not just data, but also the AI (Artificial Intelligence) algorithm that managed to pick up valuable strategies out of their data.
Data for Flexibility and Holistic Insights for E-Commerce
Thanks to data, e-commerce retailers can find out more about their customers’ behavior and improve demand forecasting. Which days they prefer to shop, what times they prefer to shop, which products they often buy, and the number of items they typically purchase – all this can be read from the data you collect from your customers. Data is collected without creating hierarchies and without restrictions (“data lakes”), and it’s the lack of structure in it that holds tremendous value for analytics and future adoption of AI. With this raw data, we can decide which part of it is useful and required at a precise moment.
Today, business owners typically use only 0.5% of all the data they’ve collected over the years. The rest of it remains stored in various external tools and software. With AI getting better at retrieving unstructured data and transforming it into actionable insights, e-commerce retailers will be able to unclog their data pipe.
Data and AI: Predicting Opportunities and Preventing Obstacles
The biggest drives of AI adoption are uncovering new opportunities and fixing broken systems. For example, Amazon has grown to become one of the biggest e-commerce stores in the world, with $100 billion of annual revenue. They are also a great example of AI utilization for e-commerce growth. The core aspect to their growth is showing their client options they didn’t know they needed and ensuring they always have the products they want. And they did it by using their data to build a better AI algorithm.
Through AI e-commerce and machine learning, companies can find a better approach to blend expert-driven systems (that can provide actionable feedback) and existing processes to machine learning. For example, by analyzing your buyer’s history, an AI can predict what a customer will buy next. The more a customer buys, the more accurately your system will be able to send relevant product recommendations. Data and AI can also help you decide on new products to develop or sell, which is not an easy task for e-commerce companies.
Today, it is essential to be present online and own and manage your customer data, as tomorrow your e-commerce brand will have to adopt AI in order to survive. However, your brand is what’s unique, while AI is something you should adopt. Without the data, AI cannot exist. Luckily, AI in the e-commerce landscape is not reserved solely for large enterprises with large in-house teams.
We suggest you collect, own, and manage your data with our DG1 platform that comes with FREE future upgrades. DG1 will be capable of giving you BI and AI tools in the future with no additional cost.