CSD: Optimizing Everything
By Julie Crawshaw
Through a special arrangement, what follows is an excerpt of a current article from Convenience Store Decisions magazine presented here for discussion.
Though many people equate price optimization with finding the highest price the customer will pay, Ken Ouimet, a pioneer in the field, said the process actually works by lowering margins on some products and raising them on others. Many of his clients, including 7-Eleven, reinvest increased profits in lower prices and use the software to figure out which products, when priced lower, can drive more volume and more market share.
The convenience store channel, he claims, is well suited to PO because it performs best in high-volume environments. Overall payback can come quick.
“When our clients run a pilot program with the software and measure the results against a control group, the result is a 1 percent to 2 percent of sales increase in profit,” said Mr. Ouimet, who sold his company, Khimetrics, to SAP last year. “That’s huge. If you look at a $10 billion retailer, one percent of sales is $100 million a year.”
Jeff Miller, president of Miller Oil Co., said that the KSS PO software he’s been using for the past three years has reduced the amount of time spent pricing gasoline by 50 percent.
“Pricing is something you have to do every day,” said Mr. Miller, who operates 40-plus stores Virginia. “This software gives you the ability to manage prices by site and by grade on a daily basis much more efficiently than you could ever do by hand.”
Dennis Williamson, general manager for Ricker’s Oil, said that before using KSS, his company kept prices the same at the 14 stores near its headquarters in Anderson, Ind. “We were afraid to price differently from one side of town to the other,” he said. “With KSS, on any given day, I now often have five prices and different price spreads as well.”
Mr. Williamson acknowledges that setting parameters for the program can be quite time-consuming. “The software requires setting up a target profit and a target volume that can subsequently be tweaked more toward margin or volume,” he said. “You watch how it reflects to your competitors – you can actually learn that somebody you thought was a competitor isn’t nearly as strong as you believed.”
Most observers agree that PO, which reached retail by helping department stores efficiently clear end-of-season merchandise, has value in determining gas prices because of gasoline’s volatility, but not everyone advocates its use across all items in the convenience channel.
“If you price items significantly less than other stores within line of sight, your competitors will adjust their prices downward and no one will make money,” said RTG management consultant and RetailWire BrainTrust panelist Mark Lilien. “If you price upward, people will simply start shopping at the c-store a block away.”
Jon Hauptman, vice president of Willard Bishop, said c-stores could earn stronger margins and higher profits using PO software to determine prices. However, he added, “Retailers get the full benefits of price optimization only when the system they use supports and enables their own comprehensive pricing strategy. C-store retailers must develop a pricing strategy that provides the guidelines that fuel the optimization engine.”
Discussion Questions: How much of an impact will price optimization software have on convenience store operations? What advice or precautions would you have for a convenience store operator exploring price optimization software?
Price optimization software is only as good as the data being used. Does the data cover a whole chain, a region, a store, or a certain group of consumers? Running the numbers is important and provides a tremendous guideline. However, in the final analysis the information needs to fit the consumers coming into your store.
I am only moderately knowledgeable here, and as the main article states, we have mostly seen pricing optimization used in department stores and similar retailers where the software really helps make decisions in the markdown cycle (specialty retailer Payless Shoes has been a huge success story from using PO, for example. Zillions of SKUs, relentless need to markdown and move out merchandise. They claim to have improved profits substantially through PO, and yes, now do price the same shoe differently from one side of town to the next).
I can see how it might work in very volatile gas prices, though in the end you still have to know what the competitive prices are, of course. Does the software do a better job once you have that info? Apparently so.
I actually think PO could in general work in C-stores because the pricing of standard items is so all over the map within a single store and between competitors. Why? Because it is convenience driven, so price is less of a factor. What price should you set for that 32 ounce Gatorade that will maximize profits? It’s experience, trial and error, or no real analysis for many C-stores now–PO software could help.
The upside benefit of PO has received very little press. Of course, retailers seldom want to talk about how they are using sophisticated software to get higher prices for goods…not the best PR. Convenience stores would seem an ideal logical fit with the prerequisites for margin enhancement pricing. This works best with impulse purchases, or those where price comparison is either difficult or not worth the effort. Intellectually, this appears a good fit with c-stores.
As a data point of one, I have the belief that c-store prices are already inflated across the board. My concern would not be with the short or medium term profit optimization. I think that would flow as predicted. Rather, I would be concerned with an almost subconscious increase in buyers remorse. I am already unhappy with my perception of the pricing practices. As the prices moved upward, at some level I think the average consumer would be aware. And perhaps without conscious intent, start to shop elsewhere.
I guess it all depends on the software but Dan raises a good point. Gasoline pricing in c-stores is volatile and often keyed off the price set by a targeted competitor. So…if the competitor is irrational, what does the software do?
There are a couple of things at play in the c-store market that I think do make it particularly receptive to price optimization. One, on the gas side, there is a lot of pricing transparency. Between looking across the street to see a competitor’s price, to price tracking mechanisms online (whether syndicated or free for consumers), there is a LOT of information available about gas prices. That makes for a strong set of inputs into PO–and a lot of syndicated services extend into the store too to track prices of things like milk.
Two, within the store, there is a limited set of SKUs. In grocery and department store, initial price setting and promotion pricing is complicated by affinities, complements, and substitutes. So understanding the impact that a price change on one item will have on demand for other products when you have, say, 35,000 SKUs under your roof is a very different problem than when you have 5,000.
The challenge with pricing is to identify the key items that your customers generally use as the basis of their perception of whether you have high prices or low prices. Almost by definition, a c-store is mostly key items. So while fewer SKUs makes it easier to understand the impact a price change will have on other products in your assortment, it also gives you less room for the higher margin items that can support competitive pricing on key items.
To me, PO for c-stores automates a time-consuming task that can certainly provide a return on investment. But the bigger challenge–and opportunity–for c-stores is not in pricing the assortment they have, but in determining the right assortment to begin with.
Pricing optimization is critical to success in the retail environment. However, it is a mixture of costs, which includes all logistics costs as well as product costs. Logistics play a greater role in product sales, since they are often the key component of how a product is priced, and how much of a product is available for delivery (and sale). They also determine the impact that cash flow has on the operations and the ability to financially manage each of the aspects of the logistics and sales cycle towards revenue maximization.
I certainly agree there is a compelling case for price optimization software in retail inclusive of the c-store segment, as borne out by the success c-store operators have experienced using this type of software. In today’s retail environment characterized by hyper-competitiveness, channel blurring, and very well-informed consumers, any retailer that doesn’t utilize what science has to offer is at a disadvantage relative to those retailers that have chosen to adopt science-based tools.
In the area of merchandising, software enhances the merchant’s ability to understand what merchandising decisions will best achieve his or her business objectives that support an overall strategy. The merchant still makes the familiar choices such as between driving volume vs. profit, expanding the assortment vs. rationalizing, or whether or how to promote, but does so with dramatically increased confidence and precision. We find that at least as often as not average prices go down in a price optimization scenario, but the mix of prices shifts, and, when varying gross margins are factored in, the retailer will find additional profit opportunities. Every retailer I know is very mindful of their price image and that is closely managed for long term benefit.