One of the advantages of conducting marketing campaigns digitally is that it makes reporting on important metrics, and gleaning insights from data more accessible.
Most marketing automation software provide an email marketing dashboard of sorts, where key reporting metrics can be overviewed and easily made sense of.
Whilst coming up with a campaign, creating and deploying it may take the majority of any marketer’s attention; staying focussed post-publication, by reviewing and analysing reports is almost as important as sending the campaign in the first place.
Analyse publication reports to see what patterns arise from data. These patterns will reveal possible theories on how to increase engagement and conversions.
For example, you may notice that although your email went out at noon, it was opened by many of your contacts in the evening. The theory you may come up with here is: we may gain increased open rates if we send our email in the evening.
The next step of course is to test your theory out.
Testing theories based off of previous campaign data takes confidence. To test a theory you have to bite the bullet and apply your theory to your next campaign.
What might that look like with the above example, “we will gain a higher open rate by sending our email in the evening”?
Simply send your next campaign in the evening, and again – analyse the results.
Is your open rate higher? Then your theory is confirmed.
You now know the best time to send an email to your specific audience: in the evening.