Dating with Fembots

17

October

2019

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Today, the world’s most valuable companies share a common characteristic: they all are ecosystem drivers and utilize different platform-based business models. Unlike companies with linear business models, platforms do not have to attract and satisfy just one group of customers, but at least two: consumers and producers. However, if these groups are not balanced, the platform’s value for the counterparty drops rapidly. To solve this challenge, platform companies apply different strategies. While some platforms subsidize one side by charging the other side a higher fee, as Microsoft does by offering free SDK to their producers, others decide to strengthen one side themselves. In the following, the attempt of a dating platform to strengthen its female user side by deploying chatbots is illustrated.

In 2016, LOVOO, a German dating platform with around 30 million users in different European countries at that time, was faced with heavy accusations. As internal documents revealed, the company was creating fake profiles on a large scale and using chatbots to interact with users. Fembots, chatbots designed exclusively for chatting with male users, attracted men to the platform and turned them into paying customers. The method: fembots sent positive ratings to male users who had to pay in order to find out where the rating had come from. The costs for getting this information were between a few cents and several euros. In sum, by using such fembots, the company had the potential to generate up to 75 euros per 1,000 artificial ratings, as internals suggested. Faced with a deceptive charge with a loss in the millions, the founders were arrested shortly after the leak. After a payment of 1.2 million euros, however, the investigations were discontinued and the founders were released again. Few months later in 2017, a large US competitor took over the startup for a purchase price of 65 million US dollars. Both founders left the company shortly afterwards.

To date, no statement has been issued by the company regarding the accuracy of the accusations made in 2016. The founders escaped in any case with a black eye (and a lot of money). Nevertheless, platform companies must carefully choose growth strategies to balance both sides of the platform and maintain their reputation. Especially when using new technologies, such as chatbots, ethical standards must be complied with to avoid violating the law and harming the own company. LOVOO’s attempt to artificially boost activity on the female user side with fembots to increase the value of the platform for male users failed and hurt the company. While LOVOO is still present in the market today with a new management, its market presence shrank from 17 countries before the scandal to 5 countries in 2019. In a recent interview, the CEO explained that the platform is once again suffering from fake profiles – this time, however, from externals. To address them, LOVOO uses algorithms to detect and delete such profiles to keep the value of the platform for male and female users as high as possible.

 

Sources:

Eisenmann, T., Parker, G. and Van Alstyne, M. W. (2006) Strategies for Two-Sided Markets. Harvard Business Review, 84(10), pp. 92–101. Available at: https://hbr.org/2006/10/strategies- for-two-sided-markets [Accessed 16 Oct. 2019].

Heuberger, S. (2019) „Wir standen kurz davor, alles zu verlieren“, sagt der Lovoo-CEO. Gründerszene. Business. [online] Available at: https://www.gruenderszene.de/business/interview-lovoo-florian-braunchschweig [Accessed 16 Oct. 2019].

Rixecker, K. (2015) Fake-Profile statt Seelenpartner: Wie Lovoo seine Nutzer verarscht haben soll. T3n. Digitale Wirtschaft. [online] Available at: https://t3n.de/news/chatbots-lovoo-dating-app-641521/ [Accessed 16 Oct. 2019].

The Local (2016) Police raid premises of popular Berlin dating app. [online] Available at: https://www.thelocal.de/20160608/police-arrest-founders-of-popular-berlin-dating-app-lovoo [Accessed 16 Oct. 2019].

 

 

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Brain-machine interface: brain data at the horizon

25

September

2019

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In the age of information goods, consumer knowledge is essential and can give companies an edge over their competitors. Product differentiation, price discrimination or advertising personalization are just some of the reasons why online businesses seek to extract value from consumer data. Looking at the way consumer data is collected online, means have become much more sophisticated over the last 25 years.

During the ’90s, companies were looking at user queries and click streams to gain insights about consumers’ search behavior. In addition, personalized discounts or registration walls, e.g. for accessing free articles from online newspapers, provided a limited amount of demographic information (Shapiro and Varian, 1998). Today, analytics tools like Google Analytics or Hotjar visualize the click, movement and scrolling behavior of website users and analyze the conversation funnel of entire websites. In-built feedback polls or simple online surveys provide fast and inexpensive qualitative consumer data. Further, smart home devices like Google Home or Amazon Echo constantly listen to their environments, thereby collecting large amounts of personal data (which, however, is only used to improve the software, manufacturers claim).

These examples show the many possibilities of collecting and analyzing consumer data nowadays.
But what’s next?

A glimpse into the neurosciences industry can give us a foretaste of what might be possible in the future. The magic word is: Brain-machine interface. A brain-machine interface (BMI) is a device that allows the user to interact with computers solely through brain activity. Futurists envision to directly connect the human brain to computers to share data and increase brain performance, but also to create a flow from the outside world into our brain.

To date, research is still at an early stage and the first implants have been used mainly in medicine, for example to restore hearing or improve sight. However, a growing number of Silicon Valley companies such as BrainGate, Kernel or Neuralink, whose main investor Elon Musk invested $100m in 2018, are on the rise and have high goals. In an interview in July 2019, Musks described his intention to ultimately achieve a kind of symbiosis with AI, which would give humans the opportunity to keep up with AI (Chandler, 2019). Another well-known company in this field of research is Facebook. The social network announced in 2017 that the organization is working on a brain-typing technology that will allow people to post messages regardless of what they are doing at that moment (Corbyn, 2019).

Although still far away, the vision and the ultimate goal of these companies is clear: connecting users constantly to the Internet. This not only creates many opportunities for companies and individuals, but also raises a number of ethical and legal concerns. Once brain activity can be successfully decoded into brain data, companies like Facebook or Amazon will have access to unique personal data they could only dream of before. If we fail to control and protect our brain data in such a scenario, perfect price discrimination might be the consequence. In addition, desired products are being advertised to us and are at our fingertips or, more precisely, at our braintips at all times.

 

 

Sources:
– Shapiro, C., Varian, H. (1998) Pricing Information. In Information Rules: A Strategic Guide to the Network Economy. Cambridge, MA: Harvard Business School Press.
– Chandler, S. (2019) Brain-Computer Interfaces And Mind Control Move One Step Closer To Becoming Reality. Forbes. Retrieved 25 September 2019, from https://www.forbes.com/sites/simonchandler/2019/09/24/brain-computer-interfaces-and-mind-control-move-one-step-closer-to-becoming-reality/#753aa96732fb
– Corbyn, Z. (2019) Are brain implants the future of thinking? The Guardian. Retrieved 25 September 2019, from https://www.theguardian.com/science/2019/sep/22/brain-computer-interface-implants-neuralink-braingate-elon-musk

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