But artificial intelligence is not like a software product that shops can purchase off the market, put in and operate. The use of artificial intelligence in retail requires the use of previously-used data in order to be effective. Working with experienced analysts is an important part of building a database. These are professionals who have a strong grasp of the creation of algorithms that serve business requirements.
Benefits of Artificial Intelligence in Retail
Example: A leading retailer used AI to view product images for their e-commerce site. In the past, people manually reviewed, placed, and uploaded individual images to a content management system. This process was time-consuming and contained operator errors. Using AI, the company applied machine learning to more accurately classify product images in an automated way, resulting in fast processing times. People are still involved in image processing, but only to make decisions when the technology doesn’t know how to categorize an element. As a result, the retail business has reduced imaging costs and increased productivity so that employees can focus on achieving higher added value.
Target audience and its understanding
As companies achieve greater functional maturity with AI, they can use the technology to gain deeper insights into audience preferences and behavior across multiple channels. This is due to the fact that AI can analyze far-reaching and seemingly unrelated data sets more thoroughly and faster than technologies that cannot be self-learned. For example, SapientRazorfish used applied machine learning to dynamically predict user behavior on a leading retailer’s website. Previously, the same retailer targeted predefined user segments for products and marketing based on a set of selected and rigid rules. Using the latest in applied machine learning, the team accurately predicted the most likely department or product the visitor was looking for. The ability to dynamically predict which products are actually needed demonstrates that artificial intelligence is a definite plus in retail. Artificial intelligence in retail can also be applied to improve customer experience. For example, Staples offers its business customers the Easy Button, which allows them to quickly refill orders for office products. Pressing the “Easy” button activates the voice interface, which asks the customer what they need to change. By answering “Post-it Notes” or “blue pens,” they can replenish the main products.
5-step plan for introducing artificial intelligence into retail
Here are some initial steps to make AI in retail a new competitive asset: 1.Identify your business’s bottlenecks: reach consensus on the most important challenges and decide which ones can benefit from AI. 2. Determine the data needed to solve the problem: This means analyzing business processes that can provide immediate benefit from improving them, and determine the kind of data required to optimize the process. 3. Build a data gathering and analysis practice: this is one of the phases where data analysts may play a key role. 4. Make a model of how you’ll gather and utilize data to make improvements to the process. You should utilize your prototype to see whether you can gather and use data successfully. This means performing tasks such as running data with models and analyzing performance data. 5. Implement a prototype that manages the data needed to solve a business problem selected for AI improvement. Additionally, you can order AWS cloud consulting from us and significantly improve your online store.
