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Data-Monetization

Monetizing the Digital Consumer through Data

Applying the organizational data to better segment and target products and services to digital consumers drives additional revenue for the organization.

datamonetization

Monetizing the Digital Consumer through Data

The digital world has paved way to interactions that have taken multiple dimensions. It is vital that we understand that these customer interactions can be monetized to increase ROI of any company. As capital plays an important role, the sustenance and prosperity of any enterprise depend on how it opts for various strategies to increase the #revenue; also how it recognizes the irrelevant operations to reduce cost.

In such a scenario, #data plays an evident role. Especially with respect to #monetizing the #digitalfootfall, decisions must be made with optimum strategy, taking into consideration the influence that data has on revenue generation. The digital world witnesses zillions of clicks each day. Consumption of information on the digital globe is increasing at an unprecedented rate. These are stored in CRM tools, ERP applications, point-of-sale systems, e-commerce systems etc. Various top-class companies across the world have already opined that the knowledge-information flow doubles at a pace that is unimaginable. AI and Internet of Things (IoT) merge together to create tech-driven systems for better businesses.

But what exactly can organizations do to indulge in revenue-generating strategies that benefit their company? In this regard, a thorough understanding of the digital presence of customers will lead to appropriate #decisionmaking. Irrespective of the intensity of your company’s engagement, tapping your digital customer data to generate revenue involves factors you must not ignore. Here are 3 significant ones.

1. Data Operationalization:

It is important to focus on understanding your customers in depth. The quality of data does this job for you. From a humongous bank of data, we need to segregate or sort the relevant data for quality analysis. If you are able to map the interactions into varied categories, you will be able to operationalize the data in order to design strategies for customer-specific products/ services. Thus, the foremost step of monetizing your digital data is to analyze the quality of it, and thereafter, focus on operationalization.

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However, bringing the data from various sources can be a daunting task. Data exists in various destinations. Therefore, understanding the true implication of IoT is crucial. By putting the data together to create systemic structures for actionable procedures, you will be able to make the way forward. AI helps in this regard to a great extent. Many companies have thus leveraged data to manage it to put it for the best use.

2. ROI and Risk Management

If you have carefully charted out the Return of Investment (ROI) for your company, then you might as well take steps for risk management. Businesses across the globe make the mistake of not assessing risks, thus missing on the probable outcomes of the investments. Your overall business strategy will largely depend on these factors. Hence, making a calculative move is what decision theory is all about. 

#Datascience comes into the scenario here. For you to turn the data into something concrete for the business is something that cannot be separated from ROI or risk management. Understanding economics from the perspective of behaviour will also help in this regard. Until you engage in the process with such a perspective, monetizing the available data might seem like an unachievable task. As you would weigh the pros and cons of different strategies for your customers, taking into consideration, the probability of the success will also add to your constructive decision architecture, in turn enabling higher revenue for your company.

3. Target-Market Study & Segmentation

A variety of approaches in consumer analytics will help you to not only keep the privacy of consumers intact, it will also do the job for you. Developing look-alike audiences is a great strategy. It demands the tracking of customers through various tools of data science like lifetime value, propensity models, loyalty programs, segmentation, customer communities etc.

A reliable analytics technique is thoroughly studying the target market and implementing segmentation of customers. By grouping your customers into the correct segments, you could engage in a specific strategy for enhancing sales, with the right target group in mind.

For instance, various dimensions of an economic segmentation may be income, education, location, gender etc. #Monetizing by using such segmentations would help you to increase the overall sales cap of your company.

Remember that you can transform your company’s position by accurately leveraging on the digital consumer data that your company generates. Your success very aptly depends on the kind of revenue you generate by monetizing data, which is the new power. If you want to stay ahead in the competition, you will have to figure out what works best for your company. Once you are through with that, using these to #monetize your #digitaldata is the way!

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