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Ello is a social network, developed by Paul Budnitz in March 2014, that was dubbed by the media as the “anti-facebook”. Ello was released in the September of 2014, with just 90 users, and prides itself on its ad-free philosophies, that extend to maintaining user anonymity and refusing to use or distribute their data. The company committed to these philosophies legally in October 2014, establishing itself as a benefit corporation. Instead of sourcing revenue from data opportunities, Ello has established brand partnerships to pursue creative solutions such as partnership with t-shirt manufacturer Threadless to produce branded merchandise (Lopez, 2014).

The platform operated with an unusual acquisition strategy upon launch, allowing users only with specific invites to join the platform. Once accepted, a user can invite ten friends to the network, which is perhaps more reflective of our real social networks. The exclusive strategy proved to be highly successful, obtaining over 1 million users and 100,000 invite requests per day in its first month after launch (Arthur, 2014). This buzz translated in to wide-spread media coverage, as journalists reported the launch of Facebook’s potential successor. As i’m sure you’re aware, this is a big label to live up to. And this, I believe, is Ello’s main problem.

When I started writing the blog, the piece was titled “Saying Goodbye To Ello”, and was a personal review on my experience with the site and my reasons for writing it off. The site is buggy, fails to incorporate media from URL links, has a complex friend system and even fails to offer private messaging functionality (Pearl, 2015). Furthermore, it’s a pretty lonely place. The sign-up initiative is great for creating an exclusive community, but it means it’s difficult – if not impossible – to find your friends on there and interact with them.

Despite all of this, I’m prepared to give it another chance. Hearing of the anti-facebook, i signed up for the site with the assumption of a social network that does things a little differently, perhaps similar to switching from Microsoft to Apple. I’m sure i’m not alone in these assumptions. The issue, however, is that this isn’t what Ello is intended to be, nor is it what it functions as.

Ello’s founders described the site as being “built specifically with creative people in mind, people who value content, with a good bit of discussion and dialogue happening around that content”. Upon reading this quote, I started to see this differently. It’s true – Ello isn’t a place where you are drowned in meme’s and selfies, it’s far more focused on creative content, which has huge implications. Ello’s “friends” aren’t supposed to reflect those that you see day to day, more it is an expression of appreciating somebodies work and interacting with them to say this. Budnitz notes this, saying that the “most remarkable thing is how positive it is” (Pearl, 2015).

Ultimately, this is a platform that is meant with a very specific type of content and people in mind, that may have received a kiss of death from the media. There are issues with the site – for example an inability to filter content according to your creative interests such as featured on Pinterest. Ello has, however, created something unique, and may become highly successful as the “beta” network adds more functionality.

If this sounds like something that interests you, comment below to ask for an invite code.

References

Arthur, C. (2014). Goodbye, Ello? Searches for new social network collapse. the Guardian. Retrieved 29 October 2015, from http://www.theguardian.com/technology/2014/oct/14/goodbye-ello-google-seacrhes-social-network

Lopez, N. (2014). Ad-Free Social Network Ello Turns to T-shirts for Revenue. The Next Web. Retrieved 29 October 2015, from http://thenextweb.com/insider/2014/11/18/ad-free-social-network-ello-turns-branded-t-shirts-revenue/

Pearl, M. (2015). Who’s Still Using Ello?. VICE. Retrieved 29 October 2015, from http://www.vice.com/en_uk/read/people-are-still-using-ello-535

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Whilst working on a recent marketing internship, my company held ambitious aims with customer acquisition and retention. Internal surveys indicated that the most satisfied customers – those with a high Net Promoter Score – referred the company to friends and, most interestingly, those friends were the ones who stuck around. This blog reflects the social media aspect of my learnings when redesigning their referral marketing program.

There is currently a significant trend indicating the uptake of referral programs across industries, with firms such as PayPal, Uber & AirBnB boasting impressive growth due to their utilisation. Research conducted, which unfortunately cannot be shared for confidentiality reasons, found that this form of word-of-mouth marketing was significantly more effective than traditional channels, both in terms of acquisition and subsequent retention. The channel is centred around the concept of social capital, which can be lost or gained through referrals. Interestingly, referrals which are perceived to have been produced as a result of financial (extrinsic) incentives damage an individuals social capital. It is important, therefore, for organisations to maximise their use of extremely satisfied customers (advocates) to refer their wider networks due to their personal experience. I will present my key learnings of referral marketing through three case studies: PayPal, Dropbox and AirBnB.

PayPal are arguably one of the first companies to utilise referral programs, and reported an initial growth of 7-10% per day. Sounds too good to be true? It was. PayPal rewarded both customers who referred friends, and the friends, with $10 cash for every sign up. The issue here, is that PayPal allowed their customers to withdrawn these incentives from their system, costing them over $20m in acquisition costs.

What PayPal Got Right: PayPal rewarded both the existing customers, and new sign-ups. The business also rewarded the customers with an “in-kind” (product related) reward.

What PayPal Did Wrong: Their referral scheme incentivised customers to sign up for the service, but not to use it. This resulted in a collection of customers who did not bring value to business.

