Friday, August 18, 2017
Affinitas GmbH. 2016 financials via
Spark Networks Files Registration Statement With SEC Over Affinitas GmbH. Merger
As filed with the U.S. Securities and Exchange Commission on August 16, 2017
Spark Networks Announces Filing of Registration Statement for Proposed Merger with Affinitas GmbH.
Match Group is 10 times bigger than Spark + Affinitas merge in revenue.
eHarmony is 2 or 3 times bigger than Spark + Affinitas merge in revenue and eHarmony has 750,000 paid subscribers and Affinitas in the range of 380,000.
EliteSingles / eDarling sites are only copycats of eHarmony.
A prospective client will not perceive eDarling / EliteSingles sites as better, superior or different than eHarmony's ones. eHarmony has about 750,000 paid subscribers and 10 million active users, which has been steady for the past five years.
eHarmony's sites are 3 times bigger in active users and revenue than EliteSingles's sites.
And worse, Affinitas GmbH. can not beat and will never beat eHarmony Inc. in United Kingdom, Australia, Canada and United States.
Compare to Affinitas GmbH. 2015 financials
Spark Networks, Inc. (NYSE American: LOV) Releases Q2 2017 Financials
eHarmony is in big war with its copycat, EliteSingles since May 2012, after former eHarmony's CEO refused to fully acquire its mother company Affinitas GmbH.
eHarmony CEO and article "The Online Dating Industry is Growing and Evolving"
eHarmony was copycatted in several countries like
the online dating sites EliteSingles in Canada, Australia, USA, UK, Chile, Mexico; eDarling in Spain, German, France, Russia;
also TeAmo in Russia is another copycat of eHarmony;
esync (eSynchrony) in Singapore,
MiMediaManzana in Colombia, Peru, Mexico, Chile, etc.,
Marrily in India
LemonSwan in Germany and other countries.
Very easy to copycat eHarmony, but very difficult to innovate: a 100 times better algorithm than eHarmony.
Online Dating sites have very big databases, in the range of 20,000,000 (twenty million) profiles, so the Big Five model or the HEXACO model are not enough for predictive purposes. That is why I suggest the 16PF5 test instead and another method to calculate similarity.