Symbaloo: from homepage website to educational tool

Symbaloo is an internet based company with 15 million users whose product is a homepage. On Symbaloo, people can click tiles that link them to their favorite websites or generate helpful tools on the website itself. People can choose to either use the standard homepage or to customize their own page (Symbaloo, 2019).

The (dutch) standard homepage of Symbaloo

The unique value that Symbaloo offers to their customers is defined in two terms: simplicity and customizability. Symbaloo mostly targets two groups of people. Firstly, the digital immigrants. This group consists of the more elderly people who have a rough time navigating the internet, who are mostly appealed by the simplicity of the website. Secondly, the digital natives. This group consists of younger people who are already sufficiently experienced with the internet and are more appealed by the customizability and the visibility of the website. (Prensky, 2001)

Symbaloo has to thank most of its users to customer centricity. Symbaloo has put a lot of effort in understanding who their customers were, why they were using Symbaloo and what the most important value was. This centricity was eventually the most deciding factor for most of the digital immigrants, who had trouble getting started on the internet by themselves. Symbaloo acted as a fallback for when users had troubles with using the internet, resulting in a lot of interactions by phone or by email.

The business model of Symbaloo consists of four different aspects:

  1. The tiles at the homepage are sold to advertisers. Although it wasn’t specified that these tiles were sponsored, the tiles were highly successful, regardless of the fact that they were promoted by a biased recommendation agent.
  2. Symbaloo sells PRO accounts for a fee, which offer more functionality than the free standard accounts
  3. The searches in the google search engine (in the middle of the page) generate referrals for which advertisers pay (through google). This search engine also contains sponsored recommendations, which are displayed as natural results and were also equally successful as other search results, regardless of being promoted by a biased recommendation agent. The working of the tiles and the search engine contradict the results of the research by Wang, Xu and Wang, who mention that the sponsorship should probably have been disclosed. (Wang, Xu & Wang, 2018).
  4. The wallpaper in the background, which either displays a beautiful picture or an advertisement .Personalized information was used to decide who gets shown what wallpaper. For example, some wallpapers were only shown to either males or females. It was not disclosed that this info was used, but it did lead to higher click to rates per view than when the advertisements were not personalized, which somewhat contradicts the research of Aguirre et al. (2015).

The homepage of Symbaloo with a (personalized) advertisement in the background

The business model of Symbaloo works well on the short term, but is not sustainable on the long term. As time goes on, the amount of digital immigrants will reduce and the amount of digital natives will increase, which means that the advertisements and the unique proposal they have now will have to be changed. The problem with the business model as it is now, is that most digital natives have little desire to use a homepage other than the standard google or bing for example. For the digital immigrants, Symbaloo offered simplicity, which was a necessity for some to be able to properly browse the internet. However, as digital natives do not experience the same limitation, the value of that simplicity becomes far less. In other words, the growth of the homepage of Symbaloo has stagnated. (Prensky, 2001)

The workings of the business model become more visible when looking at the BCG matrix. The BCG matrix is a matrix in which products are placed in any of 4 areas, defined by the dimensions market share and market growth. For Symbaloo, the homepage would be a cash cow, as they have quite a lot of users, but the growth has stagnated as mentioned before. Because of the lack of growth, Symbaloo is in danger of going out of business. In order to survive on the long term, Symbaloo has ventured into an entirely new branch: education. Symbaloo is looking to use their existing environment, userbase (a lot of users were educational users) and current knowledge in order to become a big party in online education environments. At the moment, the educational application is still starting up and growing fast (question mark on the BCG matrix), which requires a lot of investments. These investments were funded by the earnings of the homepage. (BCG, 2014)

The BCG matrix

Symbaloo nowadays offers two unique propositions to the educational world. The educational product ( offers crowdsourced content creation in the form of lesson plans, which become available online. These lessonplans are about a single subject, i.e. Napoleon, Vulcanism, or Microsoft PowerPoint, and are created and used by the teachers themselves. The lessonplans are crowdsourced and marketed as such, which according to Nishikawa et al. (2017) increased its performance. Besides that, there is also the customizability. Symbaloo sells packages to schools, which allow them to fully integrate created lesson plans and other learning environments into their own single Symbaloo page. In other words, Symbaloo creates a personalized product for each different customer, which has proven to be very valuable to schools and school communities all around the world.

The story of Symbaloo includes both success and failure. Where the original product and their original value have been mostly deprecated, the expertise and developed environment have remained very relevant in the value that Symbaloo offers to their customers nowadays. Customizability and crowdsourced content creation are the two pillars on which Symbaloo continues to thrive nowadays. The company is one of the many examples that have shown the importance of customer centricity nowadays and its effects on the fate of companies.



Aguirre, E., Mahr, D., Grewal, D., de Ruyter, K. and Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34-49.

Boston consulting group. (2014). BCG Classics revisited: The growth share matrix. Retrieved from

Nishikawa, H., Schreier, M., Fuchs, C. and Ogawa, S. (2017). The value of marketing crowdsourced new products as such: Evidence from two randomized field experiments. Journal of Marketing Research, 54(4), pp.525-539.

Prensky, M. (2001). Digital Natives, Digital Immigrants. On the Horizon,  NCB University Press, 9 (5), October 2001.

Symbaloo, (2019). What is Symbaloo? Retrieved from

Wang, W., Xu, J. and Wang, M. (2018). Effects of Recommendation Neutrality and Sponsorship Disclosure on Trust vs. Distrust in Online Recommendation Agents: Moderating Role of Explanations for Organic Recommendations. Management Science, 64 (11), 5198-5219.


Note: most of the information about Symbaloo, their business model, history and way of working is based on my experience of working there (2017), of which there is no online source available.

Written by: Oskar Sabel, 414014os

A potential for consumer value creation: Citymapper

Founded in 2012 by Azmat Yusuf (Tanasoiu 2018), Citymapper is a UK-based company which aims to transform the transportation industry. Through its application, Citymapper helps its user navigate a given city’s transportation grid and provides users with the ability to search for the desired destination, after which the app displays a number of travel itinerary alternatives. Since its inception in 2012, Citymapper has grown internationally and currently operates in 39 cities around the globe (Citymapper 2018). The company creates value for its user by providing them with a travel companion that generates personalised travel options.

But can the consumers become of more value for Citymapper by creating value other than Citymapper capturing their value through the search engine?

Current business model
Citymapper’s currently offers value in the form of efficiency and usability to the users of its transit application. The company exploits its current IT infrastructure, collected data and easy to use user interface to deliver digital content to consumers. On the digital business model framework (Weill et. al 2013) Citymapper’s business design and knowledge of the end customer most closely correlate with the supplier business model.

One way information stream

Citymapper currently gathers partial knowledge of the end users such as search and location (start and end point) data (Citymapper 2018). Other data such as name, address, demographics or search history are not being collected. Therefore, the main information stream flows through the Citymapper application to the user.

Potential consumer value creation
Citymapper can capture a great deal of value by giving its users the ability to co-create value for the application. This can be done by allowing users to give inputs, that are in turn shared with the rest of the Citymapper users. In the current situation, Citymapper supplies users with information about public transport and allows users to plan their public transport trips. The urban transport information shared by Citymapper is limited to the information that is supplied by large public transport companies or private companies gathering transport data. Citymapper has the option to turn their business model from a supplier model into a two stream model.

Two stream business model

How can consumers co-create value for Citymapper?
By starting to use one of their greatest assets they have, a large user-base. Citymapper has the possibility to crowdsource the rating system and the supply of information to their customers making it possible to better understand and support their own customers. Not only are they able to deliver more precise and real-time data on transportation and planning, but also they get more insights in the demands and needs of their own customers. A few of many options that can be crowdsourced are listed below.

The crowdedness of the vehicle
Users could indicate the crowdedness of a particular vehicle signaling that there are no seats available, encouraging users to opt for a different train. Other users could be notified while they are still at home about the crowdedness of the trip, and come prepared, saving them from the surprise of a crowded train, which is one of the greatest pain point related to public transport, according to Fellesson and Friman (2008).

