I was wondering we have a number of campaigns that does some data management. The way I have been testing locally on my machine is as follows. I have a check if the lead has an expected field. If they do I check if they have a primary job field related to their job title (it’s like a grouping as such). If they do not I assign them that primary job and then remove them from the campaign. if they already have the field assigned i remove them from the campaign.
I know that when our campaign update runs they will be added back to the campaign as we have set that leads can restart the campaign. I am wondering if this will cause too much extra processing especially as the segment has 20K plus leads at the moment, and it can grow.
I am wondering is this the sort of thing others are doing as part of their data management
can you maybe create segments based on your 2 criterias?
Otherwise it can be really problematic if you run the campaign over and over again.
I had a chat with the head of marketing today about what they wanted to achieve and propesed a solution for them which he is very happy with. Essentially the same as i described above but without all those remove from campaign action. We only have one if they do not meet any of the criteria.
Please check condition in campaign that if that field is empty then remove contact from the campaign.
I recently had the issue Joey is speaking about.
I added a “Remove from this Campaign” action inside the campaign, which was based on a segment.
As the contacts were still in the segment, they were added back to the campaign (by the cron, which runs each minute).
My campaign-conditions were heading the contact right to the same action “Remove from this Campaign”.
In 20 hours my mautic database grew > 6Gb (from 430Mb to 7Gb).
There were campaign_lead_event_log and lead_event_log that were full with actions of that campaign.
I had to solve it trough MySQL-commands with the use of ChatGBT.
The tutorial of Joey was for me as a guide: The great Mautic weight control – Joey Keller