Telecommunication, Technology & Media - January 14, 2010

Best Practices in Mobile Crowdsourcing

Successful crowdsourcing by prominent online service vendors such as Threadless, InnoCentive, iStockPhoto, Google MapMaker and Building Maker are now inspiring similar crowd-based concepts in the mobile world. What are some of the best practices for the mobile space?

The unique benefits of mobile technology in ubiquity, media convergence, and global mass reach will continue to drive new, innovative crowd-based service concepts over mobile. Some innovative start-ups or projects include:

Cooperative traffic - Google Maps and Waze are notable examples by crowd-sourcing traffic congestion information from drivers’ GPS-enabled mobile phones.

Geo-social networking - Google Latitude and Loopt generate social networks supported by geo-location features, while Twitter exemplifies the best practice of real-time content streams.

Product testing - Companies such as uTest and Mob4Hire employ crowds to test newly developed mobile applications and provide feedback on functionality, load and performance, and usability.

User-generated content - Emerging mobile video sharing applications services such as Qik and Kyte tap on crowd sources to generate a large variety of content much similar to the role of YouTube on PC.

User experience optimization - A similar trend of passive or subconscious crowdsourcing is also occurring as information vendors such as Google increasingly integrate and analyze mobile usage data extracted from the ‘crowd’ and use the information to help refine and optimize their user experience, such as personalized search.

Leveraging mass reach - Innovative services such as Google’s SMS Channels and SMS Trader bridge the digital divide by creating a mobile platform for user-generated content and person-to-person trades in emerging markets such as India and East Africa, where these types of services are otherwise unavailable on PC.

It is interesting to note that the examples listed so far partly or completely  leverage the demand for ubiquitous real-time streams, converged multimedia capabilities, and the mass reach of mobile phones:

Best Practices in Mobile Crowdsourcing Diagram


Rules of engagement for mobile crowdsourcing

To succeed in mobile crowdsourcing, service vendors need to clearly consider and effectively leverage at least one or all of the described mobile-specific characteristics, instead of simply looking to save development costs, seek user-relevant content, or quickly ramp up operations and offerings.

However, not all services are suitable for the mobile platform.For successful implementation, mobile service providers must take into consideration ‘platform’-based service positioning, value-based monetization and flexible business models often based on ‘open calls’.

‘Platform’ positioning for free services

Most of the above mentioned service examples position themselves as a service platform or market place, rather than content publishers, vendors or mobile retailers. This is an important success factor as it gives users a sense of ownership and incentivizes them to contribute information, content, or volume to the service. 

Even in the case of iReport, where CNN purports to hold the right to edit, withhold, and license the submitted content, the company maintains the platform positioning and does not actively edit every upload both in order to retain the originality of the content and to avoid unnecessary personnel costs.

Perhaps the only exceptions are fee-based services such as uTest, Mob4Hire, and txteagle, where corporate customers pay for the vendor to deploy their crowd resources to conduct application testing and localization. In these cases, the services tend to hold a more proprietary interface and act as a strict intermediary between the customer and crowd testers for commercial purposes. Here, the crowd is incentivized by financial rewards and is less concerned with gaining an audience (eg. iReport, Google SMS Channels) or social interests (e.g. Google Latitude, Google Maps traffic data).

Monetization by value

Most mobile crowdsourcing services are currently at a build-up phase and some may not yet have a clearly defined monetization model especially if they represent a breakthrough concept (e.g. Twitter, Qik).

Generally, the commercial model needs to take into account the service value proposition and there does not appear to be a one-size-fits-all model. On one hand, Mob4Hire and uTest directly compete against incumbent testing service providers by offering similar billing models, while others such as Google Maps and CNN iReport hope to monetize their services indirectly by integrating with their larger service platforms and ultimately monetize through advertising.

In many cases, some services hope to first build up the user base before entering into monetization (e.g. Google Latitude, Waze, Loopt).  If the service is to be fee-based, it is essential to clearly state payment terms and schedule in order to avoid user confusion.

Service evolution

An inherent challenge in building a successful mobile crowdsourcing service lies in managing content diversity and mass appeal.

As a pioneer in crowdsourcing services, Google tends to opt for an organic product development approach by experimenting with interface features or even service features over time within Google Labs. To date Google Maps traffic, Latitude, SMS Trader all reflect such a mentality, while even more refined and commercialized services such as uTest also took years for its service concept to evolve.

Organic quality control

Ultimately, the quality of a crowdsourced community is policed by the community itself. For fee-based services such as uTest, Mob4Hire, and txteagle this is particularly important since quality is often the number one concern for prospective customers of their services. Like the online examples such as eBay, these companies typically implement a rating system customers would rate the performance of the testers employed for projects and those that receive consistently poor ratings will cease to receive new project offers. The rating system could also be implemented by more media-centric crowdsourcing examples such as Qik, iReport, Twitter, similar to YouTube online, and the goal there is often more to increase content relevance and appeal.


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