Data is the new oil in 21st century

Data is the new oil in 21st century

Guess what? Big Data is like the Sun in the solar system around which the whole planets (today’s businesses) keep revolving.

It literally means everyone is joining the bandwagon of data no matter a geek or CEO. Those who aren’t investing in data and analytics simply mean aren’t interested in their customers. If you are all into your customers, it’s evident to invest in this today’s day and age solution that not just gives much insight but paves the way for relevant information like understanding customer behaviors and creating a roadmap for success.


It’s not the real question whether or not you invest in data, but what matters all is Return on Data Investment (RoDI). Many CEOs can announce investing a whooping amount of money in data and analytics to just make analysts happy, but the real question is- will it help? Not at all, because, it is challenging to show a realistic output metric such as RoDI!


In order to monetize data, they have to take care of significant challenges like the business model they should follow the recipe which they need to transform data to value and equalizing data privacy and security with monetization.

Below mentioned are a few successful business models:

Leverage your customer base: If customers see their own benefits, they’ll come for your products and services again and again. Yes, that’s the mantra! At present, the most common model is to provide your customers a slew of free services to collect data from them. Further you can analyze this collected data and sell insights to other set of customers like marketers and advertisers.


You can see Facebook, Google and many other companies including advertising agencies reaping benefits from this model.

In order to implement this you require four things-

  • The first thing is a bulk of consumer data,
  • Second expert scientists who code algorithms to create consumer insights
  • Third is targeting platform to use these methods to drive value for marketers
  • And, fourth is the privacy permissions from customers.

Selling Data: Collect consumer data with the help of research, cookies, web crawling and other methods and just sell it to others. It’s also very common and not different from the sell audience’s business model. What’s the difference? Well, it depends upon the buyer of the data to get insights.


Selling insights: It means selling particular insights to particular segments for example; Trip Advisor will get you to subscribe only those data consumers provide you on your restaurant or hotel property. It means sell insights to business relevant entity.


Sell Transactions: It’s an emerging model wherein websites having a large customer base do not sell data but allow customers to click and directly transact or buy a service that they require or have been searching about. Hotel and airline booking sites like Travelocity and Expedia work on this model; however Google and Amazon have joined this bandwagon as well.


Selling more stuff: Make use of data to sell items to your existing customer base. For example, Amazon may recommend a particular stuff to its existing customers whenever they buy something related. How does it do that? Well, it analyses the histories of customers and then suggests similar products or provide something relevant based on their preferences. This model needs consumers data, talent and privacy permissions and the prowess to drive sales on your platform on the basis on these insights.


All the above discussed business models are common among internet biggies like PayPal, Google, Amazon and more. Traditional sectors like telecos, banks, retailers, hotels and others have a huge data, but it’s limited to information within their own enterprise. Also their approach to creating analytics is dependent on structured data analytics. What challenges they face? The data footprint across the enterprise if 90\\% of the total world’s data, and big data analytics implementing graph theory and more, on unstructured data such as images, text and so on is outside their proficiency.  


Therefore, whatever efforts they put at data monetization are limited to selling their data or their products to their consumers. However, they don’t adapt to new or innovative business models, but revolve around the customary ones.


The most common of all these is to build a data coalition. At present, there are many non-competing businesses that pool data to make a more comprehensive data set. They use this data set for their business model. If businesses do not have that much of expertise to deploy such a platform, they generally add a technology, analytics company to reap benefits.


Each of these models is actually an approach to data monetization. The basic ingredients remain the same we have been talking about- bulks of data, a great recipe and incredible talent of course!


You know what, at present there is more, more and more data than you can imagine and analyze and more people are hopping in the bandwagon to sell it in every form. Soon, data isn’t going to be an obstacle. Technology is no longer hindering the process of the open source system and as far as cloud computing is concerned it has made it available at most affordable prices.


The future will be within the reach of those who-

Make a clear business model considering data monetization. Employ talent willing to serve in the internet mode. The traditional way of doing a deep statistical analysis prior acting on the data has to be substituted by a more dynamic method, one that test numerous options in real-time and follows the data for further insight.


Creating a unique recipe, well it’s the hardest part. Developing a unique perspective on data so as to sever innovative use cases isn’t an easier one.

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