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What Is Data Wrapping And Why Are Companies Vouching For It

What Is Data Wrapping And Why Are Companies Vouching For It

While data has been used for long to improve processes or even benefit by selling it, a research scientist at MIT Center for Information Systems Research suggested a third interesting way that companies utilise data — i.e. wrapping their data around products and services. So, what does this data wrapping mean? 

While little is known about the concept until now, mostly due to ubiquity of data, data wrapping is primarily packaging the products with data analytics features and experiences that may benefit customers and increase profitability. The process gives access to relevant data to customers that they can explore to gain insights and make better decisions. It is aimed at increasing revenue, loyalty, customer satisfaction, and more. 

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Data Wrapping Is One Of The Ways For Data Monetisation

While companies have been monetising data in different ways, they are now sharing their data packaged as products to customers and partners. This mode of data monetisation is data wrapping and is being explored as one of the key ways to achieve monetisation. Some of the ways in which wrapping can be applied are data-fueled dashboard, report, alerts etc.

As the article suggests, companies are doing it to provide a better user experience to customers as it helps clients to understand the product and service a company has and use it to their advantage to increase profits and deliver better returns for shareholders.

It also highlights that some of the key points to keep in mind about data wrapping are that it is meant for companies’ customers, not employees, it is done as a part of products’ overall feature and experience portfolio, economic returns result from a lift in sales and not from internal business, and more.

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What Have Companies Done

Some instances where we have seen companies use data wrapping are BBVA and PepsiCo. In 2016, BBVA offered a personal finance management app to its customers, which was built on machine learning algorithms. It sorted customer transactions into categories such as rent, food, and entertainment. It then displayed the customer’s expenditures broken down as a simple chart. This was promoted by the company on its digital banking website as a way for customers to better manage their personal budgets. This quickly became the most utilised feature on BBVA website as it provided value-added recommendations for customers.

Similarly, last year, PepsiCo launched Pep Worx, a suite of data analytics capabilities. It helped customers successfully launch and manage innovative marketing programs, optimise total store space, help retail customers increase product turns, profits, and more. The capability developed over four years, helped the retail customers solve problems using data analytics-based shopper insights. Pep Worx was used by the company to help transform the nature of its retail customer relationships from transactional to collaborative nature.

How To Get Started With Data Wrapping

The basic requirement is big data and data science. It is a good idea to begin by focusing on preexisting business intelligence groups, data tools, and analytics talent for data wrapping. However, capabilities and processes that helped a company use data analytics better may not work for its customers. Therefore according to the research article, it is ideal to form a cross-functional team with Finance, IT, and any other area that can offer critical insight.

The next step is to design features and experiences that inspire customer action and help them derive the value of saving time, money or gaining important information.

The most crucial step is to measure the impact, which is a twofold process. Data wrapping can create value indirectly which can be measured by techniques such as A/B testing, surveys and pilot studies to get a sense of data wrapping outcomes. Second is for companies to pinpoint the magnitude of value that they are capturing. 

Some of the effective ways to do data wrapping according to the research article are: 

  • Anticipate customer needs
  • Advise with evidence-based decision making to help customers decide what to do
  • Tailoring and adapting to meeting customer needs 
  • Act in a way that wrap performs an action to benefit the customer
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