Unexpected delays during the trip
Users could indicate unexpected events that would delay the trips. This live information can be sent to other users, notifying them that the vehicle will be running late, and suggesting an alternative trip. This is all done much quicker than first having to signal the transit company, which in turn must notify users through the rail stations.

Supplier reliability & comfortability
Users could rate transportation providers on their service, both looking at reliability and comfortability. By rating cleanliness, politeness of the driver and price/quality consumers get insights in the overal quality of the transportation modes. This would help other users to select their company of choice.

By gaining more knowledge on what the users, both as a whole and individually, like and demand recommendations can be given. For example, someone who never uses the bus does not want to have the bus in their itinerary. By receiving ratings of services, crowdedness and delays better recommendations can be made. Even more interesting, customers create recommendations and insights for other users, creating a C2C environment.

In order to improve the customer experience for Citymapper users, an in-app payment system could be introduced as well as a ticket management feature. These additions to Citymapper’s value proposition effectively introduce two additional steps in a typical user journey: Once a given user has gathered the desired information regarding his public transport itinerary, instead of leaving the Citymapper ecosystem, the user is given the option to directly purchase the tickets corresponding to the selected journey. Furthermore, once the ticket purchase is completed, tickets are stored within the ticket management feature of the new Citymapper app. This enables the user to remain within the company’s ecosystem throughout the physical public transport journey, using the app as a digital ticket. Overall, the addition of in-app ticket purchase coupled with the ability to use the app itself as a digital ticket greatly improves the overall customer experience while increasing the time a given user spends within the Citymapper platform.

Additional options
Multiple other options open up when turning Citymapper into an open platform environment. By adopting one of many other open platforms for ride sharing and including them into the transportation itinerary would really turn on consumer value creation. Imagine the option to join someone in the car, scooter or motorcycle for a part of your trip. Think of what would happen when Citymapper includes Blablacar, Snapcar, Felyx, Lime, Mobike, Car2go and many others in their system. The options to travel from A to B would become endless.


Citymapper (2018) Making Cities Usable. Available at:  

Crunchbase, 2018. Available at:

Weill, P. and Woerner, S. (2013). Optimizing your digital business model. MIT Sloan Management Review, 54(3), pp.71-78.

Fellesson, M. and Friman, M. (2008). Perceived Satisfaction with Public Transport Service in Nine European Cities. Journal of the Transportation Research Forum, 47(3), pp.93-103

Pinduoduo – “Chinese Groupon”: the fastest growing challenger in China’s e-commerce market


The Chinese e-commerce market is dominated by large players such as Alibaba and who hold nearly 75% of the total market share. Newer players often struggle to enter the market due to intense competition, but a new player called Pinduoduo has managed to claim the third spot in the e-commerce market and is the fastest growing e-commerce app in China (see figure 1 and 2). In a short period of time, Pinduoduo acquired a market share of roughly 5% (Financial Times, 2018) and achieved 100 billion RMB annual merchandise sold in two years after launch (Graziani, 2018). Data from December 2017 indicate that 50% of all users that uninstalled Taobao (owned by Alibaba) moved to Pinduoduo (Dailypanda, 2018), marking Pinduoduo is a potential threat if left unchecked.

Figure 1. Average Monthly Active Users (MAU) from March 2017 until June 2018. Retrieved from: Financial Times (2018).
Figure 2. Largest Chinese e-commerce App by Monthly Active Users (MAU) in January 2018. Retrieved from: Graziani, T. (2018)

Introduction – Pinduoduo and its business model

Pinduoduo was found in September 2015 in Shanghai by former Google engineer Zheng Huang and is a third-party social commerce platform that focusses on connecting manufacturers, suppliers and retailers with end-consumers in the B2C market. The platform earns revenue from collecting commission fees and online marketing services including advertising. Pinduoduo’s platform distinguishes itself from its competitors by providing users the option to conduct “team purchases”. The concept of team purchase is similar to Groupon’s “group buy” (see blogpost of Hsuchiachenjenny (2014) for a brief introduction). Users can invite friends through other social media platforms to create a “shopping team” and order discounted items together in bulk (see figure 3 and 4). Team purchases allow consumers to receive discounts as much as 90% off on products ranging from T-shirts to smartphones. The platform sold more than 4.8 million umbrellas at 10.3 RMB (1.51 USD) per piece and 6.4 million units of tissue paper at 1.29 RMB (0.19 USD) per box (Lee, 2018). Users mainly benefit from Pinduoduo due to getting products at a lower price, while suppliers are enabled to benefit from reducing inventories and generating revenue from aggregation of demand.

Figure 3. Steps to conduct team purchasing at Pinduoduo’s platform. Retrieved from: Fung Business Intelligence (2018)

Figure 4. Pinduoduo’s interface. Source: Fung Business Intelligence (2018)

Pinduoduo’s unique value: user engagement – more than just financial stimuli!

Pinduoduo uses financial stimuli to encourage consumers to help them expand the user base. For instance, convincing one person to install the app and sign in with WeChat will be rewarded with a box of candy and convincing nine people will grant you 1.3 kg of nuts (Graziani, 2018). While financial incentives motivate people to act, academic research (Burtch, Hong, Bapna & Griskevicius, 2018) argue that including social norms are more effective at motivating intensive effort. The social norms refer to “the prevalence of a behavior in a relevant population, such as the number of individuals who already have written reviews” (Burtch, Hong, Bapna & Griskevicius, 2018). Their study pointed out that financial incentives encourage people to write product reviews, while social norms are better to stimulate people to write longer reviews. A combination of financial benefits and social norms are posed to be the best driver of quantity and quality of writing reviews.

Drawing the link with Pinduoduo, we see that the company incorporates the concept of social norms in its business model. Pinduoduo’s application is gamified and includes a public leaderboard that ranks people based on the money they have made out of inviting friends and displays the number of friends they invited. This aspect allows its users to compare themselves with other people and creates a social motivating factor that goes beyond a mere financial stimulus. The appeal of Pinduoduo lies not merely in its low prices but comes from the satisfaction and the pleasure one receives from getting a good deal (Pandadaily, 2018). Therefore, the inclusion of a social motivating factor alleviates its dependence on the constant input of money to incentivize its users. Instigating users to act as brand ambassadors motivated by both financial and more importantly social benefits is a major success factor that allowed Pinduoduo to establish a large user base in a short period of time.

Are Pinduoduo and Groupon the same?

At the time Groupon emerged in 2008, social media and mobile was less entangled with people’s daily lives than in the current situation. Desktop usage, email newsletters, and credit card payments posed limitations on Groupon’s social commerce potential. In 2013, Groupon has dropped its group buy feature and has lost its status as a social commerce platform. The main difference with Groupon’s business model is that Pinduoduo’s business model leverages the social ecosystem in a more effective way. Tencent has been a principal shareholder of Pinduoduo since February 2017 and facilitated the integration of Pinduoduo’s platform with its own social media. Integration with WeChat (an all-inclusive social media app sharing characteristic of Facebook, Twitter and Whatsapp with Paypal functionality) allows fast and real-time communication between users and enables users to make payments with little effort. At this point of time, it is evident that Pinduoduo has surpassed Groupon’s ability to leverage the social ecosystem to establish the consumer base that it has now.

Figure 5. Difference between Pinduoduo and Groupon in user engagement.

The challenges ahead

Viewing Pinduoduo’s success in motivating users to spread the word and persuade their friends in using the app, the company however reported an annual loss of 525 million RMB (77.5 million USD) in 2017 (Fung Business Intelligence, 2018). The current strategy is focused on a push strategy and faces high costs in building brand awareness of the platform. The platform is however plagued with fake products similar to its rival Taobao and (Lee, 2018). Other questions concern to what extend product suppliers are willing to tap into the platform, as the platform highly focuses on price and pays little attention to brand awareness of its suppliers (Fung Business Intelligence, 2018).


