Anyone who uses iLab and has more than 45 customers in the database needs to be aware of this new policy.
iLab is supposed to be one complete customer database to meet our needs.
Throttling emails contacts to any number smaller than our complete customer list removes a key function we rely on. The appropriate size of a recipient group is based on each message. Sometimes this is five. Sometimes this is 300.
They offered to determine the best setup for our use case and said that they would be happy to assist. We already know this. Being able to email up to the number of every customer who used any of our services in the last three years is precisely why we purchased iLab.
Even worse, we were not notified of this change so we wasted hours with their service ticketing system, where you have to wait overnight for a response. And then they lectured us on how to communicate with our customers. What they really said here is that their product cannot email more than a few people at a time and they are not interested in correcting this.
From Agilent:
Hi Michael,
As part of recent improvements to how system emails are handled, we have standardized the maximum number of recipients per message to 45. This change was made to ensure consistent delivery, better performance, and a more usable experience as message volume and platform usage continue to grow. From a practical standpoint, this brings a few benefits, as noted below:
- Keeping recipient counts within this range helps avoid delays or dropped messages, especially during peak usage.
- Messages are delivered more quickly and consistently when sent to appropriately sized recipient groups.
- Targeted notifications reduce inbox noise and make it easier for recipients to act on messages.
- This approach allows the system to scale without degrading performance for all users.
For cases where you need to notify a broader audience, we recommend using a shared distribution list or group email address, which provides the same visibility while keeping delivery reliable.
Please let us know if you would like help determining the best setup for your use case and we will be happy to assist.
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Michael Cammer
Sr. Research Scientist
NYU School of Medicine Langone Medical Center
New York NY
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