6 Ways To Use “Big Data” To Increase Operating Margins By 60% – Part 2

In my recent post, “Why Harnessing ‘Big Data’ Is The Next Big Thing in eCommerce (Part 1)”,  I talked about extraordinary opportunities coming with “Big Data” --  or "the drift toward data-driven discovery and decision-making,” as the New York Times calls it. In Part 1, I talked about the implications and insights of harnessing “Big Data,” such as: Using existing data more efficiently, driving higher conversion, improving and automating decision-making, and innovating new business models. The successful retail businesses will be those who tease important insights and information out of "Big Data" to facilitate and enhance their competitive pricing, competitive pricing analysis, strategy, planning, personalization, and so forth.  

Search engine and social media companies have been trying to figure out how to capitalize on the tons of accumulated data they possess, not only to create more value for their users, but how to monetize that value.  (They've discovered that it’s not as easy as it sounds). “The winner,” according to new Yahoo President/ex-PayPal CTO, Scott Thompson, “will be he who has more data and who knows how to use it better than anyone else.” 

Ways Big Data Will Be Harnessed By eCommerce:

1. To increase operating margins. In a report last spring by the McKinsey Global Institute (MGI), senior fellow Michael Chui discusses how the scale and scope of companies' access to data is changing the way they do business. “The use of big data will underpin new waves of productivity growth and consumer surplus," Chui says. "For example, we estimate that a retailer using big data to the full has the potential to increase its operating margin by more than 60 percent.”

2. To segment populations to customize actions. We already know and use geographical segmentation -- "the demographic categorization that companies use to group individuals into broad target markets." The use of Big Data will provide the opportunities for more refinement, for specific targets. (Previous posts on price segmentation). 

3. To practice individual targeting/personalization. “Big data allows ever-narrower segmentation of customers and therefore much more precisely-tailored products or services.” This newer, tantalizing set of information will come from drilling down on the vast quantities of “Big Data” about customers’ purchases, behaviors, and personal information, gleaned from search-site records, people’s wanderings and postings on social media sites, credit card transactions, GPS devices embedded within smart phones, records kept by companies, government statistics, and so on. 

4. To provide added value. A large farm chemical company in Canada generated real-time information for farmers, on when to apply the chemicals for greatest crop yield. What the company did was have a data analytics firm design a mobile app, cross-reference its customer purchase data, pair it with information on real-time weather patterns, and provide the information directly to each customer in a timely fashion. You can think of ways to apply this kind of value to your own business or industry.

5. To reward customers for good behavior and increase their loyalty. When Bloomspot, in imitating Groupon and Living Social, found that too many people merely took advantage of discounts and never patronized the merchants again – Bloomspot (with permission) sifted credit card data to find the spending records of the most valuable customers -- and rewarded them with follow-up offers and benefits.

6. To improve the development of the next generation of products and services. Manufacturers are using data obtained from sensors embedded in products to create innovative after-sales service offerings such as proactive maintenance (i.e. preventive measures that take place before a failure occurs or is even noticed). 

Big Data, Big Takeaway:

New and effective eCommerce insights are coming from a vast storehouse of information called “Big Data.” A competitive intelligence company like Upstream Commerce presently collects and provides pricing, product, and other helpful information for a variety of clients.

On the "Big Data" level, accumulated information will be compared across a particular industry, and also across different industries, to provide further insights and calls to action on a bigger plane. Take, for example, a mass merchant. The time is upon us when we will not only provide the basic pricing and product information, but valuable additional data, such as statistics and analysis, showing the retailer that he’s changing prices 20% more frequently than the market, for example; or that he’s priced 30% below the market average.  

Pricing intelligence and pricing intelligence tools, already indispensable, will become even more valuable -- for collection and analysis of data; providing shortcuts to turn data into insights; and establishing valuable benchmark data. These added values will keep retailers first in developments, techniques, and tools to help them lead change into the future.  And remember, the more data available, the more effectively you can price -- and profit.

What do you think about “Big Data” and “The Industrial Revolution Of Data”? Let me know how you've tapped “Big Data” for your business.  Thanks. Gilon

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Gilon Miller, CMO

About Author

Gilon is a seasoned marketing, sales and business development executive with over 15 years of experience in the software and Internet business. He is the Founder and CEO of GuruShots. Previously, Gilon was the CMO of Upstream Commerce, VP of Marketing at iMDsoft and Director of Global Marketing at SAP. He earned an MBA at the MIT Sloan School of Management and a BS in Electrical Engineering from Tufts University.
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