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The Use Of Data In Modern Strategy Creation

Are you making the most of the data you have when you are creating new company strategies?

22Oct

Strategy essentially comes down to customers and revenue. However, customers don’t just stroll towards your product and services by chance. They’re attracted to your business’ marketing and how you’ve managed to approach them so they are compelled to buy your products. For all of this to happen, you need to build modern strategies. And what is a strategy without data? It’s nothing.

Just five or maybe six years ago, there were a number of companies that made it an ethical practice to track and store all information pertaining to their daily transactions in their own databases. They used this stored wealth of information to analyze future market trends and predict the needs of customers today or two days from now.

But that was a long time back. Now both factors (data and sources) have become huge. So huge, a business can gather click-stream data regarding any and every potential customer/client interaction with a website. It has also enabled marketing specialists to gather valuable information pertaining to what each customer is saying about their products/brand/services on the web. The question is what makes all this possible? The answer is a bunch of new processes combined with intelligent technology and varying mechanisms which have been given one point of reference and that is ‘Big Data’.

Here are some ‘Big Data’ elements which have made the creation of modern business strategies possible:

Performance Supervision

Performance supervision entails a comprehensive understanding of the workings of Big Data through the incorporation of preset queries and multiplatform and multidimensional evaluation. The primary source of data for this sort of analysis is purely transactional, for instance, decades of customer transactions and activities, information pertaining to inventory and fluctuations in turnover. And with the help of this, business leaders and managers can now pose a question, like ‘of all the customer segments which ones bring in more revenue?’ And they can get their answers instantaneously and in real-time. This helps them make better short and long-term business strategies and decisions.

Deep Sea Data/Information Exploration

Data mining and exploration involves the integration of complex and sophisticated statistics in order to get answers to problems and questions they could’ve thought of earlier. This method influences foreseeable modeling strategies and techniques which can be used to gather information about customer/user behavior primarily based on past transactions and predictions. This amalgamated analysis can be utilized to divide customers into categorized groups by identifying buying characteristics a company’s analyst might have failed to spot on his radar. Data exploration can now let managers and business leaders develop effective strategies to keep their most profitable customer segment and reduce the customer churn rate.

Social Analytics

The social analytics measurement in Big Data mainly calculates the massive amount of non-transactional data. Non-transactional information mainly exists on various social media networks, including Facebook, Yelp, Twitter and Pinterest. It evaluates three important non-transactional factors, namely awareness, engagement and market reach. The awareness factor oversees the total number of reviews, videos and other mentions on a given social media platform by members.

The engagement factor calculates the frequency and repetition of activity among social media platform users. Last, but not the least, the reach factor measures the degree to which social media content is spread and circulated across wider platforms and with them, to other users.

So, as you can see, these elements which combine to form Big Data are the driving force behind the successful initiation and implementation of important and critical business strategies and because of which businesses thrive in modern times.

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