All posts by birgitfriemann

Be My Eyes – A whole cornucopia of crowdsourcing mechanisms

In my last blog post, I already wrote about a new application that smartly makes use of crowdsourcing to benefit all participating users creating a win-win situation combined with a nice touch of gamification. Nevertheless, in that previously described model, the main motivation for users is to convert spare time they have into cash – thus, the motivation behind using the app is clearly extrinsic.

Several scholars have investigated the different kinds of motivation behind participating in crowdsourcing communities. Rogstadius et al. (2011) find that increasing extrinsic motivation such as pay leads to a higher speed of responding and willingness to respond but not to a higher quality of the output while increasing the intrinsic motivation of doing a task (e.g. by framing it as a task where you can help others) can succeed in improving the response quality. Similarly, Pilz and Gewald (2013) compare motivating factors to join for-profit or non-profit (for-fun) crowdsourcing communities and find that extrinsic motivations are much more important to incentivize the contribution to for-profit communities.

One particularly recent example of a new business model that – in my opinion – masters the art of framing to intrinsically motivate users as well as the art of combining different crowdsourcing mechanisms to fully exploit the potential of the crowd to help, design, fix codes and fund an idea, is BeMyEyes.

BeMyEyes is a Copenhagen-based, non-profit start-up and the respective mobile application has just been launched on 15th January 2015. The idea is simple, yet powerful and simply described by the slogan: “Lend your eyes to the blind” (1). More specifically, on the two-sided platform, there are blind or visually impaired people on the one hand who need help to cope with small everyday tasks, and people who can see on the other hand who want to help.

The situation of use for the application is any everyday situation where the remaining four senses that are left to blind people are not enough to master small challenges. Popular examples are reading the expiry date on grocery items, baking a cake, or choosing the right item in the store when the form of the packages is identical. Whenever a blind person faces such a challenge where “a pair of eyes” would come in handy (2), he/ she can easily request help through the application and is connected with one of the over 200,000 helpers registered (1). The technology used is simple as well – the two users described are connected via normal video chat where the blind person directs his/ her camera towards the item in question so that the helper can describe what he/ she sees. That this idea works can be seen in a lot of praise as well as a prize the founding team has won for the most innovative idea (3,4).

What I find particularly interesting about this business model – except that it purely aims to motivate people intrinsically, which seems to work as there are considerably more helpers registered than help-seeking people at the moment (5) – is that it seems to be a toolbox of crowdsourcing mechanisms, leaving me with the impression that the founder of BeMyEyes must have taken this course (Customer-Centric Digital Commerce) at RSM before.

First of all, crowdsourcing is not only used to actually fulfill the business need of helping blind people. Instead, two other instances can be found where crowdsourcing is used at BeMyEyes: (a) the application is based on open source code and programmers around the world are kindly asked to help fixing bugs and improving the code, and (b) the app aims at helping blind people globally, thus it is possible for volunteering people around the world to help translating the app to other languages (2).

Second, looking at the initial funding of the application, we see another aspect of using the crowd – next to official funding by the Velux Foundation and the Blind Foundation in Denmark, BeMyEyes obtained additional funding through crowdfunding on IndiGoGo. As mentioned by Argawal et al. (2013), similar to crowdsourcing as explained above, funders in crowdfunding are motivated by a community feeling and by supporting ideas that they think are good and have a potential to help others. Thus, BeMyEyes not only manages to intrinsically motivate people to use the platform but also to fund it so that the idea could be transformed into a working and helping application.

Since the money of the initial funding will only last until September 2015 (2), BeMyEyes is currently thinking about a future business/ revenue model that will help to sustain the application. Currently, options under discussion are to implement a subscription-based model or to base the app on donations, which would essentially make BeMyEyes an implementer of Pay-What-You-Want (Schröder, Lüer and Sadrieh, 2015).