Pinduoduo raises the traditional e-commerce platform to the next level by incorporating social media. Users may benefit from getting lower prices for products, but in return need to find friends to join them. The platform also encompasses social norms (e.g. public ranking system) for users to expose themselves and improve community building, while simultaneously gamifying the concept and adding a fun aspect. While the ability of its business model is rather successful, there are challenges that it needs to overcome to guarantee the sustainability of its business model. This is however a topic for another discussion.


Burtch, G., Ghose, A. and Wattal, S. (2013). An empirical examination of the antecedents and consequences of contribution patterns in crowd-funded markets. Information Systems Research, 24(3), pp.499-519.

Financial Times (2018). Ex-Google engineer set for big payday after Pinduoduo IPO. Retrieved from

Fung Business Intelligence (2018) Group-buying platform – Pinduoduo. Retrieved from

Graziani, T. (2018) Pinduoduo: a Close Look at the Fastest Growing E-commerce App in China. Retrieved from

Hsuchiachenjenny (2014) Business case Groupon. Retrieved from

Lee, E. (2018)

Pandadaily (2018) Alibaba’s Worst Nightmare: Pinduoduo Becoming the No.1 E-commerce App in China. Retrieved from

Nice shirt you created! How about this?

This is a review of the study “Social Product-Customization Systems: Peer Input, Conformity, and Consumers’ Evaluation of Customized Products” by Tobias Schlager, Christian Hildebrand, Gerald Häubl, Nikolaus Franke and Andreas Herrmann (2018)

Suppose you are in desperate need of a new wardrobe, but the predetermined shops with stock shirts, pants and other offerings are too stale for you. In other words, you feel like getting creative and coming up with your own design. You might be a good designer, you might not be. It does not necessarily matter when endeavoring custom clothing websites in which you get to decide what your new clothing should look like. The reason for this is the recent invention of social customization systems, which the aforementioned article discusses in depth. Social customization systems aim to offer constructive feedback on a customer’s submitted design, providing opportunities to improve the design by suggested changes or complimenting the custom piece of clothing.

This form of value cocreation can be executed in two distinct ways, publicly or privately. In public customization systems, the feedback is displayed in an accessible environment, for example on the website of the custom clothes shop. In a private setting, however, the criticism or tips are provided in a personal setting that is not accessible to others. An example of this would be through e-mail. Social customization systems are becoming more implemented in products that are often demanded to have certain customization options. Some examples are cars, computers and clothes. This study dives deeper into differences between private and public customization systems and the response on the feedback provided.


The goal of the researchers was to find information on the hypothetical relations in social customization systems between thinking styles, public and private nature of the system, conformity to peer input, perceived closeness to input providers and the evaluation of the final product. That’s a lot of vague information to take in, so to fully understand what is meant by the mentioned variables, we’ll move on to the hypotheses.

The first hypothesis the authors address is about thinking styles, public vs private recommendations and conforming to product modifications. Thinking styles, according to researchers, can be separated by the terms holistic and analytic. Holistic thinking entails taking into account the whole of a situation when addressing a problem, whereas analytic thinking tends to split up the problem in components, analyzing them one by one. The researchers hypothesize that people with a more holistic (analytic) thinking style tend to conform to product modifications more when the recommendations are provided in a public (private) setting.

Besides this hypothesis, the authors look deeper into the evaluation of the final product as a result of perceived closeness to input providers and the extent to which the consumer has conformed to peer input. The hypothesis reads that people who conformed to suggested modifications in a greater extent, are more likely to evaluate their final product more favorably when the perceived closeness to the input provider is high. Simply put, the authors wanted to find out if you, after implementing suggested modifications, evaluate the final product configuration more positively when you feel close to the person who provided the feedback and whether you evaluate it more negatively if you feel distant to the provider.

Conceptual model


The researchers did five different studies in order to find support for their hypotheses. While not all five studies were aimed at both hypotheses individually, they did in most cases contribute towards support. Consequentially, the authors managed to find significant support for both hypotheses, which means that holistic thinking people are more likely to conform to public recommendations, whereas analytic people prefer private communication. Secondly, they found that closeness to the input provider does implicate that you are more likely to evaluate the final product favorably.

Theoretical implications

The findings of this study offer three new insights in existing literature with regards to social customization systems and consumers’ final product configurations. Firstly, it is now empirically supported that when a consumer receives public input on a design or setup, this person is more likely to conform to this input when the thinking style is holistic, while the opposite goes for private input and analytical thinking styles. Secondly, the finding that perceived closeness to the input provider matters when evaluating the final product modifications contributes to literature. Lastly, this research shows that the main predictions of social impact theory  are relevant across systems in passive systems rather than systems in which active participation and contribution is the standard (Latané, 1981).

In short, this study enhances insights on two important moderators (closeness to input providers and thinking style) as well as expanding the understanding of the social influence in social customization systems.

Managerial implications

Practically speaking, these results are highly relevant in managerial decisions. Given the findings with respect to thinking styles and conforming to customization, decision-makers should take into account what the more prominently present thinking style is in a certain market or country when deciding on the nature of recommendations. For example, it was mentioned in the study that German people, on average, are more analytic thinking people while Japanese people tend to be of a more holistic thinking nature (Monga and Roedder John, 2007; de Bellis et al., 2015).

Besides that, the conclusion that feeling close to a person when taking into consideration their suggested modifications, allows for managers to think about how they wish to design their social recommendation system. Given that it is difficult to determine the personality of a person just through their browsing behavior on the website, it could possibly be a wise move to further implement abilities to share your customized product with friends, whom you are often times feeling close to.


One of the most solid decisions made by the authors of the research was the opting for five different studies to find proof for their hypotheses. While a single study often times suffices in providing support for a hypothesis, the authors decided that, in order to eliminate most doubt or ambiguities in the research, five individual studies would improve the reliability of the research. This has definitely helped the credibility of the paper.

Another strong aspect of the study was that researches 2, 3 and 4 were all conducted in a natural environment rather than a fabricated one. The participants of those studies were asked to browse a website in which custom men’s dress shirts could be designed on an actual online social customization system. By providing the natural element to the studies, the chances of generalizability of the research increase.


While the findings of the study are highly relevant and some good overall decisions were made in the design of the study, some weaknesses are present as well. Particularly the decision to attribute a whole country to a particular thinking style is considered to be a non-desirable move. The first of the five studies that were performed in this research categorized Japanese people in general as holistic thinking people while German people were all attributed with the analytic thinking style. You might have tested this for yourself and are likely to have found conflicting results. This means that the generalizability of the study is at stake. This is not the only weakness found that impacts the generalizability. Other than the thinking styles being attributed with entire countries, the studies were often times focused almost solely on male or female participants rather than having a gender neutral product with an even distribution of gender. This makes it difficult to conclude whether the results hold across genders.


de Bellis, E. et al. (2015) ‘Cross-national differences in uncertainty avoidance predict the effectiveness of mass customization across East Asia: a large-scale field investigation’, Marketing Letters. doi: 10.1007/s11002-015-9356-z.

Latané, B. (1981) ‘The psychology of social impact.’, American Psychologist, 36(4), pp. 343–356. doi: 10.1037/0003-066X.36.4.343.

Monga, A. B. and Roedder John, D. (2007) ‘Cultural Differences in Brand Extension Evaluation: The Influence of Analytic versus Holistic Thinking’, Journal of Consumer Research. doi: 10.1086/510227.

Contest holders, stop staring yourself blind!

