December 18, 2018
The world’s supply of data is exploding – doubling every two years. Retailers like Amazon who best exploit this booming source of knowledge are crushing the competition.
Data, however, is not useful without the proper interpretation. This is where artificial intelligence (AI) and machine learning enter the picture.
AI mimics human reasoning: it takes a series of large data sets, runs them through various algorithms such as neural networks and produces insights from the data like a statistician might.
There are two main types of AI. The first is AI that mimics things that humans do well like image or voice recognition. The second type learns to optimize complex decisions for specific problems in order to help humans make better decisions.
In retail, machine learning and AI tend to be used to personalize a customer’s shopping experience, automate and improve customer service, better manage inventory and optimize pricing.
AI knows your customer
Retail conversion rates rise significantly when the shopping experience is personalized. To do this, retailers need to know what products a customer will like, what discounts will get the customer to buy more and what prices the customer is willing to pay.
All of this information is available in the enormous stream of data a major retailer can gather. The hard part is finding the correlations within the data; that’s the job of AI.
Besides improving customer experience, the other main customer-facing use for AI in retail is chatbots. These are not just a cheap replacement for human labor; chatbots can also be a superior customer service agent because they have an abundance of customer data at their digital fingertips.
At present, chatbots may not seem that advanced—most rely on keywords to generate responses. In future, however, advances in AI will make chatbots increasingly human in their understanding and responses.
Fourteen percent of firms have already adopted AI chatbots and digital assistants, according to a 2017 survey of 500 top North American retailers by research firm BRP. And a further 32% plan to adopt this technology sometime in the next three years.
AI knows where to send inventory
With the proper data, a good machine learning algorithm can predict what customers are likely to buy. This allows retailers to keep the right items in stock and maintain lean inventories.
Evo builds exactly these types of algorithms for clients. Our inventory allocation engines start with in-depth sales forecasts, broken down by item and store location. Based on those forecasts, our inventory allocation model decides where and when to send out inventory.
As sales data come in, our algorithm constantly learns and redistributes inventory as necessary. The result is higher overall sales and lower holding and redistribution costs for our clients.
AI knows when the price is right
AI and machine learning are also responsible for what’s known as dynamic pricing—price adjustments aimed at optimizing margins or revenues. Dynamic pricing is now common practice among major retailers and therefore a necessary capability for brands to keep up with competitors.
Evo offers its clients personalized dynamic pricing algorithms that crunch data from a wide variety of sources. Our engines constantly update the impact of price changes versus baseline forecasts, ensuring that clients get timely price recommendations to optimize business goals.
AI knows brick and mortar too
A common misconception is that AI and machine learning can only benefit online retail where data is plentiful. In fact, in-store data is also growing quickly due to technology like RFID tags, shelf sensors, smart hangers and location-based retail apps.
Meanwhile, brick and mortar establishments are starting to use AI to compliment human customer service. Next time you walk into a Lowe’s you may find a retail robot directing you to a particular item or suggesting new products based on what you already have in your cart.
Nevertheless, in-store AI faces a problem online AI does not: connecting the person to their data. As businesses find new ways to get customers to “log in” to physical stores by means of facial recognition, loyalty cards and so forth, brick and mortar AI will become much more effective.
AI makes you money
AI and machine learning are quickly becoming the norm in retail. A 2017 survey of UK retailers by tech firm Qubit found that 38% of retailers use AI in their business and 48% use machine learning.
So many retailers are investing in AI and machine learning because of the huge potential profit boost from these technologies. Dynamic pricing alone can boost sales by 2%-5% and margins by 5%-10%, according to a study by McKinsey. Meanwhile around one-third of Amazon’s total sales come from AI-powered product recommendations.
The value of artificial intelligence in retail is expected to grow at a rate of 45% per year to surpass USD 8 billion by 2024, according to Global Market Insights, Inc. Smart retailers will make investments in AI now to make sure they stay ahead of the curve.
About the author
Will Freeman is a content expert at Evo.
He is a former economic journalist and part-time entrepreneur.
His interests include economic development, China, India, cryptocurrency and blockchain, and financial technology in general.