Reuters obtained internal Meta data on what happened after Zuckerberg cut 8,000 workers and moved 7,000 into AI roles. AI-generated code changes jumped 220%. New features reaching users only rose 36%. Major incidents spiked 40%. Time spent firefighting those incidents up 70%. Employee sentiment dropped from 74% to 55% favorable. Hours before the first round of layoffs went out, Zuckerberg quietly cancelled the second round that was planned for November.
Hedgie@hedgieMarkets
This is an odd one that I'm going to put down to perhaps being a bit lazy [reusing an add originally developed for an EU country, and/or poor copy editing before it was released.
First off, the email image quotes prices in euros [I'm in the UK, we use pounds]. Hmmm, I thought, that might be a problem [ie it could be illegal as 25 euros is worth less than 25 pounds, so if the prices are in pounds there could be a case for 'bait-and-switch'].
So I clicked on the link to check - and got this ...
Yep, the prices were in pounds - but they were from £14.99, not £24.99.
So the email message could have highlighted prices that were significantly lower - and so might have increased responses.
Update: Less than an hour later I got the same email but with the lead price in pounds not euros. But the landing page still had lower prices than the from headline.
The numbers on this don't surprise me - but I would raise the issue of how little emphasis is given to the landing page. In my opinion, if you get everything else right, but the landing page wrong everything fails.
This message from sustainable fashion brand Spilt Milk reflects the nature of the organization ... it helps the unsubscriber leave with a fond memory of the business.
If you've read any of my books, you will know that I use em dashes a lot.
OK, I appreciate that this is about the use of [so-called] martech - but this headline seems to be introducing a brand new idea to business and marketing. Is this another example of marketing jobs being taken by tech folk?
I recently read a ‘paper’ on buyer behaviour and the impact of ai on that behaviour. One of the key questions was: ‘how often do you use ‘generative AI?’ Okay, hands up, how many of you can explain the difference between ai, generative ai and agentic ai? If you can, well done. If you can’t, how could you answer this question.
Unless respondents had to define generative ai before answering - possible, but likely(?) - any findings drawn from the resulting data are deeply flawed. By deeply flawed, I mean useless.
Unless, of course, the organisation doing the research is selling AI services and so might be biased in its conclusions.
I think it’s safe to assume that these failures wouldn’t have happened if ai had not been used?