Submission behavior and its implications for success in unblind innovation contests

Today more than ever, innovation and a constant search for novel solutions with economic value, is vital to strengthen competitiveness of firms (Bockstedt, Druehl, & Mishra, 2015). In the recent years, there has been an emergence of cost-effective “innovation contests”. Innovation contests are a way to invite individuals to submit their ideas or solutions to a specified problem. These contests are used to leverage the creativity, skills and intelligence of thousands of individuals on the internet (Füller, Hutter, Hautz, & Matzler, 2014). Innovation contests can either be ‘blind’ or ‘unblind’. In blind contests, the visibility of the submission posted is limited only to the individual who submitted it and the contest holder (Wooten & Ulrich, 2015). Wooten and Ulrich (2015) define unblind contests as contests where others’ submissions are fully visible to participants while the contest is still live. Seeing others’ submissions including the feedback from the contest holder, could have an influence on the submission behavior of a participant. Figure 1 shows the difference between blind and unblind contests on, a popular innovation contest website which matches graphic designers with organizations in need of a new logo. As unblind contests are quite new and not that well-explored in the literature, Bockstedt, Druehl and Mishra (2016) analyze the effect of unblind contests by examining the implications of participants’ submission behavior for contest outcomes.

Figure 1a. Unblind contest on

Figure 1b. Adapted version of blind contest on

Theoretical background is a consumer co-production network (Dellaert, 2018) in which the consumer co-production is high and the unit of co-production is the network, as the contest holders have the main benefit of this platform (Dellaert, 2018). In that way, value creation takes place in the interaction between customers and the platform (Gronroos & Voima, 2013). A logo is a useful product to crowdsource as it contains a clear question, is easy to implement, there are no obvious skills needed to create a logo and there is no established best-practice (Tsekouras, 2019). creates benefits on social needs of the contestants, as their ideas are seen, they can be part of a community. Through receiving positive feedback, or even winning a contest, their social needs are met, leading to higher self-esteem. Moreover, contestants can have a monetary motivation and it is also fun and instructive to create logos. The four main reasons for organizations to use crowdsourcing are to solve problems, generate ideas, outsource tasks or pooling information (Tsekouras, 2019). especially focuses on idea generation and outsourcing the task of designing a logo. In this way, the contest holders gain benefits by lowering branding-costs (Tsekouras, 2019), gathering insights in the product perception of the consumer and having the choice in picking from a broad range of possible logos / solutions.

Methodology & Findings

In order to take a closer look at how contestants solve problems in unblind innovation contests, a case study was conducted. By using a HTML scraping tool, researchers collected data from 1024 logo-design contests hosted on In addition to contest data, profile information and historical performance of contestants was gathered. As contestants were not aware of this data collection, their submission behavior was not biased.  Results of this study show how submission behaviour could impact contestant’s success in unblind innovation contests. First of all, a lower position of first submission is associated with a greater likelihood of success due to greater potential for obtaining intermediate evaluations from contest holders, shaping the contest holder’s taste and participating actively in the contest.

Secondly, the number of submissions have a positive impact on the likelihood of success up to a certain point. Beyond this point, marginal knowledge gained about the problem specification and the contest holder’s taste diminishes as more submissions are handed in (Figure 2). Therefore, contestants should focus their efforts on high quality submissions as a quantity-quality trade-off was indicated.

Figure 2. Graph on the likelihood of success x number of submissions

Furthermore, contestants who participated in a contest for a longer period were more likely to succeed as it allows them, via emerging information structure, to observe and assess their submissions with respect to the competition and update their understanding of contest holder’s requirements (Figure 3).

Figure 3. Submission participation time frame


A main strength of this study is that it examines unblind submissions in an innovation contest, whereas previous studies mainly focused on examining blind contests (Bockstedt et al., 2016). As unblind contests are on the rise due to their feedback and co-learning system, knowledge about their way of working is invaluable for academic literature. Besides filling a gap in academic literature, outcomes may provide substantial benefits for the contest holders in obtaining the design results they seek. Another strength is the methodological approach. Namely, the contestants subjected to the study are unaware of their participation and therefore participant bias will decrease and internal validation will increase (Smith & Noble, 2014). Lastly, handles a “winner takes it all” policy in which they define first place as ‘success’. The study however, deploys a top-3 listing based on the judging process as a definer of success, which accounts for a broader scope of definition.

Managerial implications

By optimizing the value system design, the joint payoff of the partners involved will be maximized (Carson et al., 1999). Therefore, should invest in motivating contestants on different levels. First of all,, and other platforms alike, should motivate contestants to submit their creations early. This could be achieved by installing a rewarding incentive for early submission and by dividing the contest in separate phases. There will be both social (e.g. social capital or self image) and monetary rewards after each phase, until the final product is build. Secondly, they should promote participation for a longer period of time, by keeping contestants up to date about the contest. By doing so, contestants will likely feel more motivated to participate, possibly resulting in more submissions per contest. Lastly, should motivate contestants to only submit after receiving additional valuable knowledge about the contest and previous designs, by setting a boundary amount of submissions of one per two days. This will improve quality of the designs, which in turn is favourable for the contest holder and co-contestants who can learn from the quality designs and implement it into their own designs.


Bockstedt, J., Druehl, C., & Mishra, A. (2015). Problem-solving effort and success in innovation contests: The role of national wealth and national culture. Journal of Operations Management, 36, 187-200.

Bockstedt, J., Druehl, C., & Mishra, A. (2016). Heterogeneous Submission Behavior and its Implications for Success in Innovation Contests with Public Submissions. Production and Operations Management, 25(7), 1157-1176.

Carson, S., Devinney, T., Dowling, G., & John, G. (1999). Understanding Institutional

Designs within Marketing Value Systems. Journal Of Marketing, 63, 115. doi: 10.2307/1252106

Dellaert, B.G.C. 2018. The consumer production journey: marketing to consumers as co-producers  in the sharing economy. Journal  of the Academy  of Marketing Science, forthcoming, 1-17.

Füller, J., Hutter, K., Hautz, J., & Matzler, K. (2014). User Roles and Contributions in Innovation-Contest Communities. Journal of Management Information Systems, 31(1), 272-307.

Gronroos, Chr. & Voima, P. (2013), Critical service logic: making sense of value creation and co-creation. Journal of the Academy of Marketing Science, 41 (2), 133-150.

Smith, J., & Noble, H. (2014). Bias in research. Evidence Based Nursing, 17(4), 100-101. doi: 10.1136/eb-2014-101946

Tsekouras, D. (2019) Customer Centric Digital Commerce Lecture 1 & Lecture 3 [Lecture 1 &3]

Wooten, J. O., & Ulrich, K. T. (2015). The Impact of Visibility in Innovation Tournaments: Evidence From Field Experiments. Wharton Faculty Research, 1-36.

Organic food, handmade products, Italian pasta, French wine, and… Customized-ideated products?

A review of the article “The Value of Marketing Crowdsourced New Products as Such: Evidence from Two Randomized Field Experiments.” by Nishikawa H., Schreier M., Fuchs C. and Ogawa S (2017).

Maybe you have realised it yourself; in just a few years, nearly all muesli bars in your local supermarket have been labeled as organic. Or when you are standing in front of the twenty different pastas offered, your eyes are immediately drawn to the most italian named and looking packaging. Of course, these are marketing tools, used to show a certain quality and lure you into buying this product. The next new marketing buzzword, as identified by Nishikawa et al. (2017), might very well be customer-ideated.

Most prior research is focussed on the positive effects of wisdom of the crowds and how the customers know the pains and gains of a product best (Garcia Martinez & Walton, 2014). In this paper, Nishikawa et al. (2017) pay attention to the psychological value of crowdsourcing product development and the potential positive effects of marketing on sales.

Crowdsourcing: Objective vs. Psychological Argument

The research question the authors ask themselves is how customers perceive crowdsourced new products and whether the inferences they make affect their product choices. Quite some research has been conducted on the objective arguments of crowdsourcing new products (Bayus 2013; Poetz and Schreier 2012; Stephen, Zubcsek, and Goldenberg 2016). The general finding is that crowdsourcing can lead to promising new ideas. However, this can only happen under certain conditions. As such, there should be a necessary match between user expertise and design task complexity. Next, the size and composition of the crowd plays an important role. In comparison, the psychological argument which makes this research paper unique, argues that “customer-ideated” should be used as a cue that sells. Specifically, the authors predict that actively marketing the source of design can increase the product market performance. This because of if-then linkages between information users pick up and conclusions.

