The Four Stages of Pricing Intelligence: Turning Numbers into Action

Mihir Kittur, Co-founder and Chief Innovation Officer, Ugam,

Price Intelligence, pricing intelligence, Dynamic pricing, Competitive intelligence This may sound obvious, but when you’re making a salad, it’s optimal to use the freshest lettuce, tomatoes and cucumbers available. No matter how good of a chef you may be, using wilted vegetables will result in a rotten salad.

The same principle applies to Pricing Intelligence data.

You need to refine your raw data so it’s ready for your analysts to turn it into real intelligence – inaccurate data will lead to faulty pricing recommendations.

Here are the steps that are needed to turn your numbers into action:
  1. Gathering Prices – Web crawlers continuously scrape competitor sites for products, model numbers, prices and other characteristics.
  2. Enriching the Data – Using automated tools and retail category manager expertise, your products are matched or “mapped” to the same or similar products sold by competitors.
  3. Analysis & Recommendations – Using historical sales data, retail analysts build pricing models that explain past performance and predict future trends. The pricing formulas determine the optimal price where sales and profits will be highest.
  4. Taking Action – Analysts recommend that prices be raised, lowered or kept the same based on competitor price changes and your own consumer demand and expectations.
Unfortunately, most pricing data is not ready to use when it’s first delivered by web crawlers. For example, computers can instantly compare the prices of every iPod in the universe as long as the UPC codes are listed. But given that Apple seldom discounts their products, the more significant question is: Which competing MP3 players are most comparable – which ones will be most likely to be attached to your customers’ earbuds if they go with Plan B?

Making matters even more complicated is that shopping for consumer electronics (and many other categories) often involves three sets of prices: Manufacturer’s Suggested Retail Price (MSRP), sale price and the secret “click here” price.

Many product pages on e-commerce sites show you their list price and then invite you to move your mouse over the item or click on a shopping cart to “See Price at Checkout.” The reason retailers do this is to avoid Minimum Advertised Price (MAP) violations. Some of the more premium brands forbid stores from advertising their products below a certain price threshold – to avoid cheapening their brand equity.

Many retailers have been happily using automated webcrawlers to gather competitor prices, but most of these tools are rapidly becoming antiques. Your technology now needs to “see” these hidden prices. It needs to capture this deep data by replicating the behavior of the online shopper.

Once you’ve refined your data with the right automated tools and analyst expertise, you can then act on your intelligence.

Taking Action: What Can Be Learned From Pricing Intelligence?
Pricing Intelligence tools identify the best opportunities for increasing margins, giving you a snapshot of which products are the most price sensitive at any given moment. During the 2013 holiday shopping season, we took an extensive look at pricing data from 15 major U.S. retailers across 13 categories, including clothing, toys, consumer electronics, fragrances, cameras, kitchen appliances and vacuum cleaners. (You can read the full report, “Revealed: Retail Strategies of the 2013 Holiday Season,” here.)

Last November and December was a banner time to be purchasing clothes for girls.

Ugam’s seven-week pricing analysis revealed that girls’ clothing was the most frequently and heavily discounted holiday product category, with Belk department stores lowering prices on a whopping 98 percent of their items. Target, on the other hand, ran sales on only 40 percent of its girls’ clothing – still a sizable selection for bargain hunters.

From a brick-and-mortar perspective, the aggressive Belk strategy might seem most relevant to national retailers with locations throughout the Southern states, where the regional chain is based. However, would have popped up for shoppers searching for clothes on the Web – and their free shipping for orders of $99 or more should be factored in by retailers planning their own apparel strategies.
Price Intelligence, pricing intelligence, Dynamic pricing, Competitive intelligence
On the stingier side of the spectrum, the product category with the least amount of price volatility was video games. Last year was an exceptionally brisk year for video game sales with the release of the next generation Xbox and PlayStation consoles.

The yellow bars in the graph below show great fluctuation in video game assortment and prices for retailers from Amazon to Toys“R”Us. Amazon, not hindered by shelf space, boasted nearly 70% more choices than Walmart. But the blue dots say it all.
Price Intelligence, pricing intelligence, Dynamic pricing, Competitive intelligence
The blue dots mark the average video game title price over the busiest seven shopping weeks of the year. Note the almost negligible $5 differentiation in price between these retailers, who are usually not bashful about slugging it out over low prices.

Video game enthusiasts are not known for their patience. They put their names on waiting lists and stand in lines at midnight for the privilege of being the first to play the newest consoles and games. In general, video gamers are like iPhone fans in that they are willing to pay the “going price” for what they want – whatever that price may be.

Strategic competitive intelligence can also help you determine when significantly lowering prices will increase profits.

To learn more about the latest pricing strategies and technology, download a complimentary copy of our new eBook, “Pricing Intelligence 2.0: The Essential Guide to Price Intelligence and Dynamic Pricing,” for retailers and brands.

Download your copy today!

The Author:
Mihir Kittur is a Co-founder and Chief Innovation Officer at Ugam. He oversees sales, marketing and innovation and works with leading retailers and brands with insights and analytics solutions around their category decisions to improve business performance.


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