The Shared World espouses an economic model based on a peer-to-peer activity of selling, buying, or sharing access to goods and services facilitated by an Online Platform. From flight tickets to a ride, from finding a technician to booking a hotel to ordering groceries, you can get practically anything online by connecting to someone who offers what you need. The possibilities in a sharing economy are endless and it would not have been possible without Data Science and its ability to bring us together.
How does Sharing Economy Work?
Sharing economy simply relies on the concept of having a community based platform facilitating transactions between a pair of individuals, it ends up creating a ‘win-win’ situation for all the parties involved. For instance, AirBnB allows you to act as a hotelier by helping you monetize your unused living space. On the other hand, it allows a guest to find a great place to stay at a competitive price with an added warmth of being welcome at a home. There are numerous similar organizations that are leveraging sharing economy for offering services and creating a win-win situation for all the participants.
How Data Science Benefits Each Participant in a Sharing Economy
In a typical sharing economy model, there are three parties involved:
- The consumer
- The provider (of services or resources)
- The community platform
The provider has services, products or resources that he/she can offer to others for a price but that requires a platform where such offerings can be showcased. The community platform (such as Uber or AirBnB) provides them a place where they could advertise their offerings. In turn, the consumer can view, select and pay for the services/resources they would like to buy.
Let us see how data sciences help such a transaction:
For the Consumer
Big data analytics take into account your preferences, location, payment patterns, buying history, social connections and many other such parameters to give you the most personalized search results. It also analyses the attributes of the offering, the provider’s ratings and preferences in order to maximize the relevance of the search results. This helps you choose the best option without spending too much time looking at the less relevant options. Also, the analytics driven reports & dashboards help you compare various providers statistically in a way that helps you make the best decision.
For the Provider
A provider benefits by being able to reach their most likely customers, thanks to the profiling and segmentation enabled by data analytics. In addition, based on the analysis of various parameters, providers are able to apply intelligent pricing schemes & promotions etc. in order to boost their profitability. Also, because of an increased relevance of the consumers to the offering, chances of gaining better reputation also increases for a provider. Of course, various kinds of reports & predictions help the providers to make tactical & strategic decisions as well.
For the Community Platform
A community platform’s success is directly proportional to the trust instilled in them by the consumers and the providers. With the help of fraud analytics, risk scoring, fake reviews detection, customer profiling and analysis of their buying propensities, the platforms minimize the risk for the consumers as well as the providers. In addition, analytics help them connect the right people with the right counterparties, which results in an increased revenue by the community platform.
Increase Demand for Data Scientists
Each of the companies hosting sharing economy rely on the manipulation of data and algorithms to bring together the service providers and customer. For this, they need a team of data scientists, data science experts, data specialists and software engineers making the demand for data science experts at an all-time high.
So what does that mean for the future – community Platforms for Data Sciences?
The explosive growth of companies powered by the sharing economy makes it amply clear that sharing is the way forward and it is here to stay and grow. Not only start-ups but also larger players are increasingly embracing it because they foresee the benefits that come along. This means that Data Science skills supply shall continue to trail its demand by an order of magnitude.
In the wake of the above, Data Sciences community platforms such as Cogniticx shall continue to play a stellar role in bridging this gap by helping organizations hire analytics professionals, on Demand. Cogniticx leverages sophisticated algorithms while matching exceptional Data Science talent with unique client requirements. In the process helping clients hire analytics professionals while ensuring service providers get remunerated for their effort.