Image result for lenovo z1

To test this prediction in the real world, the authors conducted a field experiment. By labeling crowdsourced new products as “customer-ideated”, the effect on the product market performance increased by 17%. However, the experiment holds some limitations. Namely, the sample size is too small, and only one product type is used. Therefore, the authors test their prediction in a second field experiment, using two product types and a larger sample size. Moreover, the authors wanted to test if the effect of “customer-ideated” is not because of more specific information on the product display. Again, the effect was positive.

After having established their findings in the real world, the researchers wanted to validate the results and performed two control studies. The first study had the aim to verify if it was actually the customer-ideated cue that caused the increase in sales. This study consisted of an online customer survey in Japan in which participants were randomly assigned to a few different conditions. They were asked which of the two products they preferred and had to explain the reason for their preference. The outcome  of this control study further strengthens the conclusion found in the field experiment, namely: consumers prefer crowd-sourced new products, if recognizable as such, because they infer these products to be 1) of higher quality and 2) better at addressing consumers’ needs.

The aim of the second control study was to measure the quality inference of consumers. It consisted of a control test in Europe in which participants were randomly assigned to either right or wrong information about the source of ideation. As a result, the participants chose the product labeled as ‘customer ideated’ more often and labeled this product as having higher quality. This outcome confirms earlier findings; products that are labeled as ‘customer-ideated’ are believed to be better because they are more useful to customers and more effectively address their needs.

Image result for louis vuitton bag

My thousand dollar (customer-ideated) designer bag

The article has a new take on the use of crowdsourcing for product labeling to create marketing advantages. The fact that this has been studied in different environments, adds to the prove that the effect can be observed for certain products. However, the question remains whether this still applies for other product categories such as luxury brands and high-tech products. For luxury brands, such as Louis Vuitton, customers pay a high premium for exclusively designed products. A label inferring that customers designed the product might lower the value of the bag as the designer him or herself did not put its ‘magic touch’ to it. Furthermore, for high-tech products, consumers might not have the right knowledge to make valuable contributions to the product development process. Therefore, a label indicated the customer contribution might indicate lesser value to other customers who do not feel like their peers can grasp the complexity of the product to design it (Schweitzer et al., 2012).

How about business operations?

The results of the research point out a 17 percent growth in sales, which indicates that it is worthwhile investing in labeling your products as crowdsources. Nonetheless, the results might be offset by the increase in operational costs of including customer in the ideation process. Whether costs of including the customer into the process are higher (additional steps in the process) or lower (lower investment in designers) is not included in the research. Therefore it is not known whether the 17 percent increase is high enough to cover potential costs.

A future of customer-ideated products

Considering how these results will influence what our future would look like is not that easy. However, logically if the effect is positive, more and more producers will start labeling the product as customer-ideated. Once it becomes more common, the uniqueness effect might be lessened, cancelling out the increase in sales. In this scenario, the way of putting the message will become increasingly important for producers to differentiate in the looks of their product. This includes using different wordings and color palettes to avoid sameness. And who knows, once all products are labeled as customer-ideated, the label designer-ideated might conquer our hearts.


Bayus, Barry L. (2013), “Crowdsourcing New Product Ideas over Time: An Analysis of the Dell IdeaStorm Community,” Management Science, 59 (1), 226–44.

Garcia Martinez, M., Walton, B. (2014), “The wisdom of crowds: The potential of online communities as a tool for data analysis” Technovation, 34 (4), 203-214.

Girotra, Karan, Christian Terwiesch, and Karl T. Ulrich (2010), “Idea Generation and the Quality of the Best Idea.,” Management Science, 56 (4), 591–605.

Poetz, Marion K., and Martin Schreier (2012), “The Value of Crowdsourcing: Can Users Really Compete with Professionals in Generating New Product Ideas?” Journal of Product Innovation Management, 29 (2), 245–56.

Stephen, Andrew T., Peter P. Zubcsek, and Jacob Goldenberg (2016), “Lower Connectivity Is Better: The Effects of Network Structure on Redundancy of Ideas and Customer Innovativeness in Interdependent Ideation Tasks,” Journal of Marketing Research, 53 (April), 263–79.

Schweitzer, F. M., Buchinger, W., Gassmann, O., & Obrist, M. (2012). Crowdsourcing: Leveraging Innovation through Online Idea Competitions. Research-Technology Management, 55(3), 32–38.

Share, Like, Subscribe – Earn What You Deserve

Imagine writing a nice post for your friends on social media on something you have experienced that day. You put some effort in it, put in a nice quote, make a meme and post it on your social media. It turns out your friends like it so much, that they want to share it with their friends. And their friends with their friends. Before you know it your post goes viral and millions of people have liked or shared it. This off course sounds amazing, but what do you get in return? You get some likes and appreciation, but that often fades away faster than you can enjoy it. Moreover, many funny posts or memes are shared without acknowledging the maker of this post and claim it as their own. To tackle this problem, Steem, came up with a new social media platform, Steemit. Steemit believes that the users of the platform should be rewarded for their contributions to the platform. Therefore, on their platform you can earn rewards for the content that you post on the website.

How does it work?

Steem is a social network site where you can earn rewards as a publisher or as a curator. The website is developed using Steemit Blockchain technology and STEEM Cryptocurrency. The content that is written on the social media platform is written to the Steem Blockchain, where it is stored in an immutable Blockchain ledger. Users in turn get rewards for posting content or acting as curator in the form of digital tokens called Steem.

Everyday new Steem tokens are added to the so called community rewards pool by the Steem Blockchain. These Tokens are given out to users, based on the amount of votes that their content has received. Moreover, active users that have a high amount of tokens in their wallet get additional recognition by giving them so called “Steem Power”. This gives them the power to decide where a larger portion of the rewards pool is distributed too. (Steemit FAQ, 2019)

Below video gives an clear overview of how Steem voting works:

(Tomlinson, 2017)

As described above Steem tokens cannot only be rewarded by posting, but also by acting as a curator. Below there is a list of how a user can earn their digital tokens:  

  • Posting: If you post and share it with your fellow users you can earn so called upvotes. The higher the amount of upvotes you deserve, the bigger portion of the rewards pool you will get.
  • Voting and curating: If you vote for a post before it becomes popular, you can earn a curation award. The amount you will receive for curating is dependent on your amount of Steem Power.
  • Purchasing: STEEM or steem dollar tokens can be purchased on various market exchanges
  • Vesting: By Holding your tokens to get extra steem power, you can earn extra tokens as reward for holding.  

(Steemit FAQ, 2019)                                                               


This platform sounds as a dream come true for many contributors of the web, earning by simply posting or voting. However, the dream has not completely come true yet since there are some negative side effects causing the platform not to live up to its full potential. Below graph 1 shows that there is steep decrease in the amount of active users in the past month, indicating that people are no longer actively contributing to the platform. This decrease in active users can be described by the following problems.

Graph 1 – Active users per Month on Steemit (Arcange, 2019)

One of the problems Steemit recently encountered is that of the fluctuating crypto market, which can cause the valuation of the company to diminish tremendously. A few months ago, CEO Ned Scott Posted and announcement saying Steemit had to let go 70% of its employees and that they would focus on keeping the cost of infrastructure that is running low (Scott, 2018). This sudden reorganization is due to the crash in cryptocurrency prices in 2018. The value of  Steem decreased from 8USD in the beginning of 2018, to only 0,30 USD at the end of the year, causing a large decrease in the cash flow of the company. (Zachary, 2018) This is off course a huge danger for the Steemit platform, being reliant on such a unreliable currency.

Other problems are more related to the set-up of the platform. By giving extra power to users that have a high amount of Steem tokens, you create so called whales that have total control of the platform. (Masters, 2018) They have more voting power and power over the division of the Reward Pool, and thus have high control over what gets rewarded. This makes it extremely hard for new users to enter to platform and gain a substantive part of the payout.

