Predictive Analytics: A Retailer’s New Best Trend!

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Retailers are finding that the path to optimal and dynamic pricing and increased profit margins goes through predictive analytics. To properly capitalize on nascent scientific solutions, retailers have to: Determine how the technology fits into their company culture; integrate the technological capabilities with existing support systems; involve key company folks at many levels; find people able to perform the required analyses; work with the technology provider; translate the analytical outputs into insights; transform the insights into definitive business decisions; put the decisions into action on a regular, ongoing, basis -- the results being the highest level of inventory management and price optimization.  See "6 Powerful Paths To Profit Using Predictive Analytics."

Predictive Analytics Are A Retailer's Best Trend

It's essential for retailers to continually monitor data and analyze competitive pricing changes over time to get the true picture.  

Gone are the days of competitive pricing when some businesses underpriced, hoping to drive up volume by offering their product as the least expensive alternative. Pricing too low was really a dead end for everyone but those whose true position was EDLP (Every Day Low Prices) -- even Walmart, with its ability to operate on slim margins while banking on volume, finds it hard enough to remain competitive.

The main pitfall before price intelligence solutions, was that a retailer didn't know whether she/he was pricing lower or higher than his competitors, which resulted in thin or greatly decreased profit margins, as well as leaving money on the table unnecessarily.

Another downside (exhibited by most retailers) was pricing low on purpose or having sales too often.  But the most egregious problem of all retailers was that they were selling products at lower prices than they could have gotten had they been using the science of predictive pricing to maximize the use of their inventory.  

So as the science of predictive pricing gained momentum and respect, these questions pretty much answered themselves.  

How Innovative Predictive Analytics Boost Profit Margin  

With today's tools, retailers are planning ahead and avoiding unpleasant, costly mistakes; they are finding the hidden profits residing in their current products or services and optimizing their merchandising and prices accordingly.  

First, utilizing retail intelligence to gather the information and set it up for interpretation; then using specific tools for predictive pricing, price optimization, dynamic pricing, advanced trending, product lifecycle intelligence, inventory management, and more.

Retailers can focus on the profitability (or lack thereof) of every one of thousands and thousands of products, and know its performance, making best-selling items more valuable and competitive, placing products in the right locations where there is demand; and diminishing stock (inventory) where there is less demand. That includes the simple problem of finding the products on which they might be losing money -- and, unless they were a loss leader, fixing them immediately.  

Bottom Line For Your Bottom Line:

Using the science of intelligence, retailers can optimize products, pricing, and profits.

Each retailer, however, must march to his or her own drummer, do what is right for him-or-herself, set a strategic plan; involve the right people at the right levels; manage inventory well; determine what to charge optimally to make sales, follow and fine tune the results, and, as a result, increase sales, profit margins, and profit.   

And, a nod and a smile to Marilyn Monroe: Analytics really are a retailer's best trend!  


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Shai Geva, Co-Founder & Chief Technical Officer

About Author

Dr. Shai Geva is CTO and co-founder of Upstream Commerce. As a leading technologist with more than 25 years of practical experience coupled with a strong academic and research background, Shai is intimately familiar with web technologies and e-Commerce. Before co-founding Upstream Commerce, Shai served as Chief Scientist at Mercado (acquired by Omniture Inc., now Adobe), where he provided technology leadership, helping to formulate and realize the company’s strategy and vision. Prior to that, Shai served for five years in an elite technology unit of the Israel Defense Forces, where he was responsible for innovative system design and implementation. Shai holds a Ph.D. in Computer Science from Carnegie Mellon University and a B.Sc. in Mathematics and Computer Science from Tel Aviv University. He is co-inventor of two US patents and has a number of patent applications pending.
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