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Date: 20. February 2017

EHarmony: Using Machine Learning to Find Love
The online dating agency is taking things up a step!

Consider a dating site without photos. This was eHarmony’s reality at the beginning when they started 16 years ago. Singles would write a dating profile and fill out questions on a questionnaire. They would then look at their matches, however were unable to see what the other people looked like.

The site naturally improved over the years by adding photos and ensuring that the interface became easier to navigate. Free mobile dating apps (such as Bumble and Tinder) have nonetheless been attracting users away from the site… and this is of course not a good thing for the operators.

"People do end up on those sites looking for relationships, and we see that as our challenge,"Grant Langston, eHarmony’s CEO, told Fortune.com.

These days, according to Langston, users are likely to be interested in “swipe friendly” dating apps due to the cost-effectiveness and easiness that they offer. However, Tinder and Bumble (according to him) have nothing on the 16 years worth of rich and complex data that the platform has gathered. In stark contrast to location-based dating apps, matches on eHarmony are determined thanks to a minimal, slimmed-down version of their questionnaire – the original one that is!

EHarmony and Machine Learning

Now, users only have to answers 150 questions. There is often a completion rate of 80% (which does mean that many people are actually interested. Along with this high rate there are many members who will also go for the monthly subscription to the site.

The most interesting thing, however, is what is done with the data by the site. Demographic information (location, gender, age) as well as psychological details (habits, likes, interests) and even behavioural data (what actions are taken by users on the site) are all collected by eHarmony. A research team also investigates couples who met up through the site, and in-house psychologists and scientists give this information to machine learning algorithms in order to help match people who are compatible.

"That data lets us optimize the site and the process for a number of variables," Langston says. "We are about relationships, and we track the quality of the relationships we make."

Source: Fortune.com

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