We use cookies, including third-party cookies from Google to serve personalized ads through AdSense, to operate this site and understand how it is used. By continuing to browse, you accept this use. See our Privacy Policy and Terms of Use for details, including how to opt out of personalized advertising.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
    What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
    7 Min Read
    chatgpt image jul 21, 2026, 04 34 30 pm
    4 Core Benefits of Predictive Maintenance after Vibration Analysis
    10 Min Read
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results -- AI-generated illustration
    How Does Data Mining Boost Customer Satisfaction in Logistics? Harnessing Analytics for Results
    11 Min Read
    chatgpt image jul 13, 2026, 04 23 45 pm
    How Data Analytics Helps Companies Improve User Engagement
    19 Min Read
    chatgpt image jul 13, 2026, 03 59 46 pm
    How Data Analytics Improves Multi-Location Search Strategies
    10 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Ignore Your Business, Rake in the Profits
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > Ignore Your Business, Rake in the Profits
AnalyticsBig DataData MiningModelingNew ProductsPredictive Analytics

Ignore Your Business, Rake in the Profits

BillFranks
BillFranks
6 Min Read
Ignore Your Business, Rake in the Profits
Illustration generated with FLUX.2 [klein 4B] via Cloudflare Workers AI.
SHARE

Want to uncover interesting ways to drive value from data? Most organizations focus primarily on internal opportunities that support their business, such as understanding customers better, determining how to more effectively price and promote products, or figuring out how to make the supply chain more efficient.

Want to uncover interesting ways to drive value from data? Most organizations focus primarily on internal opportunities that support their business, such as understanding customers better, determining how to more effectively price and promote products, or figuring out how to make the supply chain more efficient.

More Read

Why This Snaky Python Language?
Why This Snaky Python Language?
Analytics at Google: Great Example of Data-Driven Decision-Making
Why Business Intelligence Software Is Failing Business
6 Ways Big Data Hadoop Is Helping America Become Energy Independent
Data Management for Better Business in the New Age

These are valuable, but in recent months I have seen a new, recurring trend popping up across industries that I believe is going to soon become quite common: Look for ways to provide value to external, third party stakeholders through analysis of the data that your organization initially collects just for itself.

This trend is about totally ignoring your own business. Don’t focus on your customer, your products, or your supply chain. Instead, take a step back and think about how the information that your company is collecting might be of value to third parties who may have nothing to do with your core business. Privacy considerations must be taken into account, of course, but in many cases adding value for a third party requires only aggregated data that doesn’t raise privacy issues.

At first this sounds a bit radical, but upon further reflection it doesn’t seem like such a stretch. A few examples include:

  • A cellular company leveraging its customers’ GPS data in aggregate to provide traffic status for a traffic or map application
  • A financial institution analyzing card purchases to provide more accurate measures of consumer-level market share to manufacturers and retailers
  • A farm equipment manufacturer leveraging sensor data and farmland yields to develop better estimates of the potential yield of land for investors

In each of the above examples, internal data is analyzed in a way that provides no value to the organization itself. However, the analysis does provide value that third parties would be more than willing to pay for. The data required was collected for internal purposes initially and is certainly still used for internal purposes. However, as analytics continue to become strategic, revenue generating endeavors, it makes sense to look for ways to add completely new revenue streams. Put another way: can your organization get into the data and analytics as a service business?

Note that I’ve discussed looking for unexpected value in data at other times as well. However, the context then was unexpected internal value, not the concept of unintended external value.

As outlined in “The Amazon Whisperer” from Fast Company, one company has built its entire business model around this concept. The fascinating article details a unique and different way of building a business. C&A Marketing studies customer reviews on Amazon and looks for mentions of product combinations that don’t exist. For example, multiple buyers of a waterproof radio mention in their reviews that they wish there was a rechargeable, wireless version to go in the shower. Once identifying a product gap, C&A then manufacturers exactly what Amazon customers are asking for. C&A is now a nine figure business!

What is most interesting to me about C&A Marketing is that they don’t stick to a specific type of product. They pursue any opportunity where there is a product gap not being served by the larger vendors. In traditional retail, it wouldn’t be possible to get the distribution and brand recognition required to succeed. However, a key quote from the article is, “On Amazon, the consumer doesn’t look at a brand’s full line of products; she looks at Amazon’s full line, meaning a tiny company with one [product] can compete against anyone.”

“The Amazon Whisperer” example is a little different in scope than a large organization using its own data to find new external opportunities. However, the mindset is similar. It is about stepping outside your own view of the world and what you were thinking of offering to the world and instead looking at what the world wants. From the conversations I’ve had with clients, I am convinced that some of them are going to make quite a bit of money in very unusual and unexpected ways by following this path.

To get your organization heading down the path, I suggest a very simple starting point. Bring together a few people for several hours. Bring an inventory of the various data sources your organization has access to. Then, brainstorm ways that the analysis of that data can be of value to anyone except your organization. Don’t talk about understanding your business with the data, but rather talk about what opportunities the data can support for others outside the organization. You might just find some very intriguing ideas to pursue.

Share This Article
Facebook Pinterest LinkedIn
Share
ByBillFranks
Follow:
Bill Franks is Chief Analytics Officer for The International Institute For Analytics (IIA). Franks is also the author of Taming The Big Data Tidal Wave and The Analytics Revolution. His work has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to small non-profit organizations. You can learn more at http://www.bill-franks.com.

Follow us on Facebook

Latest News

Flat editorial illustration: The article describes an AI safety incident where an agent bypassed sandbox controls by exploiting D
OpenAI Pauses Advanced AI Work After Agent Bypasses Sandbox Controls
Artificial Intelligence News Security
Flat editorial illustration: The article explains that training robots for physical interaction requires three distinct data cate
Physical AI: What Data Do You Need to Train a Robot?
Artificial Intelligence Exclusive Robotics
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers -- AI-generated illustration
What Kind of Problem-Solving Distinguishes Data Analysts From Software Engineers
Analytics Big Data Exclusive Software
Flat editorial illustration: The article examines AI agents that escalate from legitimate data retrieval to attempted intrusions
OpenAI’s Government Website Incidents Raise a Hard Question for AI Agents: When Should They Stop?
Artificial Intelligence News Security

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

eCommerce Brands Use Big Data for Logistics and Fulfillment Warehouses Protection
Big Data

eCommerce Brands Use Big Data for Logistics and Fulfillment Warehouses Protection

10 Min Read
The Top 5 Email Analytics Tools
Analytics

The Top 5 Email Analytics Tools

6 Min Read
Turning Geographic Data Into Competitive Advantage
Big DataExclusive

The Rise of Location Intelligence: Turning Geographic Data Into Competitive Advantage

5 Min Read
Trading Up: The Shocking Evolution Of Data Analytics In Online Trading
Analytics

Trading Up: The Shocking Evolution Of Data Analytics In Online Trading

5 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence
ai chatbot
How AI Website Chatbots Improve Customer Support and Lead Generation
Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-26 SmartData Collective. All Rights Reserved.
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?