Blog

Online Dating Marketing: Where Data and Emotions Converge

Published: October 3, 2012

Author: Jon Fendrich


 
 
 
Managing advertising campaigns on Facebook is frequently a quantitative exercise rather than a psychological one. While predicting human behavior up front is important, being able to analyze the data can make even more impact. To understand the preferences of Facebook users, how and when they click and take downstream actions, hypotheses can be confirmed cheaply and rapidly. Facebook ads provide a rapid feedback loop by showing thousands (or even millions) of impressions in a short period of time and allowing an advertiser to make decisions based on data, rather than just intuition.
There is, however, a critical piece of the puzzle many advertisers miss. Tying campaign data back into theories about human thoughts, feelings, and emotions can allow the next round(s) of ad optimization to be smarter and more effective.
What better place to examine the convergence of Facebook data and human emotion than the world of online romance?! Using data collected from campaigns Ampush has run for multiple dating sites over the past two years, we find the following breakdown of registrations broken out by day of the week, normalized for varying interest levels:
online dating trends
Even a cursory observation shows an obvious pattern. One can infer that interest in online dating wanes as the weekend approaches. On the weekend, many people go out socially and therefore have their best chance at finding romance Friday and Saturday nights. Those who were disappointed in their weekend dates and festivities may choose the internet as a source of potential romance when the wait until another weekend is the longest.
While segmenting by day of the week and even hour of the day may not prove fruitful for all advertisers, it should definitely be considered by any business putting time and money into a user-acquistion strategy involving Facebook ads. Use the data, but do more than that – try to interpret what the data says about its users and whether that insight can be leveraged as well.
– Jon Oberlander, Ampush

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