Another important aspects of a platform is network effects, meaning that more users will generate more value for each other. For Steemit however, more users does not automatically generate extra value for the users, because there is also a form of competition on the platform. If more people will be part of the platform it will become harder to get large amounts of upvotes, and thus rewards. This causes the amount of reward to be spread more evenly over many contributors, making the amount of reward almost dismissible. By doing so the platform creates a trap for itself where more users actually discourages the effect of rewarding contributors.  

A side effects for this increased difficulty to get upvotes is that Voting bots have been developed. You can pay these voting bots to create additional up votes on your article, and by doing so increasing your rewards. (Masters,2018) Articles do no longer get rewarded for their quality, but are more dependent on the amount of money people are willing to invest in voting bots. This diminishes the quality of the platform, since it cause low quality articles to also reach high amount of appreciation. Moreover it  is causing prominent users to leave the platform, since it results in unfair competition (Skoll, 2018).

Steemit, Yer or No?

So, the idea of being able to earn rewards for your content sounds great but it has been shown that creating such a platform is harder than it sounds. Money always triggers a form of greediness, making people focus more on earning more rather than creating valued content. This causes cheating and collaboration which does no good for the quality of the platform. If you are still looking for a platform where you get more recognitions for you contributions, (but no money), check out Reddit. Do you really want to monetize your content you can always become an influencer on Instagram or Youtube.


Arcange. (2019). Steem Statistics – 2019.01.01. Retrieved from

Masters, C. (2018). Losing Steem: One of the Most Active Crypto Projects Cuts Staff. Retrieved from

Steemit FAQ. (2019). Retrieved from

Skoll, M. (2018). Why I Left the Steem Blockchain. Retrieved from

Tomlinson, S. (2017). An explanation of Steemit Voring Power – retrieved from

Zachary. (2018). Steemit Lets Go Over 70% of Employees, Blames Bear. Retrieved from

Virtual reality for elderly

Over the past twenty years or so the media have frequently carried reports about population aging. According to World Health Organization, the number of people age 60-and-over will rise to 2.1. billion in 2030, which translates into one fifth of the global population being in the retirement age. It goes without saying that this trend raises many issues, such as a significant increase of health or public and private pension costs. However, there is a silver lining to this phenomenon: older people are on average healthier than in past generations and especially in the developed countries, economic growth and accumulation of wealth have created a generation of elderly that is wealthier and more willing to spend money than ever before. As a result, the demographical trend has turned out to be a boon for business, creating an attractive, profitable customer segment. Companies who acknowledge that older people have slightly different consumer needs resulting from physiological changes connected to ageing, such as changes in eyesight, hearing, mobility and dexterity, can benefit from an access to a vast customer group. This attention shift is not entirely novel, and has already been recognized by some companies, especially in the financial and healthcare industries. What is new is that firms currently targeting this market have now started to leverage the most innovative technologies that allow them to personalize their offer and encourage their customers to co-create the products. One of the most interesting examples of innovative business ideas targeted at elderly is virtual tourism offered by Rendever.

Business model
Rendever is a company that leverages virtual reality technology to create a virtual journey experience by using algorithms that convert 360 panoramic photos and videos. The firm’s offer is a subscription-based service for individuals and facilities and is designed specifically for elderly. The virtual reality headset allows older adults to overcome mobility difficulties and virtually travel to a myriad of places in the world. The firm’s offer includes various touristic spots destinations, such as Machu Picchu, but also other ways of entertainment such as concerts, historical tours or architectural exhibits. Apart from the company’s existing virtual tourism destinations offer, Rendever also provides a service of a personalized content. This includes recreating spots of sentimental value such as childhood homes or wedding locations and converting photographs of family members, but also capturing a family event on camera that is later converted to a virtual reality experience. Finally, the Rendever wearable devices can be synchronized with other headsets, allowing users to virtually travel together.

Seniors at Maplewood Senior Living travelling virtually with Rendever headsets.

Apart from the entertainment aspect, the company puts an emphasis on health benefits of using virtual reality. As research shows, leveraging this technology can serve as a distraction from pain, which is especially vital for seniors, many of whom have to deal with chronic pain and painkiller medication side-effects. For this reason, VR can be used during exercises or rehabilitation. Moreover, using virtual reality helps delaying the progress of dementia, stimulating the brain and reactivating neuropathways. In such case of cognitive decline or memory losses, as a part of reminiscence therapy, the firm offers individualized packages created from images of family members and meaningful locations from the person’s life.

A senior diagnozed with dementia smiles for the first time in months after being shown a VR video with puppies.

Efficiency criteria
Both customers and the company profit from the product, therefore the joint profitability criterion is met. Elderly people, who due to mobility difficulties cannot commute, can overcome this barrier by travelling virtually – whether to far-off touristic destinations or places of sentimental value. The virtual technology helps them to avoid isolation that tends to increase especially when an older person needs to be transferred to an assisted living community, but also when he still lives at home but due to his age is not as dexterous as before. Customers of Rendever profit from goods and services tailored to their needs: the personalized offer helps them reconnect with family members and virtually attend events they would not be able to travel to. Furthermore, Rendever technology serves not only as an entertainment and an educational mean, but may also facilitate building new relationships through allowing users to virtually travel with others, therefore fulfilling their social needs. The health aspect is also of paramount importance, as using virtual reality may delay the diminishing quality of life due to memory and cognitive losses.
The company, on the other hand, gains access to two market segments. First, it can target a profitable and an increasingly larger group of elderly directly through their individual offer. Second, it can leverage a B2B business model. Marketing to elder care market and health care segment opens up a potentially vast revenue stream. As geriatric population increases, the number of elderly people suffering from chronic diseases such as dementia or Alzheimer rises. As a result, the senior care industry that encompasses elderly care or memory care facilities and assisted living communities has already reached 400 billion dollars of an annual revenue and is expected to grow at a significant pace. The company could also cooperate with the public health sector which struggles with providing care to an increasing number of seniors.
Furthermore, even though the company has to invest into costly advanced technology and production of wearable devices, a subscription-based business model allows it to reduce fixed costs. The manufacturing cost is also expected to decrease as virtual reality gear is becoming more popular and commonly used. Furthermore, the firm’s personalized offer creates an additional revenue stream and increases switching costs that customers may experience, as moving to a competitive product is connected to a loss of the personalized content.

There are two significant obstacles that the company may face in the future. Firstly, some of the elderly have an anti-technology views and can oppose using virtual reality technology. As a result, convincing assisted living communities to partner with Rendever may meet with challenges. Secondly, despite the fact that virtual reality technology may help sooth isolation in the short term, there is no guarantee that it would be able to still cheer elderly up as they get used to it. And while seeing family and friends in the virtual reality may ease the loneliness for some time, even an advanced technology cannot replace a real, human contact. In order for the company to overcome these barriers, an awareness about what virtual reality is, what are its benefits for elderly and limitations, needs to be built. Only then will Rendever be able to expand its reach and become profitable in the long term.

Bruun-Pedersen J.R., Serafin S., Kofoed L.B. (2015). Simulating Nature for Elderly Users – A Design Approach for Recreational Virtual Environments. 2015 IEEE International Conference on Computer and Information Technology. doi: 10.1109/CIT/IUCC/DASC/PICOM.2015.235.
Irving P. (2018). Aging Populations: A Blessing For Business. Forbes. Retrieved 13th February 2019 from
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Mass Challenge Health Tech. (2018). Reconnecting the Elderly with the Joys of Everyday Life through Virtual Reality. Retrieved 13th February 2019 from
Ward P. (2017). Virtual Reality Is Helping Elderly People Explore the World. Retrieved 13th February 2019 from
Wolf Williams R. (2017). How Virtual Reality Helps Older Adults. Forbes. Retrieved 13th February 2019 from

Spread Your Wings with Triberr

You have this perfect idea of creating a blog that is going to be fed with eye-catching and breath-taking blog posts. You then decide to sign up on (or any other blogging platform of your choice) and start to upload your first posts. Only to find out that your content is not as spectacular as you thought it will be because nobody is actually reading your posts. So, after a few more trials, you see no progress and decide to abandon the whole blog. Why? Because you assume after a few trials that your posts are useless and boring for the audience? Slow down. Relax. The chances are, your blog posts have not even reached your targeted audience.

