Crowdsourcing is not a new idea. Crowdsourcing is all about taking a task and having hundreds, if not thousands or tens of thousands or even millions of people located all over the place, to handle that particular task. Crowdsourcing has often been equated with market research. Companies would crowdsource customer feedback or product evaluation and work with the data being generated.
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There’s a problem with using crowdsourding for marketing purposes because there are a lot of self-selection issues. Also, there are statistical representation issues. You might not necessarily get the kind of data that you need or that you should use. In the case of marketing, since crowdsourcing requires some sort of conscious action, the resulting data might not be all that good.
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That said, crowdsourcing through the power of mobile apps can be a great technology to invest in. There are all sorts of opportunities. First, data can be crowdsourced. Notwithstanding the problems with marketing-related data, there are other sorts of data that could benefit tremendously from crowdsourcing data gathering technology. These types of data don’t involve conscious actions. Instead, this data collection is all about macro data. You’re tracking patterns and you’re tracking behavior. As long as the privacy and legal concerns are taken care of, using a crowdsourced distributed model can work wonders as far as data collection is concerned.
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Another very important and potentially lucrative field for crowdsourced mobile apps is crowdsourced data processing. You can take a task and you break it down into small standardized pieces that doesn’t really take much time for people to do. It is very easy to send out this data processing task to a widely distributed group of people and have them process that data. Mobile app technology would then collate this data into a central location and piece it together. This can save companies quite a bit of money on hardware and infrastructure costs. Of course, this type of crowdsourcing initiative would make more financial sense in some countries but not with others.
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Finally, data analysis can be crowdsourced as well. There are a lot of data tasks that require a heavy level of human analysis. These data tasks cannot be automated. By using mobile apps to spread out small data analysis tasks to a wide distributed user base, companies can save quite a bit of money. Of course, the big drawback here is ensuring that the analysis and quality match the customer’s expectations. This can be done through software parameters. Make no mistake about it, there is definitely a lot of opportunity in crowdsourced mobile apps.
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