To personalize email or not?
Well, there is a lot of controversy around this question. Here is some list of studies:
Studies (Heerwegh et al. 2006, Experian study, 2013 ) on the topic suggest that personalizing an email results in higher response rates ( around 5-10% ). There are numerous studies on the topic - search for Email personalization studies.
Here's a quick summary of the Experian study:
Personalized emails generated six times higher transaction rates and revenue per email compared to emails that were not
Personalized promotional emails had 29% higher unique open rates and 41% higher unique click rates.
Similarly, personalized triggered emails had 25% higher unique open rates and 51% higher unique click rates.
Personalized triggered email campaigns demonstrated more than two times the transaction rates of campaigns that were not personalized.
Emails with personalized subject lines from multichannel retailers had 37% higher unique open rates compared to emails without
personalized subject lines.
Inputting the name lowers the subscription rates
Additional input field should be presented in the subscription form to obtain the name of the subscriber. But we know that the more fields that need to be filled the less the conversion rate is going to be. Therefore, to obtain the name of the subscriber comes with a price - slightly lower conversion rate. This leads to fewer people subscribing because of the more complex form.
Users sometimes put false names just to complete the form
Imagine that you send an email with the following greeting:
Some users might not want to share personal information like name. Therefore this field should be optional.
The best thing to do is to make an A/B test. Put one form which asks for the name and one which doesn't. Put 50% of the traffic to the first variation and 50% to the second. Try to track everything you can, like click through rates, conversion rate, etc. The see which of those two variants gets you the most revenue. This way you will have objective data to base your decision.
I advise you to design an A/B test because your case is unique and different to the studies outlined above. So you cannot take their data and expect it to work for you. Rely on your data.