Dropbox is a further example of referral schemes, and achieved resounding success by targeting key opinion leaders via twitter. The business also made it easy for customers to refer their friends, adding social import features such as “Invite your G-Mail contacts”, Facebook and Twitter sharing.

What Dropbox Got Right: Dropbox rewarded referring customers with more space, increasing lock-in to the product. By making it easy to share across social media, Dropbox successfully reached vitality throughout their users extended networks.

The case of AirBnB is perhaps the most sophisticated and developed program. Optimising the platform for sharing, the company also included social sharing and, on its second release, pushed promotion across all aspects of the business, its social media and opinion leaders. They also developed a “share through whatsapp” feature, allowing people to directly message their friends.

What AirBnB Got Right: Made it easy to share to all friends, and allowed customers to use their social media in the way they deemed most appropriate.

For further case studies and information, click here.

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References:

Word-of-Mouth and Referral Marketing Blog,. (2015). Referral Program Examples – An Epic List of 47 Referral Programs. Retrieved 20 October 2015, from http://www.referralcandy.com/blog/47-referral-programs/

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As of 2013, Spotify boasted an active user database of over 50m people (Spotify Press, 2013). The platform has experienced resounding success and is a key driver behind a movement towards music consumption online Saari and Eerola, 2014). There is, however, a problem. 37.5m of Spotify’s users are free users, who fail to act as a source of direct revenue for the platform. Despite failing to provide revenue to Spotify, these users incur variable costs with each song played due to royalties owed. Spotify must, therefore, find a way to increase their conversion rate of premium customers in order to reach profitability.

In response to this scenario I propose a social commerce solution, named “Spotify Tribes”. Literature has found that people are increasingly “eager to recompose their social universe” (Cova and Cova, 2002: Pp.596) and hold a primal need to interact and exchange knowledge with like-minded others (Faraj and Johnson, 2011). Whilst these needs have been shown empirically, Music-as-a-Service (MaaS) providers have failed to satisfy the market. I propose an example of this case through the following question: How do you share music with your friends?

The answer, most likely, involves you sending a URL link to digital media via a social platform. This is a very basic level of sharing, and fails to incorporate the social and self-esteem needs (Maslow, 1943) that should be incorporated within the experience.

My platform, therefore, operates as a built in functionality within the desktop’s current platform, alongside a stand-alone mobile application – very similar to that of Fb Messenger – which can be seen in the below wireframes.  The development establishes groups of users that can share music within their communities – or “tribes” – and subsequently manage this content from within. Online community literature states that communities should be formed in three states, which is mirrored in my innovations functionality: open, closed (approval required) and secret (by invitation only) (Kietzmann et al., 2011). Within these groups, there are the standard social communication features such as expressing approval via likes, commenting and reposting to other groups / streams. Drawing inspiration from Netflix, community members are able to anonymously rate submissions, enabling taste profiles to be developed for individual users and the community as a whole. Social media literature suggests that the inclusion of social tagging for content aids in user engagement (Tan et al., 2011). Communities will, therefore, be able to tag each post and produce custom playlists from community content. Recommendations are then made to the individual based on community content, in either its whole or select form.

This solution resolves Spotify’s problem of conversion by increasing the value its premium offering whilst also complementing its fit with the free service, which is empirically recognised to increase conversions (Wagner et al., 2014). Whilst the web functionality will be available to all user categories, the mobile application and ability to create a community is included in the premium membership only. Whilst this sounds like a simple, if not ambitious, solution to Spotify’s problems, an increase of just 0.5% in conversion rate would result in millions of dollars of revenue based on previous annual revenue of €747m (Sisario, 2014), reported subscription ratio (Dredge, 2014) and published user figures (Spotify Press, 2013).

References

Cova, B. and Cova, V., 2002. Tribal marketing. European Journal of Marketing, 36(5/6),

pp.595-620.

Dredge, S., 2014. Spotify’s UK revenues rose 42% in 2013 as music service turned a profit. [online] the Guardian. Available from: http://www.theguardian.com/technology/2014/oct/07/spotify-uk-revenues-2013- profit-music [Accessed 5 Jan. 2015].

Faraj, S. and Johnson, S., 2011. Network Exchange Patterns in Online Communities. Organization Science, 22(6), pp.1464-1480.

Kietzmann, J., Hermkens, K., McCarthy, I. and Silvestre, B., 2011. Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54(3), pp.241-251.

Maslow, A., 1943. A theory of human motivation. Psychological Review, 50(4), pp.370- 396.

Saari, P. and Eerola, T., 2014. Semantic Computing of Moods Based on Tags in Social Media of Music. IEEE Transactions on Knowledge and Data Engineering, 26(10), pp.2548-2560.

Sisario, B., 2014. As Music Streaming Grows, Spotify Reports Rising Revenue and a Loss. [online] Nytimes.com. Available from: http://www.nytimes.com/2014/11/26/business/spotify-discloses-revenue-but-not- its-future-plans.html?_r=0 [Accessed 5 Jan. 2015].

Spotify Press, 2013. Information. [online] Available from: https://press.spotify.com/uk/information/ [Accessed 5 Jan. 2015].

