eCommerce & Merchandising

IBM Dynamic Pricing: Hitting it out of the ball park using Trends data

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A post in the continuing how-to series about IBM Dynamic Pricing software

It’s opening day at the baseball park. The home team is up to bat and my favorite player, the shortstop,  steps into the batter’s box.  The catcher gives the signal and here comes the pitch. Crack! The ball flies deep into center field. He knocks it out of the park, and the crowd goes wild!

You start to think — how can I knock it out of the park with my pricing strategies? You could say the batting coach is like the Trends data.  The batting coach looks at the competitor’s pitcher and analyses your swing (strategy). After a few adjustments, it’s game time. You adjusted your swing strategy and now you are ready to hit it out of the park!

Think of Dynamic Pricing as your own personal coach.  Before you know it, you’ll be consistently driving the winning runs in and playing in the World Series championships.

Let’s take a look at the ALL Batteries – Price rule strategy. The purpose of this strategy is to price your batteries:

  • All of them, no more than 3 percent below Competitor 1
  • Only price your RAYIBAT batteries within 3 percent of Competitor 2

Let’s take a look at each component of the Trends data.



The Summary data is based on the dates represented in the Timeframe selection. The summary data is like looking at your own personal baseball stats.  Where Unit volume is number of times at bat, Revenue is Number of home runs (the more you get, the more money you make) and Margin is number of stolen bases.



You can adjust the timeframe using the timeframe selectors.  Whatever timeframe you select here is reflected in all of the Trends data. I think of it as keeping track of how my team is doing this season, but if needed to, I can zero in on a certain month to see exactly how we are doing.



Sales history data includes:

  • Unit volume – each dot represents the unit volume by data for the products in this pricing strategy (or in baseball lingo, how many runs did our team score in each game by date)
  • Revenue and Margin – The color-coded lines represent revenue and margin by date. If I was a baseball manager, I would use sales history data to see how much money the ball club was making.



As for competitors, just take a look and see how your products are doing against your competitors’ products. This chart makes it easy with the color-coded lines.  The more competitor data you load, the more points of comparison you have.  For my baseball team, I would use this data to look at ticket sales over time in comparison to other ball teams.

After reviewing the Trend data, if you are not happy with your trends, adjust your pricing strategy and see what happens.  With the Trends data you can fine tune your strategies as frequently and whenever you want so your team always stays on top of the game.


See more posts by Denise Gary on IBM Dynamic Pricing.

Today’s Hot Tip:  You can take the tour from Help > Getting started.

Next up:   In the next blog, we’ll discuss how to import your own data into the trial.

If you haven’t signed up for the trial, then maybe you should.   You can have a free 30-day trial. You can play with the sample data we provide, or you can upload your own data.

Go here to enroll:


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