Data is the new gold. With each passing year, enterprises and other institutions are slowly realizing the value of data, so much so that companies are now profiting from it. While they are using data to improve their processes, some of them are selling data or wrapping their data around products and services. These wrapping helps in increasing customer retention and wallet share and boosting customer satisfaction.

Given the pervasive nature of the data, a little is known about data wrapping-which is a phenomenon or process of amplifying the value of the products by adding analytics-based features and experiences. This is one of the three keys ways to achieve data monetization (the other two being selling information solutions and methods to improve business processes and decisions). Wrapping can take the form of a data-fueled dashboard, report, alert, and benchmark, suggested next step, or automated action to help and delight customers with profitable results. This is done by giving them access or a platform to see spending-categorizations, automatic sound optimizations, and buyer insights.

There are some certain attributes make data wrapping a unique feature. These include conversion of available data into financial capital by prompting a lift in sales of a core product and delivery of wrapped products that adhere to qualitative standards on par to ones with an underlying offering. Since the product owners and managers control the wrap, it is them, who look after their products' overall feature and experience portfolio, not the IT team. And the costs and benefits of wrapping are evaluated within the context of the offering's profit formula to ensure wrapping activities are lucrative. Besides, here the users are the customers, not employees.

According to a 2018 research survey by the MIT Center for Information Systems Research (CISR), companies with high performance in data wrapping devoted to impressing customers with useful and engaging wraps, and adopted measures to quantify and monitor financial returns. These companies further, drafted features and experiences that follow the 4 A's, i.e.:

• Anticipate by perceiving customer requirements where wraps present predictive and proactive features

• Advice by using evidence-based decision making to provide data and insights, informing a customer's decisions.

• Adapt by arranging the customer needs in a crafted way for different environments and contexts.

• Act on solutions that will benefit the customers through integrated processes and behaviors.

The research also highlighted how companies could implement a perfect data wrapping strategy by following these steps:

1. Assembling a multidisciplinary team led by product. Here the product owners must analyze and comprehend a particular entity's cost breakdown and the customers whom they cater to, channels to respond to their needs, and identify the key problem are to mitigate them.

2. Design features and experiences that inspire customer action by meeting their requirements while saving time, money, and providing information. This is achieved by the previously mentioned four A's. An Australian company Cochlear's product, CochlearTM Nucleus® 7 Sound Processor, is an example that represents all these characteristics. Here, the sound processor's SCAN Scene Classifier processor anticipates the hearing shifts as people change environments throughout the day and adapts to new contexts, like a crowded street corner or quiet room. The feature then advises the end-user of optimal settings using an app; later, it acts by automatically adjusting its settings to deliver the best hearing for the conditions.

3. Measurement of the value. This further a two-step procedure where first the indirect value of data wrapping is captured with a mix of techniques like tracking customer usage, A/B testing, or controlled experiments and surveys or pilot studies. In second, companies have to pinpoint the source and magnitude of the value that they're capturing: how much and in what way does this help customers in acquiring usage, or creation of value with the product? Other parameters can be figuring out which metric to use for monitoring purposes both for firm and customer, and what to anticipate in return, this comprises of customer retention, acquisition, wallet share, or from the increased willingness to pay. The latter is essential as the company may not have visibility into exactly how and when a customer benefits and also for better results in the long run.

Data wrapping is evolving as a crucial element of a company source for the data monetization methodology while augmenting the product value proposition. Not only this seems promising, but it may also be soon be employed by companies seeking to differentiate products under threat of commoditization. Additionally, it also bridges the gap between the data analytics team and the managers. So, it is high time to invest in this culture.