To take a step back: A machine customer is a non-human economic actor who obtains goods and/or services in exchange for payment.
In the new Gartner book, When Machines Become Customers, authors Don Scheibenreif, distinguished VP analyst at Gartner and leader of Gartner’s research on customer experience, and Mark Raskino, distinguished VP analyst, Gartner Fellow and leader of Gartner’s CEO research, explain that machine customers will be involved in a wide range of consumer and business purchases.
In the book, they anticipate and unpack key challenges and opportunities for organisations, and how these organisations should tackle them.
“The machine customer era has already begun,” said Scheibenreif. “There are more machines with the potential to act as buyers than humans on the planet. Today, there are more than 9.7 billion installed IoT devices, including equipment monitoring, surveillance cameras, connected cars, smart lighting, tablets, smartwatches, smart speaker and connected printers. Each of these has a steadily improving ability to analyze information and make decisions. Every IoT enabled product could become a customer. In fact, Gartner predicts that by 2027 50% of people in advanced economies will have AI personal assistants working for them every day.”
The book asserts that now is the first phase of the machine customers’ evolution, which can be seen in services such as HP Instant Ink, Amazon Dash Replenishment and Tesla’s automobiles. These are examples of automatically performing limited functions as “co-customers” on the owner’s behalf. People set the rules, and the machine executes them within a specific and prescribed ecosystem. These machines are therefore “bound customers”, and they represent the first in a three-phase evolution (see Figure 1).
In the final phase, these new economic actors are “autonomous customers”. They have enough intelligence to act independently on behalf of humans with a high degree of discretion and own most of the process steps associated with a transaction.
“What the machine customers from each phase have in common is that they will make decisions differently from humans in three ways,” said Scheibenreif. “They are logical and will make decisions based on rules that may or may not be transparent. Second, they can also process large amounts of information. Lastly, machines focus on completing tasks efficiently and without emotion, and they can’t be influenced by being ‘wine and dined.’”
When Machines Become Customers is available now on Amazon.