A final aspect that I found striking because it seems like it has been taken out of a university textbook is how BeMyEyes has also implemented a point system, where users get points for using the platform and helping others to gain reputation. Additional points can be obtained by sharing the application on different media (2), thus creating electronic Word-of-Mouth, which has the potential to reach a high number of people and thus can help the application to grow (King, Racherla and Bush, 2014).

All in all, I really like this business idea because it is exclusively non-profit and has the candid intention to help people and to make their lives easier on a daily basis. For helpers, this application offers the opportunity to help and feel useful without needing to invest a lot of effort. This way, a win-win situation is created without the need to pay anyone for it. What do you think about this business model? Would you like to be a part of this community and help others or if not, why not?

Academic References:

Agrawal, A.K., Catalini, C., & Goldfarb, A. (2013). Some simple economics of crowdfunding (No. w19133). National Bureau of Economic Research.

King, R.A., Racherla, P., & Bush, V.D. (2014). What We Know and Don’t Know About Online Word-of-Mouth: A Review and Synthesis of the Literature. Journal of Interactive Marketing, 28(3), 167-183.

Pilz, D., & Gewald, H. (2013). Does Money Matter? Motivational Factors for Participation in Paid-and Non-Profit-Crowdsourcing Communities. In Wirtschaftsinformatik (p. 37).

Rogstadius, J., Kostakos, V., Kittur, A., Smus, B., Laredo, J., & Vukovic, M. (2011). An Assessment of Intrinsic and Extrinsic Motivation on Task Performance in Crowdsourcing Markets. In ICWSM.

Schröder, M., Lüer, A., & Sadrieh, A. (2015). Pay-what-you-want or mark-off-your-own-price–A framing effect in customer-selected pricing. Journal of Behavioral and Experimental Economics.

Online References:

  1. BeMyEyes Homepage
  2. BeMyEyes FAQ
  3. Article
  4. BeMyEyes Press
  5. Article TechCrunch

Featured Image:

Screenshot from

Scavenger Hunt 2.0 – Crowdsourcing at its best with Streetspotr

Imagine yourself having a list of to-dos for the day, including a doctor appointment, grocery shopping, meeting a friend for lunch and your mother for an afternoon tea. Even though these are a number of things to be done, there will always be slack time in between where you cannot be as productive as you would like to be – and as we all know and as it was eloquently put into words by Benjamin Franklin: Time is Money.
Wouldn’t it be great if you could use your waiting time more efficiently and earn some money on the go?

Now, in a second scenario, imagine yourself to be part of a big company, selling products worldwide in thousands of retail shops, creating a massive amount of points of sale. Since you cannot be everywhere at the same time yourself to check how your products are presented in a store, whether enough items are on stock, which types of consumers buy your product etc. you would usually have to send out field workers to collect these valuable information. Unfortunately, this takes time, is very costly and to evaluate the effectiveness of a specific campaign, for example, it is vital to get timely information from various different locations to be able to adapt and improve your strategy while the campaign is still running (1).
Wouldn’t it be great to either clone yourself or have another option to have scalable workforce at the right place at the right time?

Just during the time when crowdsourcing was entering the peak of Gartner’s hype cycle, representing the market’s inflated expectations as well as the start of a mass media hype (2), Streetspotr was founded in Germany in 2011, with the beta phase ending in 2012 – a company exploiting two trends that affect almost all (IT-related) companies at the moment: crowdsourcing with the help of mobile.

Streetspotr is a platform that constitutes a two-sided market (3): On the one side, there are private users who face, for example, the first scenario described above. These individuals can download an app for their smartphone and learn about so-called microjobs (or “spots”) just in proximity of where they’re currently located. When they decide to take the job, they have a limited time frame in which they can answer questions, take photos etc. As soon as the result is accepted by the “employer”, the spotter earns a small amount of money, typically around 2-3€, which is accredited to the spotter’s PayPal account (4).
This way, otherwise wasted time can be turned into money while there is also a social and fun aspect as by now there is a real spotter community, where points and badges can be earned that show your credibility, enhance your reputation and unlock higher paid jobs over time (5).

