Data-as-a-Service lessons from a company that was right about Trump

Data-as-a-Service lessons from a company that was right about Trump

Data-as-a-Service lessons from a company that was right about Trump
One company correctly predicted both Brexit and Trump’s victory, using data insights that most pollsters missed. This is how to make your own.

The US presidential election results sent shock waves around the world and led us to question the validity of political polls, one of the longest-standing and most prestigious data products. Those of us who watched the polls were told that Hillary Clinton was clearly in the lead. In 2016, The Huffington Post tracked 377 polls from 43 pollsters in the US through Nov. 7th, as visualized here. The model predicted that Clinton wasvery likely leading.  

This chart, as it appeared in theHuffington Post, combines the latest  opinion polls into  trendlines using a poll-tracking model and was updated whenever a new poll was released.

One South African company,BrandsEye,correctly predicted both the outcome of the Brexit vote and Trump’s victory. BrandsEye delivered a Data-as-a-Service (DaaS) product, amalgamating social media analysis, geolocation data and other inputs to create impactful insight that most pollsters missed.

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In my blog Creating your Data-as-a-Service Customer, Iexplained that Data-as-a-Service (DaaS) can be described as productized data-driven insight on demand. Going beyond the technology stack and into core business decisions, DaaS distinguishes itself from other ‘-as-a-Service’ products, because it enables data to become an active partner in human decision making.

Creating the a product that delivers actionable insights using the latest technologies can be very profitable, as I explained in my blog Turning Big Data Disillusionment into an Opportunity with Data-as-a-Service Products. 

The triumph of social media analysis taught us many valuable lessons about how to improve our existing data products by harnessing the promise of the new technologies. As data analysis becomes more sophisticated, many companies who do not see this as core to their business or do not have the means to build the requisite skillset in-house will look to providers of DaaS products.

Those who can proactively productize and scale technology at the peak of inflated expectations inGartner’s Hype Cycle for Business Intelligence and Analytics, 2016, such as Real-Time Analytics, Geo Spacial and Location Data, Self Service Data Preparation, Hadoop-Based Data Discovery and more can realize huge monetary and strategic opportunities.

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BrandsEye started collecting social media data in July 2016. In total, over 37.6 million conversations from over 4 million authors were collected for analysis. BrandsEye’s geolocation algorithms identified in which state the author was located, and finally the conversations from the battleground states were sent to the BrandsEye Crowd – a crowdsourcing platform trained to understand sentiment. As visualized onBrandsEye’s website, this method successfully predicted both the Brexit vote and Trump’s victory.

Non-response bias.

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