Stormberry on Nostr: Three findings on how customers respond to artificial intelligence, from research ...
Three findings on how customers respond to artificial intelligence, from research summarised by MIT Sloan Management Review.
First, people avoid the chatbot even when it costs them nothing. Participants chose it only 28 per cent of the time when the wait was identical either way.
Second, and more useful, the effect is not symmetrical. Across studies with more than 82,000 participants, customers accepted a worse-than-expected offer 78.6 per cent of the time when it came from a machine, against 60.4 per cent from a person. But humans were better at delivering a better-than-expected offer, 89 per cent against 76. The explanation is that nobody reads intent into a system. There is no generosity to credit and no meanness to resent.
Third, a meta-analysis of 163 studies puts adoption down to two things: whether the customer believes the machine is capable, and how much personalisation the task needs.
That last pair is a better test than choosing by department. Before you automate anything customer-facing, sort your interactions by whether the customer expects to be recognised. Start where they do not. Keep a person where they do, and wherever you have good news to give.
Source: MIT Sloan Management Review, 2026-08-31
https://stormberry.as/ai#AI #customerexperience #automation #Stormberry
Published at
2026-09-07 12:30:29 UTCEvent JSON
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"content": "Three findings on how customers respond to artificial intelligence, from research summarised by MIT Sloan Management Review.\n\nFirst, people avoid the chatbot even when it costs them nothing. Participants chose it only 28 per cent of the time when the wait was identical either way.\n\nSecond, and more useful, the effect is not symmetrical. Across studies with more than 82,000 participants, customers accepted a worse-than-expected offer 78.6 per cent of the time when it came from a machine, against 60.4 per cent from a person. But humans were better at delivering a better-than-expected offer, 89 per cent against 76. The explanation is that nobody reads intent into a system. There is no generosity to credit and no meanness to resent.\n\nThird, a meta-analysis of 163 studies puts adoption down to two things: whether the customer believes the machine is capable, and how much personalisation the task needs.\n\nThat last pair is a better test than choosing by department. Before you automate anything customer-facing, sort your interactions by whether the customer expects to be recognised. Start where they do not. Keep a person where they do, and wherever you have good news to give.\n\nSource: MIT Sloan Management Review, 2026-08-31\n\nhttps://stormberry.as/ai\n\n#AI #customerexperience #automation #Stormberry",
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