Soon it will be spring and we all know what that means – love is in the air.
And when it comes to love (or at least online dating), big data in general and customer intelligence in particular play increasingly significant roles in connecting people to their soul mates.
In the Information Age, you can find virtually anything online. This now includes true love – online dating is now a $2-billion-dollar-a-year industry.
Fill out a survey of questions, the answers are loaded into a customer database and – voila! – a computer algorithm finds your perfect match! Sounds like something out of a sci-fi movie, but there is plenty evidence that it can work: up to 33% of marriages now involve an online match.
How Online Dating Sites Leverage Data to Help Their Users Make Love Connections
Data is the lifeblood of online dating sites. So how much data is necessary to unlock the mysteries of the heart? Well, Match.com claims it has upwards of 70 terabytes. That’s a whole lot of phone numbers scribbled on bar napkins!
Of course, sites like Match.com, eHarmony, OkCupid and others are now collecting data from social media platforms, online shopping histories and credit rating agencies, as well as online behaviors such as media consumption.
The reason online matching firms use new streams of behavioral data is that they improve outcomes for users. In other words, online dating sites are showing their own customers some love by trying look for the “key” to match compatibility.
But just like their counterparts in digital marketing, brand management and marketing analytics, the online cupids and matchmakers must learn to find the most useful information to improve user experience.
According to the BBC’s take on big data dating, “there is a limit to how much data is really useful.” Explains Christian Rudder, co-founder of online dating site OkCupid:
We’ve found that the answers to some questions provide useful information, but if you just collect more data you don’t get high returns on it.
That’s true for most industries, not just online dating. As many data practitioners already know, answering the question of “Could we collect the data?” is very different than answering “Should we collect the data?” For more on how big data volumes are changing new and established industries, check out this infographic.
Ultimately, discovering the most useful matching criteria is a very complicated, scientific endeavor that likely requires one or more data scientists. Data scientists have helped figure out exactly which questions – e.g., do you like horror movies? – are the strongest indicators of potential compatibility.
According to the BBC, pioneers in the online dating space are now developing advanced analytical techniques and running algorithms:
[One such] algorithm can…suggest potential partners in the same way websites like Amazon or Netflix recommend products or movies, based on the behaviour of other customers who have bought the same products, or enjoyed the same films.
And as data scientists at UC Berkeley understand, these algorithms must take into account how people misrepresent themselves. A full 60% of online daters “reported inaccurate information” about their weight and nearly 50% did so about their height. In aggregate, they presented their incomes as being 20% higher than accurate.
In essence, these businesses are taking an analytical approach to love – taking an online version of people and translating that into an analog interaction in hopes of finding “the one.” And we thought retailers having to track online browsers as customers turning up at a bricks-and-mortar location faced a big challenge. Love may be the ultimate omni-channel experience.
Guide for Data-Driven CMOs
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