Let’s see how the love arrows that are thrown by Big Data work. Today, flirting has been converted into more of a personal data transfer and an algorithmic game. This is because, many dating apps such as Tinder are the ones that are most chosen by singles to flirt.
However, most of its users don’t really know how their personal data is treated. Smartup, a Big Data and Digital Marketing agency analyses how this virtual cupid treats digital identity and if it really has a romantic aim.
Tinder, more than a virtual cupid, the love arrows that Big Data throws.
Tinder is the dating app par excellence. Its popularity is due to it being active in more than 190 countries and that only people who make a “match” with you can chat with each other. This is of great help to the virtual cupid. Even though at first, it’s based on geolocalization services, we’ll see that in this digital love game there are many more variables to take into account.
In order to flirt in Tinder, it’s only necessary to register via Facebook or telephone number and complete the profile.
As it might happen, if we add an extra payment, we’ll have more advantages. For example, changing the location, hiding your age or knowing about possible suitors, among others.
In 2018, Tinder made more than eight hundred millions of dollars, not only from the ones aspiring to fall in love, but also from advertising revenue.
Tinder Ads
Tinder offers the advertisers the possibility to buy advertisement space thanks to its alliance with Audience Network from Facebook. Because of this, potential suitors can see ads when they use the app. These advertisements will be more personalized if they have previously registered with Facebook or if they have linked their profile with Instagram or Spotify.
Tinder makes clear that they will not share information on Facebook profiles. Only if you read their privacy policy, you’ll know that their entailment with third parties has a merely commercial end. <<We use your information to help you keep safe and to bring you advertisements that might interest you>> indicates the legal text.
Tinder makes data available for the user and it can be downloaded with the tool “Download my data”
Connections
In order to get “significate connections”, just how Tinder calls them, the app demands a series of personal data such as name, age, educational level, occupation, etc., as well as the possibility of uploading photographs or linking your profile with other social media such as Facebook, Spotify or Instagram.
Even though this data “supposedly” serves Tinder to pair related users, it is also another way that it has to access personal data for other ends such as the merely advertising ones. It’s through that data that the digital identity of a user can be known, his/her tastes and behaviour, which is something very interesting for brands.
Big Data, a new cupid for the lovers of the 21st century
This new cupid has changed arrows for Big Data technology based on product recommendation models.
<<It is founded on the basis that, as people, we can have a predictable behaviour which may be similar to our “equals” and that the number of outliers (atypical values, out of the norm) are the minority>> says the operations director of Smartup
Through the use of the app, such technology is capable of finding patters or similar behaviour based on the historical data of users. Because of this, Tinder situates suitors in a certain group and classifies them in a more refined way the more it knows about them. It proposes certain profiles based on the way that they react to its proposals.
The big challenge of Big Data would be to know if the proposed connections have really been successful outside the virtual world. Knowing this answer would be the key for algorithms to learn from the proposed pairments. Of those that have been successful and those that haven’t. In that way, it could get more accurate at the time of proposing future recommendations.
Love is not only a question of physicality and chemistry. It also involves algorithms and Big Data.
The love algorithm
A lot has been talked about the Tinder algorithm, but even today, it’s not really known how it works. Even though a series of criteria can be established in order to filter the candidates: age, sex, distance, etc., for a long time, Tinder used the Elo Score, where all users had a secret classification according to the number of likes they had received. The users that had a similar punctuation were more likely to establish a connection or get a match.
This produced inequality among the different profiles, so the paid subscription came in to solve this problem.
According to a message from Tinder, one of the more efficient ways to get relevant matches is to use the application often, as it prioritizes the most active candidates and takes into account the ones that are connected at the same time. Also, by completing your profile entirely, or linking it to social media, you allow this cupid to know about your tastes and personal interest, as well as helping initiate conversations with other profiles.
For example, if in a profile appears the word “motorbike” or a picture of it is uploaded, Tinder will search for profiles with similar tastes in the “motorbike fan world”. In the same way, it uses a tool of visual recognition to pair similar profiles according to ethnicity, physical appearances, etc.
Through the data that is shared on Tinder, the app can deduce personality, physical aspect or the behaviour of the user, something that helps other brands to offer more personalized announcements in order to sell their products and services.
This information petition that comes from apps and webpages can put into question where the user privacy is. Because of this, it’s recommended to always read the complex privacy policy in order to know if our data will be safe or will be used by third-parties.
What’s your opinion? Do you use Tinder? Are you worried about how your data is being used?
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Las flechas del amor que arroja el Big Data
Source: https://www.marketingdirecto.com/digital-general/digital/tinder-siglo-xxi-flechas-amor-arroja-big-data