Tan, S., Bu, J., Chen, C., Xu, B., Wang, C. and He, X., 2011. Using rich social media information for music recommendation via hypergraph model. TOMCCAP, 7S(1), pp.1- 22.

Wagner, T., Benlian, A. and Hess, T., 2014. Converting freemium customers from free to premium—the role of the perceived premium fit in the case of music as a service. Electronic Markets, 24(4), pp.259-268.

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Open source projects are becoming a significant economic phenomenon, defined as “internet-based communities of software developers who voluntarily collaborate to develop software that they or their organisations need” (von Hippel & von Krogh, 2003; pp.209). My homework assignment focuses on the three key readings whilst also exploring two case studies and future applications of open source development.

von Hippel & von Krogh’s (2003) text provides a useful introduction to open source development and proposes three models which aid in the understanding of contributor motivation. The private-investment model explains the traditional format of innovation, whereby an organisation provides extrinsic incentives for individuals to produce intellectual property which is protected by the parent organisation. The collective-action model notes that individuals are motivated to contribute to community innovation developments – often creating public goods – when the market fails to provide an adequate product or solution for a need. Neither models, however, explain open source software and thus, the private-collective model is proposed. This model notes that individuals gain intrinsic benefits from contributing, such as learning, enjoyment and improved carrer prospects (for more information see Purohit, 2014).

The second paper, by Zhang & Zhu (2010), focuses on an empirical study of Chinese Wikipedia. Traditional literature (e.g. Olson, 1965; Hardin, 1971) states that as group size increases the relative importance of an individuals contribution, and thus altruism, decreases which leads to free-riding behaviour. Free-riding is where a user extracts benefits from open source development, but does not directly contribute towards the project and is a major concern of peer production projects. Subsequently, many hypothesise that free-riding is more likely to occur in large groups. Zhang & Zhu, however, noted that the contributions of non-blocked users during enforced bans in China declined by 42%. These findings are attributed due to a decline in the social benefits received from contributing when the community size is reduced, thus dominating free-riding effects.

An Interview with MySQL CEO Marten Mickos delves in to the managerial implication of open source development. Mickos states the importance of building a culture of innovation within an organisation and sourcing innovation from as many sources as possible.

For my additional reading, I researched the importance of social ties in OSS. Mallapragada, Grewa and Lilien (2012) state that by increasing a users embeddeddness (volume of input) and brokerage (novelty of input) product development time is cut by 51%. The theory is illustrated in the below model:

Using the case of Firefox, I investigated the security risks and benefits of OSS. Whilst having transparent code can make developers more vulnerable to breaches, it is found that the increased flexibility of OSS communities allows for more agile responses (Barth et al, 2011). I also drew upon the case of Fetchmail email client to illustrate that OSS adds value to all stages of the project life-cycle as users were able to quickly and thoroughly test new developments, leading to agile release.

Finally, I explored the hypothetical application of OSS in Greece, whereby the benefits of low cost sourcing of expert producers could provide economic relief to the country (Papadopolous et al., 2013)

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Barth, A., Li, S., Rubinstein, B., & Song, D. (2015). How Open Should Open Source Be?. Eprint Arxiv:1109.0507, 1-19. Retrieved from http://arxiv.org/abs/1109.0507

Hardin, R. (1971). Collective Action As An Aggregate N-prisoner’s Dilemma. Syst. Res., 16(5), 472-481. http://dx.doi.org/10.1002/bs.3830160507

Mallapragada, G., Grewal, R., & Lilien, G. (2012). User-Generated Open Source Products: Founder’s Social Capital and Time to Product Release. Marketing Science, 31(3), 474-492. http://dx.doi.org/10.1287/mksc.1110.0690

Mickos, M. (2008). The Oh-So-Practical Magic Of Open-Source Innovation. MIT Sloan Management Review, 15-19.

Olson, M. (1965). Logic of Collective Action: Public Goods and the Theory of Groups. Cambridge, Mass.: Harvard University Press.

Papadopoulos, T., Stamati, T., Nikolaidou, M., & Anagnostopoulos, D. (2013). From Open Source to Open Innovation practices: A case in the Greek context in light of the debt crisis. Technological Forecasting And Social Change, 80(6), 1232-1246. http://dx.doi.org/10.1016/j.techfore.2012.10.030

Purohit, S. (2014). #Hackademics: How Hacker Culture Is Changing Recruitment. The Huffington Post. Retrieved 15 October 2015, from http://www.huffingtonpost.com/siya-raj-purohit/hackathons-hackademics-how-hacker-culture_b_4591539.html

von Hippel, E., & von Krogh, G. (2003). Open Source Software and the ‘Private-Collective’ Innovation Model: Issues for Organization Science. SSRN Electronic Journal. http://dx.doi.org/10.2139/ssrn.1410789

Zhang, X., & Zhu, F. (2011). Group Size and Incentives to Contribute: A Natural Experiment at Chinese Wikipedia. American Economic Review, 101(4), 1601-1615. http://dx.doi.org/10.1257/aer.101.4.1601