Why predictive analytics is necessary for successful pricing strategies

We've all heard it by now. The business world is being fed more and more buzz words every single day. Words like modeling, predictive analytics, big data, econometrics, fact based marketing and price optimization. Now these are not just buzz words. There's a lot of content behind them. Content that's important to all businesses worldwide. You can easily write a whole book about each and every one of these words, but what's really important is the one thing that unifies them: Facts! Predictive analytics and extraction of knowledge from data has taken a leap from science into the corporate world. This is really good news since questions like:

• How do we minimize markdown?
• How much is our demand affected by competitive prices?
• Which of our products have a strong reaction to changes in price?
• If our strategy is to keep our price below competition, then how much below?
• Are our price reductions just temporary markdowns, or everyday low prices? What is more beneficial?
• How will lowering prices on certain products affect the sales of your other products?
• How much do our products cannibalize on each other?

can now be answered with a much higher confidence than previously. Typically many of these critical questions are answered by rules-of-thumb and/or gut feelings, which might actually work out from time to time. Don't get me wrong, I'm all for gut feeling and taking calculated risks. The point I'm trying to make is here is that they should be calculated. This is precisely what predictive analytics can do for you.

Sounds good right? So, what is predictive analytics? Well it's a set of algorithms and methods that can extract knowledge from data. For example it can identify all the different variables that drive your sales. It can also figure out which media mix you should have as well as what price that will be most beneficial for your specific product.

So even if it seems like the world has gotten a lot more complicated with all these science terms flying around, in reality it's gotten a whole lot simpler. The intelligent algorithms along with a scientific approach to decision making are now able to not only identify cause and effect relationships but also to provide actionable recommendations. The question you should ask yourself today is not whether or not to do predictive analytics, rather it's all about how to get started. Trust me, it will be the smartest decision you'll ever make.