Artificial Intelligence is a key component in the revolution of the retail industry. However, the impact of AI and machine learning on the retail sphere isn’t limited to companies; vast data collection and advanced algorithms are shaping a new, streamlined consumer experience.
Traditionally, retailers would effectively throw out a wide net and try to catch as many potential buyers as possible. Of course, billboards, radio spots, and 30-second TV slots are very expensive—a 30-second commercial during Sunday Night Football, for example, will run companies an average of about $666,000.
With the growth of online ads, advertisers big and small had a new window into large-scale marketing. Facebook, for example, is a massive platform that can cost businesses as little as $1000 per month to advertise on. Thus, the massive influx coupled with sweeping data collection makes it more affordable and feasible for retailers to reach their targeted audience.
Of course, there are other ways that companies can use AI to optimize their marketing campaigns and break even. One such tool is trade promotion optimization, which essentially takes every constraint in a company’s promotion policy and finds a way to maximize the value of a promo. One key difference here is the importance of integration along a retailer’s processes, whether it’s in pricing or logistics, to better integrate a promotion with their image.
Regardless of strategy, implementing AI tools and algorithms is maximizing the value of advertising, and it’s clear that artificial intelligence has made advertising a whole lot more personal.
Seamless Buyer Experience
Perfect data unification mostly goes unnoticed, which means it’s working smoothly. With the sheer amount of data available and usable—order time, logistical details, product patterns, to name a few—it is both challenging and rewarding to neatly structure all of this data. While AI isn’t unique in this sphere, it made keeping track of data more organized and simpler for the retailers.
You might’ve noticed that you get an email after most (if not all) online orders, often coupled with a personalized message—perhaps a list of related items you might like. You may also receive messages or emails giving you suggestions for future purchases or notifying you about deals.
All of this is a direct result of a company structuring their consumer data (such as purchase history, preferences, and loyalty) to build a better picture of the type of consumer you are, often through machine learning algorithms. In building such a unified and transparent data system, retailers make their consumers’ experience simple, unique, and secure.
Chatbots—One For The Future
Early implementations of chatbots were of the virtual assistant variety. These mostly work through input commands to attempt to guide the user to a solution. Virtual assistants can be found en masse on Facebook Messenger, and help the user through a Q&A-based process.
AI retail chatbots, while in their infancy, could realistically revolutionize online customer support. Ever wanted to effectively find an item based on descriptions alone? North Face’s AI chatbot can help you pick out clothes based on what you’re looking for. Want to get some insight on the type of wine you should buy for tonight? Lidl’s “Margot” offers advice depending on your budget, taste, or pairings with natural speech.
Chatbots using artificial intelligence might just be a mainstay of customer service in the future; for now, they are a novel, but impressive, tool.