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Home»For Buyers»Retail News»Increasing Retail Sales with Data Analytics
Retail News

Increasing Retail Sales with Data Analytics

Krystina MorganBy Krystina MorganNovember 26, 20194 Mins Read
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Retail data monetization is the process of using your company’s transaction and customer data to optimize the way you make and spend money. There are two different ways to monetize data: direct monetization and indirect monetization. 

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. 

illustration of digital customer dataIndirect 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  toward more people who fall under that demographic. Either of these processes can be applied to retail data monetization.

Retail Data Monetization: Why Should You Do It?

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:

  •     Use data to geo-target retail for specific locations
  •     Traffic and density planning for agencies, such as:
    advertising, government, transportation, city planning, and healthcare
  •     Detecting fraud in financial institutions and credit/debit card companies
  •     Targeted ads based on click insights for brands and advertisers
  •     Layout, location, and staff planning for retail stores
  •     IoT (Internet of Things) applications for a wide assortment of companies

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%.

How to Start Monetizing Your Data

Here are the 6 major factors you and your company should evaluate:

  1. Usage Rights: Do you and your company have the legal rights to re-use and sell your client’s (B2B and consumer) data?
  2. Readiness: Does your company have the required infrastructure? (IT, Sales, Service)
  3. Privacy: Do you and your company understand the privacy regulations pertaining to this data?
  4. Value Proposition: Do you understand how to value the data accurately in order to create a fair but profitable price for both you and your consumers?
  5. Timing: Are you a first mover among your market’s competitors? Are you at least in the first 50%?
  6. Market Share: How much of the market does your organization control?

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.

Christopher Rafter is the COO of Inzata Analytics, the first full-service data analytics platform powered by artificial intelligence for revolutionary integrating, exploring, and analysis of any kind of data from any source, on a massive scale. 

 

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