A home is the most expensive item most of us will ever buy. That’s why we invest so much time in negotiating the details of the purchase, often with the help of an experienced realtor. We hope for a buyer’s market—a market in which there are more sellers than buyers, giving buyers the leverage to drive low prices.
In comparison, we perceive bottled water as cheap, even though the markup on water is many times that of any house. In fact, consumers regularly pay two dollars for something that costs the manufacturer only five cents to produce, a forty-fold increase that makes water one of the most heavily marked-up products in the world.
So why don’t we bargain for water when we know the markup is so high? In large part, it’s because of this simple equation: value of negotiating = money saved – (time to negotiate x financial value of our time)
In other words, if time is money, negotiating is only worthwhile when the amount we save by bargaining down the price of something is more than the value we place on our time spent doing it.
It makes sense for someone earning the median U.S. hourly wage of $18 per hour to invest, say, 10 hours to research and negotiate five percent off the purchase of a used vehicle with an average price of $20,000. The buyer spent $180 worth of time to save $1,000.
By comparison, imagine that same person trying to negotiate a discount on a $2 bottle of water. We already know the huge markup of 40 times the cost should leave room for a win-win outcome for both parties. However, a buyer who can persuade the seller to drop the cost by 50 percent in just five minutes has still spent one-twelfth of an hour, or $1.50, to save $1.
So for now, the time it would take to haggle over most purchases makes it not worth the effort.
But, artificial intelligence (AI) intermediaries will soon change that.
What takes humans hours or minutes to do, computers can accomplish in seconds or less. Instead of taking five minutes to negotiate a deal individually, or 50 hours to organize a group to negotiate collectively, a human can give a command and let AI quickly handle the negotiations in the backgound. And, when a negligible “time to negotiate” is plugged into our equation, the result shows why AI-assisted haggling will become common for many products.
To see what that might mean for the future of customer experience, consider a recent demonstration of Google’s AI Assistant’s ability to contact a local business to schedule an appointment. The AI placed a phone call to a business that doesn’t have an online booking system, spoke to a human receptionist, responded with pauses and phrasing that mimicked human speech, and parsed the nuances and context of the receptionist’s comments to complete the transaction exactly as a person would. Now imagine eliminating humans entirely in favor of lightning-fast negotiations between and among AI intermediaries.
As more of our mundane shopping moves online, we’ll trust AI to organize more of it. Eventually, groups of personal AI intermediaries will band together to barter and buy collectively without our intervention, creating economies of scale to ensure the best deals on whatever they’re purchasing for us.
In essence, this will create temporary, virtual marketplaces where AI intermediaries cooperate with each other to meet a group of human buyers’ needs without involving them in the negotiations. This AI cooperative buying will have the benefit of numbers: 500 AI intermediaries negotiating as one will have more influence than each one negotiating individually. Just as critically, the individual AI intermediaries will be able to leverage the combined historical and real-time data from each buyer’s purchasing habits and insights as market trends to influence pricing and product availability before they begin to negotiate.
Of course, sellers could have their own AI intermediaries on the opposite side of the negotiating table, and they wouldn’t necessarily be at a disadvantage. When buyers have delegated the purchase of a low-volume, highly customized product to AI or if demand is high but supplies are limited, the buyers’ AI intermediaries may decide to compete with each other instead of join forces, thus temporarily shifting negotiating power to the sellers’ AI intermediaries instead.
Either way, expect AI cooperative buying to complete hundreds or even thousands of simultaneous, automated transactions each day, with participating AI intermediaries gathering data all the while. Sellers will need strategies to attract the attention of these ephemeral alliances and present them with winning offers before they make a choice and dissolve again.
David Jonker is lead of the Global Thought Leadership team at SAP.
Christopher Koch is editorial director of the SAP Center for Business Insight.