In today’s fast-paced world, the internet enables you to connect with almost everyone around the globe. You must already know this when you first considered blogging. But what you might have forgotten is that the internet gives not only gives the reach but also a pool of tools to maximize that reach. One of those tools, given we narrow it to the blogging sphere, is Triberr – a blog post sharing platform that will give life to your blog (posts). Not by using fake humans that will artificially increase your readership figure but by connecting you with real humans who will help you grow your blog organically. We are not talking about social media bots, we are talking about a whole community of like-minded bloggers, who share each other’s contents and this way, support each other. Triberr calls this community a “Tribe”.

So, how does this ‘Triberr’ platform, that I have (hopefully) hyped you on, work?

Triberr is a platform that aims to connect like-minded bloggers to support each other. To understand how the platform works, let’s have a look at its core element: Tribes. Let’s say you are a fashion blogger looking for (more) readers to read your latest blog post that you put so much effort into creating. Triberr does exactly that. It helps you increase the readership rate of your blog posts by connecting you with another fashion blogger, let’s call this person Blogger A. Once you connect with Blogger A, after few procedures, you become a member of a tribe that Blogger A is currently enrolled in. That is, you are now surrounded by people who blog about fashion as you (aspire to) do. After you are officially in, you can start sharing your blog post in the community. What happens next is, once you share a blog post, your team members (called tribemates) will support your blog post by sharing your post on their social media – this way, your post reaches more people but also a more relevant audience. As said before, Triberr is a community of bloggers that support each other. As such, you should reciprocate the received favor you received by doing the same thing – you share your tribemates’ blog posts’ on your social media. Your tribe(s) hence becomes fuel for your blog’s organic growth.

Let’s evaluate Triberr’s business model further via efficiency criteria

Triberr is a platform that aims to increase the same-sided network effect by engaging and connecting bloggers around the world. We can thus define Triberr’s business model as crowd-sourced based. In theory, it means that at Triberr, consumer co-production is high and a network is a unit of co-production (Tsekouras, 2019, p. 28). In lay terms, the previous sentence says that bloggers (i.e. consumers) are willing to actively participate in activities that will create value for Triberr which brings benefits to the platform but also to bloggers themselves. That is, Triberr grows as more bloggers are active on the platform but bloggers also benefit from a higher number of shares and thus, a higher readership of their blog posts. This mechanism thus satisfies the first efficiency criteria, which is [joint profitability] of partners involved (i.e. bloggers and Triberr) who work together to create greater value (Tsekouras, 2019, p. 35). Triberr works as a customer-driven value system and it works because both consumers (i.e., bloggers) and the platform both benefit from each other. To name a number of benefits for bloggers: an increased audience that is relevant, getting to know other like-minded (successful) bloggers from whom they can learn from, and satisfied social needs through the feeling of belonging into a community (aka tribe). To name a number of benefits for Triberr: lower marketing prices because of (electronic) word-of-mouth and increased platform value as the number of bloggers grow. In terms of effort and investment, both participating sides exert minimal efforts: bloggers produce contents they enjoy and outsource sharing efforts, Triberr leverages bloggers and outsources the growth of the platform to them altogether.

In many cases, bloggers can abuse the platform by creating inappropriate tribes as well as tribes could be polluted with inappropriate bloggers. Triberr solves this issue by disabling aspiring members to join the tribe immediately. Aspiring members must first go through an “introduction period” in which they can follow their desired tribe and “join” the tribe as observers (Triberr, 2019). As observers, aspiring members’ posts are not (yet) visible to the members of the tribe. Nevertheless, they are allowed to interact with the members of the tribe and share their posts – this way aspiring members can “earn” the tribe’s trust and thus a place in the tribe. Only after observers become full members, their posts will become visible (and thus shareable) to all members of the tribe. Bloggers are responsible for their own content, which must be original. Contents that are perceived hateful or involving threat and harassment are taken care and act upon Triberr as well as US legal bodies. Moreover, a user’s identification is linked to the user’s social media profile to increase authenticity. In addition, a user’s privacy is protected by Triberr’s compliance with GDPR. As such, the Triberr’s feasibility of required reallocations, the second efficiency criterion, is considered met as (aspiring) members are carefully screened (by the community) and user’s trust is achieved with legal compliances.

Triberr goes beyond tribe community and content sharing.

In addition to the above-mentioned two services, the platform provides three premium services. Users can measure content performance with “triberrAnalytics” in the form of post analytics (e.g., number of clicks or content shares) and growth analytics (e.g., number of new and active members). With “triberrQueue”, users can optimize the posting time of their contents. Lastly, “triberrCurate” helps clients with discovering and choosing the relevant content for their targeted audience.

So, my last question for you is:

“Are you now ready to spread your wings with Triberr?”


Triberr man proof [Digital image]. Retrieved from

What’s in the name?

Firms have tracked consumers’ shopping behavior in their stores for decades. Back in the days, most businesses were neighborhood stores. Employees greeted each customer by name and knew what each customer liked. These employees used consumers’ information to tailor interactions on an individual level across sales, marketing, and customer service. Nowadays, customer interaction often takes place online so firms rely on online customer data. Therefore, customers benefit by receiving products and services that match their personal preferences. Firms, however, can benefit as well, by charging higher prices for the recommended products as they provide better service (Chen et al. 2001). Therefore, the use of information for personalization sounds like a win-win proposition for firms and customers. However, customers can see it as a double-edged sword, which on one hand enhances consumer utility and at the same time cause privacy violation (Malhotra et al. 2004).
Recently, customers are becoming increasingly aware of the amount of data that firms collect and what risks are involved. We call this phenomenon overpersonalization (Bleier and Eisenbeiss 2015). Because of the trade-off between enhanced consumer utility and privacy concerns, Wattal, Telang, Mukhopadhyay and Boatwright try to find out how consumers respond to firms’ use of two types of information: product preferences and name.

These two types of information can for instance be used in an e-mail campaign targeting customers. Firms can send you such recommendations via e-mail in two ways: explicitly and implicitly. Where explicitly means that the company discloses that they based the recommendation on your preferences, whereas implicitly means they do not. Imagine that you receive an e-mail of a company recommending you the product that you have always wanted. You visited the website the day before for the first time and the sites’ algorithm already learned about your preferences (Johan, Mookerjee & Sarkar 2014). The e-mail does not explicitly state that the recommendation was based on your browsing behaviour. So, this is an example of implicit personalization.
These two ways of giving recommendations can lead to different levels of effectiveness. Imagine that a week later you wake up and the firm took their personalization a step further and begins the recommendation e-mail with a personalized greeting. You are not really familiar with the website as you only visited it for the first time last week. At this point you might start to become wary of the e-mail, as in recent years your awareness of the data you provide to retailers on the internet has increased. As the recommendation helps saving time, the data usage might lead to increasing concerns by customers (Tsekouras 2019). Companies start to take the negative effects of explicitly mentioning the use of personal information into account. Therefore, it might be more interesting for firms not mentioning the recommendations explicitly, but implicitly.

To find out how customers react to these different forms of personalization and how familiarity moderates this effect, the researchers collected data of approximately 20.000 customers from a web-based firm that is a distributor for many products varying from phone services to mortgage lending.
To research implicit personalization, the researchers studied the product-based personalization emails that the firm sent to customers and the customer’s reactions. The customers were divided into pools and when a customer in the pool “long-distance” received an email about long-distance phone services, it was classified as product-based personalization. When a non-related pool of customers received the email about long-distance phone services, it was classified as non-personalized. To research the explicit personalization, the researchers looked at personalized greetings that the firm used. The firm used these personalized greeting randomly, so some customers were greeted with their name while others were not and therefore the researchers could measure the differences between them.
To assess whether a consumer was familiar with a company, the researchers looked at prior purchases. If a consumer already bought something at the firm, the customer was deemed familiar with the firm.
The customers went through two decision phases. Imagine when you receive an email. First, you need to decide whether you open the email. Once you choose to open the email, you can choose several actions: unsubscribe, do nothing, click through but buy nothing and purchase the product. When the customers decided click through but buy nothing or purchase the product, their reaction was branded positive.

