You want to know whether you need to read her profile to craft an eloquent essay about all the things you have in common, or if you can get away with sending a generic, cut-and-paste email to everyone. Crafting that perfect personalized email takes a lot of time.
And if you consider the fact that even with a perfect email, the likelihood of a response is fairly low, you’re going to have to send somewhere between 5 and 20 emails to get one response. If you do some research online, you’ll probably see a lot of articles written by women whining about how generic emails are such a turn off, how unromantic they are, and how no one wants to respond to them, yada, yada, yada. The question isn't, Do people prefer personalized emails to generic ones? With the help of some open source software, I set up an algorithm to randomly email women in my area and record the vital stats of each.
There’s a huge jump for nearby profiles, and a huge decrease for inactive profiles. The difference between the baseline curve and the email curve is almost imperceptible, and it’s dwarfed by the other variables that have a meaningful impact. Let me say that again in all caps so there’s no confusion, THE EMAIL JUST DOESN'T MATTER!
Now you might still be tempted to ignore these results, because hey, I’m just one guy.
The Z-Score Delta is essentially an indirect measure of how each variable affects the probability of an email response.
If you’re not familiar with statistical analysis, let me just briefly explain the numbers in the table.The “P Value” estimates how significant the analysis results are for a certain variable.One way to look at the P Value is to think of it as the likelihood that the analysis is due to coincidence. A general rule of thumb is that any variable with a P Value below 0.05 or so is considered “statistically significant.” So in the table above, Age and location (the Nearby variable) are very strong indicators of email response rate.Many online dating advice articles recommend sending the initial email on certain days of the week, but the timing didn't have any effect in my experiment.Neither did the factor that I call “delay,” which is the amount of time after a member joined the site before I sent the initial contact email.Some articles are less emotional, but also conclude that generic emails are less likely to get a response, usually using a mixture of opinion an anecdote. The question isn't even, Are people more likely to respond to personalized emails than generic ones? In an effort to optimize the online dating process, I set out to determine which factors determine whether or not a woman will respond to my email. Things like Age, Height, Location, Ethnicity, self-reported Body Type, and whether or not they were listed as “new” according to whatever criteria Match uses.No, the relevant question is much more specific: Is the increase in response likelihood gained by a personalized email over a generic email worth the time it takes to write it? Out of curiosity, I also recorded the “percent match” to see if the algorithm used by Match had any effect on whether a woman would respond to one of my emails. You can read all about the nitty gritty statistical details of the analysis in the sidebar if you’re so inclined, but first let’s just look at the results.Recent profile activity and the profile being a “new” member also are fairly strong indicators.The email text is not significant at all according to the P-Value.—You’re on or Ok Cupid, and you send out a few online dating emails to people you like. I love being able to spot the problem areas and help clients write emails that attract the right attention. More emails get answered, and more connections are made=more first dates = more relationships=happy clients (and a happy coach)! One of the services I provide for my private coaching clients is analyzing their email exchanges.