Plugging Big Data Into Small-Scale E-Commerce


Back in March, we talked about the way large-scale businesses can use big data and analytics to determine optimized pricing for products and personalized pricing for select customers. What's a small-scale Amazon merchant to do, though? It's easy enough to check competing sites and set prices slightly lower, but that's a losing strategy, unless you're watching them 24/7 and you don't mind chipping away at your margins until they're gone.

Enter Feedvisor, an algorithmic pricing engine delivered via a SaaS model. Any Amazon merchant can sign up and grant Feedvisor access to its e-commerce backend, and then the software begins optimizing prices automatically.

The trick, according to the site, is not to set prices lower but to tweak prices based on seller rating, inventory available, and dozens of other variables. The goal is not to undercut any particular competitor but to "win the BuyBox" as often as possible. From the site: "As well as checking your competitors' prices thousands of times an hour, Feedvisor takes into account their shipping options, available stock, seller ratings, and a multitude of other variables that Amazon looks at when calculating the BuyBox."

In addition, the software considers historical pricing trends when formulating its models, and it learns from each successful or failed transaction, so it's constantly refining its algorithm to suit each customer.

The software is so impressive that Feedvisor won a Best of SaaS Showplace Award this week from the Cloud Computing Showplace, a vendor-neutral site hosted by the consultancy THINKstrategies that delivers insight around cloud providers.

The rapidly growing and thoroughly confusing cloud services market is a quagmire of unreliable information and competing claims, and the Showplace aims to cut through some of that hype and help businesses navigate their cloud journey more smoothly.

In a press release on the award, THINKstrategies highlighted one Feedvisor success story. Vanko Trading Inc., which maintains several retail websites, reported a 50 percent increase in profits after implementing the software. Steven Kirchhof, an executive at Vanko Trading, said in the release:

The Feedvisor algorithm determines the best possible price, balancing sales volume and profit margins. With Feedvisor running in the background, we can concentrate on the other aspects of our business, trusting that our prices are being continuously and automatically optimized.

Feedvisor not only sets pricing dynamically, but it also balances inventory to ensure that high-selling products don't deplete supplies. It also masks remaining inventory from competitors, so merchants can decide how much of the kimono to open, depending on varying conditions.

The best parts of any SaaS tool are the subscription pricing and the fact that it can be set up in minutes. Feedvisor offers a pay-as-you-go model, and it takes a percentage of each successful sale. If profits go up at rates similar to Vanko Trading's, it's well worth the investment.

Members, what do you think? Is anyone else providing this kind of service? Is price setting best carried out the old-fashioned way? What variables do you consider when setting prices? Share your insights below.

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— Michael Steinhart, Circle me on Google+ Follow me on TwitterVisit my LinkedIn pageFriend me on Facebook, Executive Editor, AllAnalytics.com

Michael Steinhart, Contributing Editor

Michael Steinhart has been covering IT and business computing for 15 years, tracking the rising popularity of virtualization, unified fabric, high-performance computing, and cloud infrastructures. He is editor of The Enterprise Cloud Site, which won the Least Imaginative Site Name award in 2012, and he managed TheITPro.com, a community of IT professionals taking their first steps into cloud computing. From 2006 to 2012, Steinhart worked as an executive editor at Ziff Davis Enterprise, writing and managing research reports, whitepapers, case studies, magazine features, e-newsletters, blog posts, online videos, and podcasts. He also moderated and presented in dozens of webinars and virtual tradeshows. He got his start in IT journalism at CMP Media back in 1998, then moved to PC Magazine, managing the popular Solutions section and then covering business technology and consumer software. He holds a Bachelor of Arts degree in communications/journalism from Ramapo College of New Jersey.

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Helping Amazon or Sellers Increase Profits?
  • 10/30/2013 10:45:24 AM
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It would seem to me that the programs described are mostly going to benefit Amazon, helping to push prices downward and seller compete in the online market, usually by lowering prices as recommended by the program as it sees lots of competitive pressure.

Sellers may think this is the best thing since slice bread, since it seems to scientific and all, but just look who's leading the way and promoting the idea....Amazon.

Great idea
  • 10/30/2013 10:43:43 AM
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This product sounds like a great idea. It helps a merchant win orders, at the best price he can get at the time. This is soo much smarter than just having an everyday low price.

Re: Pricing strategy
  • 10/29/2013 11:07:15 PM
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That chaos can multiply depending on the analytics application for mobile - I am reviewing features set for two solutions and realized that analytic data is not sent in real time in some conditions.  So it can be possible to miss some data that is important to a trend.  I need to understand more fullt, but it begs the question of how much delay is detrimental given the push for remarketing strategy. 

Re: Perfect information
  • 10/29/2013 6:24:02 PM
NO RATINGS

 

Maybe it's time to invent the "limit order" for purchasing items from online retailers.

Limit orders are used for stocks.  Imagine, for example, that a certain stock is worth $17 (to me), but it's currently selling for $20.  I can place an limit order to BUY that stock at $17. Then I can go away and forget about it - if the price dips to $17 anytime in the next couple of months, my order executes and I've bought that stock.

So, how much is toothpaste really worth?

 

Re: Pricing strategy
  • 10/29/2013 2:27:09 PM
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:) It could also create chaos of your favorite toothpaste is changing prices every five minutes.  

Though, this technology is needed, especially since consumers can compare prices online in real tie. 

Re: Perfect information
  • 10/29/2013 12:24:58 PM
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That's interesting, Jeff, but in this case, the analytics are working in favor of the seller, not the buyer. What kinds of programs are available to the purchasing side of this equation?

Re: Pricing Psychology
  • 10/29/2013 12:23:49 PM
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Very interesting, Beth. Do you think large-scale brick-and-mortar retailers will start adjusting their prices on the fly, now that they have access to historical and national sales data in real time? That would make for an awfully confusing shopping experience. Nowadays the retail sales cycle is at least a week or two, right, from the time an advertisement hits to the time the sale period ends.

Re: Pricing strategy
  • 10/29/2013 12:20:12 PM
NO RATINGS

That's spot-on, Seth. And that's why a program that can adjust pricing from one minute to the next can help merchants leverage the unique features of online selling. It's almost like bringing real-time market fluctuation data to ecommerce.

Perfect information
  • 10/29/2013 11:18:32 AM
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This reminds me of those finace/econ classes where they say that the price is set by all the known information, and if you have perfect information you won't over or under pay for a stock or anything on an open market.  Seems like we are getting closer to this situation.  Perfect information, disseminated to all will send all the middle men and scammers scurrying.

Re: Pricing Psychology
  • 10/29/2013 10:29:32 AM
NO RATINGS

@SethBreedlove -- this reminds of some of the points raised last week at a conference session by Ted Rudman, who is the interim vice president for pricing, marketing/loyalty, supply chain, and corporate systems at Sears. The point he was making is that traditional retailers couldn't ask too many questions relative to pricing because they didn't have a way of storing all the data on all the price points for all the merchandise they sell (or, more to the point, storing it in a way that wouldn't be exorbitantly expensive and hugely difficult to access). At Sears, bringing in Hadoop has meant the ability to save everything, including all those price points, so business managers can ask as many questions they want about pricing and selling. Interesting stuff. 

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