Wordfly IP Migration - successes/challenges?

After last week almost successfully being off the grid, I've now dug into this for us. Short version: I'm not happy either.

We're down quite a bit in Open Rates and I'm now working with the colleague who's managing the next campaign to figure out how to segment into separate sends. One of my main concerns at the moment is how to incorporate the suppression element re: the lower Engagement-rated people into the Tessitura side of things, as I feel it's important that the coding of constituent records, etc not be wildly misrepresentative. Almost a full 50% of the addresses for this current initiative are Gmail and I need list counts in Tessitura to have correlation to what people are actually receiving.

Will reply again if we come up with a brilliant (read: not beyond painful way) of handling this.

For what it's worth, here's what we prepped for this morning's campaign:

• Should have a list of about 23K.
• Split into three segmented campaigns for 8am deployments, each around 5K: 
  • Gmail 4 and 5 star
  • Non-Gmail 3, 4, 5 star
  • Gmail 2 star (not sent yet)
  • ...we are forgoing getting this content release notice to anyone 2 star or below

Results at the moment are that the Non-Gmail open rate is still slowly growing. As we never usually segment this way, nor watch speed of open rate growth, I can't really say how it compares to normal--except that it is still definitely way below the rate from prior campaigns about related videos.

Gmail has not yet reached inboxes--the open count is 0, even several hours in.

How we managed CRM side:

1. Set up extraction
2. Save to list
3. Import list to WF (no association to a campaign)
4. Export Data - Subscribers by List (make sure to select Engagement Rating and CRMSubscriberID)
5. Manually finagle in Excel into separate CSVs for gmail domain and for the different star ratings
6. Import each as Tessitura list
7. Use those as segments in new extraction
   1. Gmail segment of IN gmail list and HAS 5 stars; repeat for 4 stars
   2. Other star lists as suppression segments against original list of everyone we'd normally include
8. Save extraction to new lists by appropriate selection of which segments apply during each save

I'm sure there are other approaches that feel less fussy, but that got the job done without needing SQL (or DBA help).

For what it's worth, here's what we prepped for this morning's campaign:

• Should have a list of about 23K.
• Split into three segmented campaigns for 8am deployments, each around 5K: 
  • Gmail 4 and 5 star
  • Non-Gmail 3, 4, 5 star
  • Gmail 2 star (not sent yet)
  • ...we are forgoing getting this content release notice to anyone 2 star or below

Results at the moment are that the Non-Gmail open rate is still slowly growing. As we never usually segment this way, nor watch speed of open rate growth, I can't really say how it compares to normal--except that it is still definitely way below the rate from prior campaigns about related videos.

Gmail has not yet reached inboxes--the open count is 0, even several hours in.

How we managed CRM side:

1. Set up extraction
2. Save to list
3. Import list to WF (no association to a campaign)
4. Export Data - Subscribers by List (make sure to select Engagement Rating and CRMSubscriberID)
5. Manually finagle in Excel into separate CSVs for gmail domain and for the different star ratings
6. Import each as Tessitura list
7. Use those as segments in new extraction
   1. Gmail segment of IN gmail list and HAS 5 stars; repeat for 4 stars
   2. Other star lists as suppression segments against original list of everyone we'd normally include
8. Save extraction to new lists by appropriate selection of which segments apply during each save

I'm sure there are other approaches that feel less fussy, but that got the job done without needing SQL (or DBA help).