The researchers found that consumers respond positively when product-based personalization is used in the email. Contrary to this, they discovered that consumers respond negatively when a personalized greeting was used in the email. Furthermore, they found that familiarity moderates the negative effect of a personalized greeting. Customers who already made a purchase at the firm responded less negatively to the firm using their name.

A main strength of this study is that this study examines personalized emails that are directly sent by the merchant to consumers, whereas prior work only examined the personalized content made available on merchants’ websites or in controlled experiments. The biggest advantage of this research design is that it resembles real world answers the most; it incorporates people’s real reactions as they have to respond to personalized offers with real monetary risks. Controlled experiments can cause various biases. For instance, knowing the nature of a study can make consumers behave differently and subconsciously give response that they think that the researcher wants to hear, also known as the research bias. Using real world data can to a great extent omit these biases.

An important implication that you could take away from this article as a business owner is that personalization of an e-mail to your consumers might not always yield the positive responses you hoped for. It rather depends on the familiarity customers experience with your firm and the type of personalization you choose to use. Like Top marketing speaker David Meerman Scott once said “Instead of one-way interruption, personalized marketing is about delivering value at just the right moment that a user needs it”. So firms need to carefully consider how they use personalization because these good intentions might have the opposite effect.


Bleier, A., & Eisenbeiss, M. (2015). Personalized online advertising effectiveness: The interplay of what, when, and where. Marketing Science, 34(5), 669-688.

Chen, Y., Narasimhan, C., & Zhang, Z. J. (2001). Individual marketing with imperfect targetability. Marketing Science, 20(1), 23-41.

Johar, M., Mookerjee, V. and Sarkar, S., 2014. Selling vs. Profiling: Optimizing the Offer Set in Web-Based Personalization. Information Systems Research, 25(2), pp.285-306.

Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users’ information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information systems research, 15(4), 336-355.

Tsekouras, D. (2019) Customer Centric Digital Commerce Lecture 2 [Lecture 2]

How recommendation agents can restore trust lost through promoting sponsored products

A review of the article “Effects of Recommendation Neutrality and Sponsorship Disclosure on Trust vs. Distrust in Online Recommendation Agents: Moderating Role of Explanations for Organic Recommendations” by Wang, Xu, and Wang (2018)

Ever wondered why a pair of 5-inch stilettos, completely out of your price range, shows up as the first product option when searching for a pair of trainers online? Much of the answer lies in how recommendation agents (RAs) – essentially the algorithm tool that sits on many online stores’ and aggregator’s websites – reflect neutral or bias outcomes. Neutral RAs will display outcomes based solely on the user’s requirements. However, biased RAs manipulate the outcomes to promote sponsored products, irrespective of its relevance to the user’s requirements. In the adjacent example, a user searching for “rainbow socks” is first presented with a sponsored box-set of socks and, below that, the product aligned to his/her requirements.

Amazon search of rainbow socks

The Study

This study explored the extent to which consumers perceive their psychological contract – a “contract” that online users establish to guide their trust and interaction with websites – to have been violated through the manipulation of search outcomes to favour sponsored products. The outcome of this violation is a loss of trust or even creating distrust in the recommendation agent. A second study looked at how the disclosure of sponsorships or the display of explanations can restore lost trust or reverse distrust that has settled in.  Data was collected by means of a lab-experiment during which the researchers manipulated the order of search outcomes to simulate bias and neutral RAs and then surveyed participants on trust and distrust.


  • Neutral vs bias: participant’s had higher levels of trust and lower levels of distrust in neutral RAs when compared to bias RAs.
  • Sponsorship disclosure: participants had higher trust in a biased RA with sponsorship disclosure than a biased RA without sponsorship disclosure. However, sponsorship disclosure did not lower distrust.
  • Explanations: participants had higher trust in a biased RA with explanations than a bias RA without explanations. Again, distrust was not resolved by displaying explanations.

The same study was completed in Hong Kong which confirmed the findings from the USA and that the findings are applicable cross-borders.

Practical applications

We see the roles of recommendation agents and sponsored advertisements come to life on social media platforms such as Instagram. As a celebrity with more than 120 million followers, Kylie Jenner is an influencer. Her followers would pay attention to the products she uses. However, based on her Instagram posts, her followers do not know whether or not a product is sponsored. In the example below, we do not know whether Lyfe Tea is a recommendation coming from Jenner or a third-party sponsor. Based on the findings of the study, individuals are less likely to trust this product promoted by Jenner, making her post a potential example of bias without sponsorship disclosure.

Kylie Jenner’s non-disclosed sponsored ad

Conversely, there are numerous examples of paid sponsorships on Instagram. Below, we see a post by a social media influencer, where it clearly states that the post was paid for by Volvo. In a snap survey in a recent Masters-level class at RSM, more individuals trusted the below social media influencer over Kylie Jenner because of the disclosure that the post was paid for by Volvo. By seeing that this is a sponsored post, individuals know up front that it is biased. 

Sponsored Volvo Ad

Strengths of the study

The study researches a relevant topic, due to the popularity of e-commerce, and takes a holistic approach in the experiment design. The researchers clearly identify the factors associated with trust, including biased and non-biased sponsorship disclosure, and neutral recommendation agents. The experiment itself focuses on purchasing a camera within an ecosystem designed by the researchers, where they can better manage participants, as opposed to having participants go on a third-party e-commerce website.

Weaknesses of the study

The study doesn’t really reflect consumer decisions – consumers make purchase decisions online based on a tradeoff between perceived benefit, perceived risks and trust(Kim, Ferrin, & Rao, 2008). Even when their trust has been violated, they may still proceed based on their perception that the benefits exceed the risks or distrust they have.

It may also not be appropriate to generalize outcomes of the study which is derived using students as data subjects. Hanel and Vione (2016) found that, when testing personal or attitudinal variables, such generalizing is problematic as students vary randomly from the general public.


The fact that individuals would have higher levels of trust in neutral RAs over biased sponsored-disclosed RAs indicates that individuals are more likely to trust recommendations that are sincere, over paid-for advertisements by a company where the motive for recommending the product may be for financial gain. In the digital age, we may not know who our peers are online, but there is a level of trust established with the majority or popular opinions. 

In regards to motives for consumer-focused businesses, this is an opportunity to create online communities for products. Glossier, a US-based cosmetics startup company, began as a platform where users share reviews on different beauty products. This evolved into Glossier-lined products, which were developed through the reviews on their platform. Although their business model has evolved to be more commercial-focused, the platform still exists. The members of the Glossier community are neutral RAs and have been integral to the development of the company. 

Ethical implications should be considered in the role of recommendation agents. In the example of the Fyre Festival, concert organizers paid social media influencers to promote that they will be attending the event, creating hype that is seemingly organic. While these social media organizers were paid, they did not disclose this fact to their fans; influencers were promoting a concept to the masses without knowing much about the event themselves. Eventually Fyre Festival fell apart, and some individuals believe that the social media influencers are to blame. In fact, the improper use of influencers is now the subject of a $100m class-action claim against the organizers. Thus, having sponsorship disclosure is also a matter of ethics. While this can be detrimental to a business, the practice better informs consumers.

Fyre Festival marketing


Hanel, P. H., & Vione, K. C. (2016). Do student samples provide an accurate estimate of the general public? PloS one, 11(12), e0168354. 

Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision support systems, 44(2), 544-564. 

Wang, W., Xu, J., & Wang, M. (2018). Effects of Recommendation Neutrality and Sponsorship Disclosure on Trust vs. Distrust in Online Recommendation Agents: Moderating Role of Explanations for Organic Recommendations. Management Science