A consumer does some Christmas shopping on Amazon – a variety of items – toys, clothing, small electronics, etc. Within seconds, while he is still adding items to his cart, he is provided recommendations for additional purchases, with the message, “Other customers who have bought this have also bought…” And when that same consumer returns at a future date, further recommendations are waiting for him.
How does this happen? It’s a matter of the use of AI in marketing and retail. The use of AI has permeated the retail advertising industry – and it is allowing companies/businesses to reap competitive edges over those not using it.
Here are just eight examples of how retailers use AI in their advertising campaigns.
Personalized Recommendations/Segmentation
The above example of AI use by Amazon is just the tip of the iceberg. AI is used to cluster customers based upon their purchasing behaviors, their demographics, and other profile information which is “out there” for big data efforts to compile.
If you are a Netflix user, for example, you will receive movie recommendations; if you have looked at products via Facebook ads, you know what shows up in your news feed – more of those product offerings.
This is all a part of the ability of AI to segment audiences far more precisely and certainly much faster than could ever be done manually.
Data Analysis
AI is the technology that allows businesses to gather oceans of data from all over the web and to organize it based upon specific business questions. A bank, for example, can collect data on loan products and consumer behaviors relative to those products. It can then use AI to predict the types of loan products that will be most attractive to which types of customers. This allows the development of new loan products and marketing those products to consumers who meet the demographic profiles for each of them, even down to the times of the year that they should be marketed.
Product/Service Searches
This was addressed somewhat above, with the example of Amazon. But it goes further than just product recommendations. When consumers conduct searches via Google, Bing, or, yes, Amazon, AI algorithms make product searching smarter. Even voice searches are smarter, because of the natural language processing and semantic search capabilities built into these algorithms Coupled with machine learning, text and voice searches both provide better results for consumers.
An additional early but promising search feature is “visual.” A consumer may be shopping and take a picture of a clothing item s/he likes and conduct a search for like items. AI can be then pull up similar items from various retailers, including prices, that allow a consumer more choices. It’s called image recognition, and it holds great promise for retailers.
Social Listening
AI can now gather data about individual consumer product interest and sentiment about specific products on social media. It can then churn that data and prepare reports to companies, not only so that they can target individual consumers, but also so that they can get information about sentiment surrounding a product. This allows them to address issues early on and take a proactive approach to fix those issues.
Pricing
What will the market bear in terms of pricing, based upon consumer demographics, season, etc.? There’s a reason why airline and hotel rates vary throughout the year. This is nothing new. But AI has now allowed retailers in the travel industry to gather data that will allow better pricing. Airbnb uses AI to recommend rental charges to its registrants, for example. It can also be used to predict when discounts or special pricing will be more attractive and to which customers those will be most attractive. Again, it allows highly targeted marketing.
Predicting Demand
Using AI to gather and churn data about previous sales by a company and its competitors, and then asking AI to make predictions about future demand, time of demand, etc. will allow companies to make smarter decisions about production and inventory. Consumers are not happy when they order a product only to be told that it is on “backorder” because it is out of stock.
AI and AR
This is perhaps one of the most exciting aspects for retailers, as the power of AI is being recognized and used to provide amazing shopping experiences. It is based on AI visual recognition of its physical surroundings to provide AR experiences. Home Depot, for example, allows consumers to select a wall paint color and superimpose that color on their walls to see if they like it. H&M clothing allows visitors to virtually try on clothing before making a purchase. Eye ware retailers now let consumers try on glass frames and make their selections before coming in for an exam and purchase.
Chatbots
Infused with natural language processing and machine learning, AI is providing customers with faster and more accurate service experiences. They can ask questions about a product, get an issue resolved, and even receive recommendations for other or additional products/services. Tacobot takes customer orders for pickup, but also provides other food choice options based upon what the customer has actually ordered.
Not the End
These eight uses for AI in marketing and retail are just the tip of the iceberg as the technology develops and becomes far more sophisticated. Retailers must stay op top of these technologies as they are developed if they want to remain competitive.