The other side of the two-sided market is represented by businesses of any size that want to have access to near real-time information collected by a scalable workforce in an extremely cost-effective way. Via the website of Streetspotr, they can enter all different kinds of microjobs, determine a price that the spotter is paid and a time frame (4). As soon as the job is taken and executed by a spotter, Streetspotr controls the result’s quality and the “employer” gets to either accept or decline the result. This way, businesses can utilize the wisdom of the crowd without having to employ masses of field workers; instead making use of a temporal mobile workforce (6).

That this concept works has been shown in several ways by now. First, a number of 300.000 spotters (1) has ensured a critical mass, attracting more and more (and larger) businesses to use Streetspotr for the location-based microjobs they have, causing positive network effects for both sides of the market (3). Second, gamification and the community aspect, as well as the money to be earned ensure an excellent consumer engagement, where hardcore users purposefully plan routes to execute 20- 30 microjobs per day, earning a 4-digit sum of money in one year (6, 7).
Third, after winning two awards for their timely, well executed business model and the way they make use of the trend mobile, having created an “ideal mobile app” (8), Streetspotr now thinks about expanding beyond German-speaking countries to Great Britain and even the United States of America, after having received their first injection of capital in 2014 (7).
Talking about expansion, there is the idea that in addition to the co-creation model of C2B, Streetspotr is thinking about opening the platform to private consumers to occupy both sides of the two-sided market as well (C2C); in this respect, users shall be able to have others collect information on a used car they want to buy or any other information that can be found on the street (6, 9).

All in all, I think Streetspotr has managed to develop a business model that is really interesting and has a high potential – it is timely, makes use of current trends and serves the individual as well as the business side of the market, having managed to create a critical mass on both sides. Personally, I have just downloaded the app and look forward to earning some money on the go from now on.


  3. Eisenmann, T., Parker, G., & Van Alstyne, M. W. (2006). Strategies for two-sided markets. Harvard business review84 (10), 92.
  9. Saarijärvi, H., Kannan, P. K., & Kuusela, H. (2013). Value co-creation: theoretical approaches and practical implications. European Business Review,25(1), 6-19
  10. Featured Image: Streetspotr Facebook

Are cross-platform social recommender systems the future?

(This blog post is based on the research article ‘A social recommender mechanism for e-commerce: Combining similarity, trust, and relationship’ by Li, Wu and Lai, 2013)

In a world where there is not only a massive selection of different products but also the internet that enables us to theoretically choose among all those offerings without the high search costs that have hindered us from an informed choice in the past, the problem of information overload is a challenge for both the consumers and the companies offering those products (Li, Kauffman, Van Heck, Vervest and Dellaert, 2014). As explained by Murray and Häubl (2009), especially in the e-commerce environment, good recommender systems (RS) that aid the consumer in finding the right product are becoming increasingly important, ensuring a higher consumer satisfaction and increased sales for the offering companies (Li, Wu and Lai, 2013). Even though good RSs exist in the market (such as Amazon’s collaborative item-to-item filtering mechanism or Netflix’s hybrid model of collaborative and content based filtering (Jones, 2013)), it seems that today’s RSs fall behind what should be technically possible. Thus, Li et al. (2013) suggest a new RS that does not only take a customer’s past behavior into account but adds a social component that would greatly increase the information available to the system and thus improve its prediction accuracy. An important drawback of today’s RSs mentioned by Li et al. (2013) is that the platforms utilizing RSs are independently operated and only use the data obtained within the boundaries of their respective platform. Real value, however, could be obtained when integrating the data of various different platforms and adding the social component of the social network of a consumer to the recommendations shown on an e-commerce platform. In real life, after all, we also tend to ask our friends for advice when shopping and especially in cliques of close friends, the shopping behavior of individuals potentially influences the shopping behavior of the others (Li et al., 2013; Shang, Hui, Kulkarni and Cuff, 2011). Continue reading Are cross-platform social recommender systems the future?