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Dynamic Pricing in the Big Data Era

After the Thanksgiving marketing push, Black Friday online sales were up close to 20 percent in 2013 over the same period last year. For the uninitiated, Black Friday is the day after Thanksgiving that marks the start for the Christmas shopping rush.

As many brick and mortar stores remain closed on Thanksgiving, Black Friday is a great opportunity for eMarketers to earn profits. One of the greatest plus points as far as ecommerce sites are concerned are the various pricing options they present.

Customers love discounts and freebies. This is a universal truth. No matter what one may be able to afford, discounts or complimentary goods are always welcome. Maybe that is the reason “end of season sales” are so popular!

Dynamic pricing refers to the practise of pricing items at a level determined by a particular customer’s perceived ability to pay. Factors like competition, time of the year, the weather, etc, affect people’s moods and ability to pay. Our recent article on showrooming explained how customers go shopping to brick and mortar stores, find out what they like, and buy it online for a lower price.

Pricing, therefore is one of the most important factors that determine the sale of a product. In fact, dynamic pricing has become one of those latest trends that seems like it is here to stay. It is everywhere. And the easiest way to arrive at the correct price is through complicated algorithms. A retailer might frequently change the price of an item based on consumer demand, price fluctuations at a competing retailer, or even the time of day and weather conditions.

Competitive pricing is a trend that many big names already follow. Pricing for everything from airline tickets, electronics, to household goods and show tickets, vary from week to week, even day to day, just because of a few algorithmic predictions. These algorithms easily predict to the Marketer what the price of a particular item should be at any given time.

The price consumers pay for the exact same product can differ based on personal data collected through various means. In an industry where profit margins are thin, retailers are basing their prices on the behaviours and habits of their shoppers.

Electronics retailer Best Buy is a case in point. They have been using the dynamic pricing strategy as well. Customers can easily research prices online. Thus they should get an equally lucrative deal at their physical counterparts. As a matter of fact, the travel industry has been using dynamic pricing for years now.

The goal of dynamic pricing is to allow a company that sells goods or services to adjust prices on the fly in response to market demands. With the advent of big data analytics, business rules for price adjustments can be made more granular. By collecting and analyzing data about a particular customer, a vendor can more accurately predict what price the customer is willing to pay and adjust prices accordingly.

At IntelligenceNODE, we analyse your data so that you can set the right price for your products and target the right customers at the right time! Our portal will provide you with intuitive dashboards through which you can study your customers’ needs and deliver accordingly. For more information, or a free trial, see