Inability to extract intelligence from the data will harm competitiveness, the company says.
Anyone involved in marketing knows the adage as old as advertising itself: “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” The reality may be worse though – not just a half, but an absolute majority of marketing budgets is wasted on customers that don’t generate enough profitability, says Peter Fader of the Wharton school of economics at the University of Pennsylvania.
The rise of big data and analytics technology promises to change that situation. Today, decision-makers are increasingly able to tell a wasted marketing budget from an effective one.
Nevertheless, few companies have what it takes to tap into big data riches, and the consequences may be dramatic. Singapore-based data science firm DATAVLT says that 99 percent of corporate data is wasted and never used to draw knowledge from it. Only one percent of the data companies collect and store is ever analyzed. This, according to DATAVLT, will cause as much as 96 percent of businesses that exist today to fail in 10 years.
Worldwide, big business is coming to realize the importance of data analytics. According to a 2017 Gartner study, “Out of 13 marketing capabilities, chief marketing officers [polled by Gartner] allocate 9.2 percent of their total marketing expense budget on marketing analytics — the most of any capability.” Only a couple of years earlier, analytics occupied 4th place in terms of marketing spending.
In absolute numbers, spending 9.2 percent of a marketing budget of, say, $10 million is $920,000, and not an uncommon price tag for data analytics projects. Amazon spends $7.2 billion on marketing worldwide, and data analytics is Amazon’s core competency. Data science truly becomes the secret weapon of large corporations to cut costs and anticipate customer expectations.
Smaller businesses in danger
But what kind of insight can $5,000, which is 10 percent of a marketing budget of, say, $50,000, buy? Right now, not much. “If you do not have five to six figure budget, you will not get anything of value out of the data”, said DATAVLT’s co-founder Michelle Yeo to Cointelegraph.
According to PayScale, a median data analyst salary in Shanghai, China, is around $14,000 a year. In Singapore, the same skill set is worth about $33,839 a year, without bonuses. This is a bare minimum expense required even to be able to analyse data with at least some sophistication. Expensive analytical tools add even more to the price, without any break-through results guaranteed.
DATAVLT says that if their predictions are correct, the first candidates for extinction are small and medium businesses.
Despite the doom and gloom, DATAVLT sees an opportunity for itself. The company targets its affordable Software as a Service (SaaS) data analytics product specifically to smaller and medium business, seeing the most potential demand in the Asia-Pacific region. It bets on blockchain as a cost-cutting tool. Even with a share less than 0.01 percent of the current market, DATAVLT plans to achieve a revenue of about $50 million in seven years.
In essence, DATAVLT’s platform crosses all available and relevant customer data, for example, services consumption, communication and behavior, with different external and open data sources. The engine takes into account economical, sociological, and anthropological information, and then correlates the data with behavioural inputs like profiling, tonality, and sentiment. The result of this correlation is data which is much deeper and analysis that is more meaningful, the company says.
“It is about empowerment. In an age where the norm is for large corporations to dominate, we can build something inclusive where independent brands can thrive and play a role in building the community together as an alternative. For that to happen, we actually have to help each other out”, says Michelle Yeo.
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Source: Cointelegraph https://cointelegraph.com/