Retail data monetization is the process of using your companies transaction and customer data to optimize the way you make and spend money.
There are two different ways to monetize data:
Direct data monetization is when a company sells their data to another party. This can be done in many ways, such as in a package (ex. Data from 2015-2016), or as in giving access to a live feed of data as it comes in.
Indirect data monetization is where it gets more complicated. This is when a company uses their data to optimize their business strategy to be the most profitable. This could involve finding a cheaper way to do things, or using data to find among which demographic your product is the most popular and target your advertising more toward people who fall under that demographic.
Either of these processes can be applied to retail data monetization.
There are two main ways data is monetized indirectly. The first way is using data for cost reduction by increasing productivity or reducing consumption/waste. The second way involves using the data to improve sales or strengthening the customer base.
For example:
As you can see, there are many many uses for data in any business, and especially so in the retail industry. Retail data monetization is becoming the next big thing for any and all retail companies to invest in, and if they want to get ahead or stay ahead, they should make it a priority to utilize within the next couple years if they haven’t already.
Retail companies should realize that one of their best products, and most valuable assets in today’s world is data and data analytics. In 2015, the size of the retail analytics market was estimated to grow from $2.2 billion to $5.1 billion by 2020, with an estimated Compound Annual Growth Rate (CAGR) of 18.9%.
Here are the 6 major factors you and your company should evaluate:
Before a company can start monetizing their data, they need to upgrade their foundations. This includes their strategy, design, and architecture. It will help them build their platform to begin monetization effectively.
Data analytic companies can be externally sourced to provide help outside of existing capabilities. They may host tools or data providers that can get access to unique sets of data that may be otherwise unavailable.
Many companies struggle to monetize their data to its fullest extent, only about 1 in 12 companies do it correctly. By finding the right strategy, and delegating the efforts to be focused on the more valuable use cases, a company can gain access to a whole new source of income that many businesses have yet to discover.