Article

Susheel Kumar
Susheel Kumar 31 May 2016
Categories Data & Analytics

Big Data Tools & Techniques: What successful CMOs need to know?

Big Data has the power to divulge amazingly helpful patterns and trends that can go a long way in improving the various business strategies of a company. Organizations can utilize the unprecedented data generated by machine-to-machine interaction across the enterprise networks to analyze and improve the efficiency of the processes.

Big-Data-Tools-Techniques.jpgThe assessment of customer relationship in terms of dollar value projects the future cash flow from the affiliation. Leveraging Big Data, predictions can be modeled with maximum accuracy and erudition.

The colossal amount of data collected by businesses over the years refers to what’s known as Big Data. It could have been collected in various methods from the organization’s own processes or from the various channels of customer interactions.  Big Data has the power to divulge amazingly helpful patterns and trends that can go a long way in improving the various business strategies of a company. These strategies can drive growth and profitability and could help build their core competencies. CMOs can specifically harness its power to create astounding strategies by integrating it in the overall marketing strategy. This could help scale their business to new heights effectively and seamlessly.

The good news is that there exist several ways CMOs can utilize the Big Data techniques to accomplish their endeavors. Some of these effective methodologies are discussed below -

Machine-to-machine (M2M) analytics

The life-cycle of a product can be managed effectively by using M2M analytics. Organizations can utilize the unprecedented data generated by machine-to-machine interaction across the enterprise networks to analyze and improve the efficiency of the processes. The exhaust of massive data being generated by devices can be highly useful for data scientists to unravel the hidden patterns of consumer preferences and product/service propensity. These deep insights could help the marketing teams to enhance the attributes and features of their deliverables by accurately forecasting them. With this, they could inculcate them into the existing deliverables and address the specific requirements their potential customers are yearning for. Pro-active alerts could then be triggered at appropriate moment to interact with customers to promulgate the innovative features. The continuous cycle of regular product upgrades can help improve the products/services to an extent that they become highly customer-centric and functionally effective for the end-users, leading to enhanced customer experience.  

Data Source Integration

The disposition of Big Data calls for synthesis of disconnected data sources across various touch-points to be integrated. This can be accomplished using the innovative Touch-point Management technologies. The various desperate sources including point-of-sale systems, social and e-commerce platforms, etc., thereby are connected together. This results in a holistic view of customer-generated data like transactions, purchases and other interactions. The consummate acumen leads to innovative segmentation and refined personas that can be used to drive highly specific targeted campaigns to motivate consumers. The marketers can leverage it to foster the brand affinity and cultivate evangelism amongst their target-market segments.

Customer Loyalty Mapping

The ideal method to measure the level of customer’s allegiance to the brand, product or service is by employing the technique of Net Promoter Score (NPS). It is the statistics that forecasts the number of times your customer is likely to recommend your product/services to others. Big Data can be effectively leveraged to calculate a profound promoter score for a business. Depending on it, a favorable customer engagement strategy can be devised by marketers to drive goodwill and enthusiastic support from their existing clientele.

Customer Lifetime Value

The purpose of the metric is to assess the financial value of each customer by predicting the net profit attributed to the total future relationship. The assessment of customer relationship in terms of dollar value projects the future cash flow from the affiliation. Leveraging Big Data, the predictions can be modeled with maximum accuracy and erudition. It helps in precise forecasting of upper-limit of expenditure for new customer acquisitions and to quantify the lifetime value. It can be further leveraged to quantify customer preferences by accurate formulation of reports, and also summarize outcomes of past activity. Marketers can use it as a vital element in the payback calculation of total advertising expenditure in the overall marketing mix modeling.

Innovative data sense assimilated with business acumen from Big Data can be employed to strike right balance of analytical agility. The futuristic insights conjured by the various techniques can help the CMOs to parse the patterns to enumerate data-driven intelligence. They can then utilize these valuable insights to drive actionable results.

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