Organisations are increasingly striving to be intelligent, giving rise to decision-making systems that are based on analytical business models. Big data, analytics, predictive decision making and intelligence are jargons that are thrown around frequently in board room meetings and strategy discussions.
However, according to a recent survey, conducted by Deloitte LLP, American Marketing Association and Duke Universityâs Fuqua School of Business, top marketers have reported a modest effect of analytics on improving the business performance. The capability of analytics and related decision-making systems, to give actionable insights, has been rated at an average of 4.1 on a 7.0 scale. This performance has shown only a minor increase from a score of 3.8 in 2014.
According to the CMO Survey, despite the lacklustre performances of analytics and decision-making systems, companies do not undermine the importance of data analytics in the decision-making process. This is evident from the fact that organisations will increase their budget allocation to analytics and decision-making systems by a whopping 198%. Now, what is the reason that despite a sub-par performance of analytics in improving economics, organisations are still planning to spend heftily on analytics? As illustrated by Harvard Business Review, two competing forces are causing this discrepancy:
The data challenge
The abundance of data is not correlating with performance improvement. In fact, according to the report, the cluttered and disjointed nature of data is hindering performance economics rather than augmenting it.
In digital marketing, data is disjointed and coming from multiple sources such as Google Analytics, Facebook, Instagram, Youtube, Twitter, LinkedIn, Performance Networks, Email Analytics and much more. Thatâs why the report stresses on integrating distributed digital data and understanding how data will ultimately be manipulated to give actionable insights. This problem has been articulated well with the following statement:
âAn irony of having too much data is that you often have too little information.â
Worse, as data grows, this problem compounds. Without the right analytic tool and a decision-making system, no amount of investment will translate to insights.
This is where iCubesWire Delta steps in for digital marketers. Delta, stemming from an organisation that is leading the digital marketing ecosystem in India for over a decade, has a unique approach to combat this data challenge.
iCubesWireâs approach in developing Delta began first from identifying the actionable insights needed by marketers and intelligent digital organisations. This is a fundamental shift in approach as we believe that companies should do two things to harness the power of analytics in their marketing functions. First, rather than create data and then decide what to do with it, firms should decide what to do first, and then which data they need to do it. âCapture data and pray.â
Once the engineering team of Delta knew what marketers needed, they knew what data sources to integrate and how to integrate them. This is when the team started pulling data from disjointed marketing platforms and started colouring the insights canvas. Delta creates an insights warehouse instead of just a data warehouse, i.e. the data is translated to insights and the analysts will know what to do with it.
The analyst challenge
The CMO Survey also found that only 1.9% of marketing leaders reported that their companies have the right talent to leverage marketing analytics. Good data analysts, like good data, are hard to find. Companies need to better align their data strategy and data analyst talent to realise the potential that analytics can bring to marketing managers. In the absence of talent, even great data can lie fallow and prevent a firm from harnessing the full potential of the data. Some of the characteristics that companies should look for in good data scientists are:
How can Delta help a good analyst?
One of the key requirements for a good analyst is the ability to communicate insights instead of data. Delta, having identified requisite insight categories for digital marketers, provides a robust platform with ready to use insights and reports with clear actionable intelligence. Delta is the best friend a good analyst needs. Automate multi-source reports, report on disjointed data sources, listen for social chatter, organise and measure influencer campaigns and much more.
To conclude, realising the potential of data analytics requires a proactive and strategic approach to identify what insights are needed and recognising data sources that need to be mapped, and suitable analytics tools. Companies need to invest in the right mix of data, systems, and people to realise these gains.
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