The 5 most common Analytics Blunders

prtk.nayak

Prtk Nayak
1. Insufficient Investment : Most companies are under invested in Analytics. Big companies have millions of customers and hundreds of datapoints per customer. Such data can not be analysed using Excel or SaaS which takes two hours to implement. Intelligent and sufficient investment in Analytics can help companies maintain their competitive advantage in the long run.

2. Messy Data: Different platforms collect different data point in different structures. Combining all those data accurately and correctly is quite an uphill task and not being able to do that would only mean wastage of the financial resources taht companies expend in doing Market Research. Besides every data set has formatting issues and errors which needs to be dealt with also.

3.Ignoring the Complexity: For every brand, the number of non-converters are far more than the number of converters. It is very important for companies to understand what worked and what did not. This makes the task od data management and analysis more difficult by a factor of 10 or 50 or 99 or 999. Therefore we need to invest appropriately and assign the right people for the right task.

4.Need of Accountability: The key issue in branding campaigns is understanding the impact of a tactic on the ROI which is difficult. Most brands substitute ROI impact with surrogate measures like clicks, Likes, tweets etc. Actionable analytics are focused on your true business goals and not on surrogate measures whose value as business drivers are unknown.

5.Lack of Political will: The challenge of analytics driven marketing is that it requires commitment and alignment across an organization. There are no sacred cows, no pet tactics- if there are we need to recognize that that's exactly what they are, that there are reasons other than ROI maximization why we do them.
 
Hi Prateek, excellent post. I found point no.1 to be the most valuable. Indeed, without proper quantitative analysis of outputs compared to investments, it will be outright impossible to maintain proper efficiency in running a business. Company owners will never be able to run their businesses profitably for long, unless they dig deeply into analytics, pinpointing the aspects that need urgent attention.

As for point no. 2, I wonder whether decentralizing management of analytics between different branches of a company will work better, rather than collating all the data in a huge central data center and attempting to collate all of those. What do you think?
 
4.Need of Accountability: The key issue in branding campaigns is understanding the impact of a tactic on the ROI which is difficult. Most brands substitute ROI impact with surrogate measures like clicks, Likes, tweets etc. Actionable analytics are focused on your true business goals and not on surrogate measures whose value as business drivers are unknown.

I think this one is really relevant. If you are able to somehow truly measure ROI and business drivers, the role of big data and investments become very clear. Not only that, it acts as a catalyst to funnel growth and profitability.
 
What is Business Analytics?

Analytics is the systematic computational analysis of data. In the simplest sense, Analytics is Applied Business Statistics.Statistics is a collection of methods for planning experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions to understand underlying macro trends.

Applied statisticians apply their knowledge of statistical methods to a variety of subject areas, such as biology, economics, engineering, medicine, public health, psychology, marketing, and education.

Get a brief explanation on History of Analytics & detailed information on Competencies for an Analyst, Future and Careers in Analytics and Business Analytics Course.
 
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