In part 1 of this three-part blog series, we talked about theoretical v. results-oriented data science We’ll now continue with discussion of other aspects of price optimization and what REALLY matters.
Don’t think all vendors provide “strategic” answers because they all say they can implement “strategies”.
Basic price elasticity talks about the relationship between margin, revenue or units given the price of an item. Most providers make that their “strategy”. Do you want to increase margin, units or revenue? Others may add in a “competitive strategy,” often for an upgrade fee. Which usually only entails price matching or being within a specific price range after they implement. This is not a real pricing strategy. I’ve never talked to any retailer who doesn’t want to increase their margin, revenue, and units sold as much as they can all while being competitive. What about increasing market share, basket size, or traffic? Aren’t these strategies you need to achieve for your categories, product segment and items? What about doing it in a way that your vendor funds are fully maximized?
Strategies need to be tied to how retailers want to run their business to achieve their financial objectives. Science needs to be aligned to one’s strategy and be adjustable for each retailer. Additionally, science needs to inform how realistic a strategy is when you factor in actual consumer shopping behavior. For example, maybe as much as you may want hot dogs to be a traffic driver, with changing demographics and shopping patterns they are more suitable to grow the shopper basket once they are in store.
Higher customer benefit reported numbers doesn’t mean better software.
Every vendor likes to say how much they can help you gain and improve your sales and margin. They can point to double-digit increases in both. These aren’t lies, but they can be cherry-picked numbers to twist the perception to their liking. Real gains depend on your current maturity and the categories you are working with. There are many categories and a single item that you can show amazing numbers, but retailers are not measured on the success of a single item or a single channel. It’s much more complex. The best software delivers benefits (both hard and soft) in the most basic and most mature retailers, and everything in between, across all channels.
Be careful. Algorithmic pricing and promotions doesn’t mean science. It could be rules in disguise.
There is no clear definition of algorithm. In its basic terminology, according to Wikipedia, it “is a self-contained sequence of actions to be performed.” So what does this mean? Well, an algorithm can be anything from very basic mathematical instructions all the way to a very complex multistep sequence. Simply put, in retail terms it could be to direct a tool to match a competitors’ pricing. Alternately it might be to lower prices when competitors do as long as you maintain at least a 25% margin. So be careful when people state they can provide algorithms to you.
Check back shortly for Part 3 of this three-part blog series.