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Price Optimization Software Big in Retail Business
prostoalex writes "Even if you spent only a single day in an economics class, you're probably familiar with a concept of supply and demand. The Associated Press is running an article on retailers employing mathematical models for price optimization, where some products are priced higher to generate higher margins, and some are discounted to generate larger volumes even at the expense of per-product margins. DemandTec, Oracle and SAP are some of the companies producing those mathematical models for retailers around the country, with AP listing some of the pricing optimizations employed currently."
Seriously - this is NOT new. Not even in the software field.
Yes, this is true, but you don't need complicated mathematical schemes for this. They've been doing it for years.
It's called coupons!
The product is priced on the shelf at the price most consumers are willing to pay (say, about 60%). The coupon discounts the product to a price the other 40% are willing to pay. Now you get to charge two prices for the same product! Woohoo!
One technique for this is the extended warranty racket. For the perception of improved service, and to make up for frequent shoddy workmanship, the product is available with several different layers of warranty available. The person who can marginally afford the product gets just the product but no added service or peace of mind, the person who will pay more for the product, gets the service he should expect with a quality piece of merchandise. All with just one line of product.
I used to have a cool sig, back when I cared
No to be rude - and you're correct in your premise - but that is typically called (market) segmentation in the industry, and not price optimization (I have some background in telecom marketing segmentation). The idea that one can segment their customer base and target product marketing efforts (either by price, features, or what advertising is focused on) is a little different than the article, which talks about looking at behavior within a larger set (the entire "chain") are large demographic subset (all of Dallas), and making a strategy out of existing full-set behavior. One could argue that charging a different price in Dallas versus Boston is segmentation, but it misses to definition a bit and falls more accurately into the price optimization category.
I just wanted to point out they're two different (but related) interesting topics.
how many pairs of boxer shorts should you own?
2) Never look at the products at eye level, they are the most expensive and worst value.
That is really not a valid statement, for a couple reasons. The first error is the last two words 'worst value'. Only the customer can determine what the value is. If I'm looking at a condiment section and at eye level is a name brand catsup, and below it is a private label equivalent, the price per unit will probably be lower on the private label. That doesn't necessarily make it a better value. If I think the private label tastes rotten and wont eat it, the more expensive catsup is a much better value.
The second issue is that quite often what you see at eye level is determined by who payed for the placement. It may not be the highest margin item for the retailer on its own. But it is their because the vendor payed a royalty to have it where they want it.
3) Move as fast as you can to the back of the store. Start at the back of the store and work your way forwards.
That doesn't make a whole lot of sense. If you are talking grocery, very few stores are laid out the same way. There's no way this can be a 'rule' that will help you when what is at the front or back will vary from location to location. I think a better way of looking at this might be - don't buy what is on end-caps and floor displays until you have looked at the prices for comparable items. This means, not running to the back, but going to the aisle where the item is normally located.
In larger stores this really doesn't make sense. If I go to Fry's Electronics and run to the back, how does that help me? If I go to Best Buy and hustle right back to home appliances, I'm not sure what I've done to help myself out.
The psychology of all this is over rated. A little common sense - like many of the other suggestions in the list, will go a long way. That's not manipulating the 'system' it's just using your mind and operating above a visceral level.
It's hard to believe that's how Micronians are made. Why don't we see it right now by having you both kiss one another?
The amusing fact is that this is nothing more than a capitalist version of taking from the rich (those are willing and able to pay more) and giving to the poor (those aren't willing or able to pay more).
Some people might think you are kidding there, but there really are cases where everybody wins from differential pricing, and businesses really do take from the rich so they can afford to sell to the poor. Let me add an example to make it clearer:
Imagine you want to build some sort of clever new software. You see that 10,000 people would pay $100 for it (as a fun toy, say), and 5 companies would pay $1m for it, because they can each make $3m from using it commercially.
If the software costs $1m to develop and you sell all the copies for $100, your profit will be $500. Nobody's going to go to all that trouble for $500, so you wouldn't make the software. And if you did, you'd be steamed that these companies made millions while you got pocket lint.
However, if you sell the first 5 copies for $1m each (with, say, some fancy documentation and a support contract), you can then go on to release a consumer version to get everybody else. You get $5m in the bank, so you're happy. The companies netted $10m, so they're happy. And everybody else got a fun toy at a reasonable price.
Note that although your average price per copy there is $600, you couldn't get the same effect by charging $600; none of the consumers would pay that much for a toy.
Yes, you are right that they are separate but related. (Your post is not rude and I hope my response is not rude, either). The lead example concerned pricing of drills. The three models (perhaps from three different makers) define different market segments as far as the retailer is concerned. Optimizing the price on the three models gives the retailer a chance to maximize both revenues and profits even if the retailer doesn't do anything to market the products differently. Similarly, markdown optimization is both a price optimization and a segmentation issue -- segmenting the "I'll pay anything to be the first person to own this" customers from the "I'll buy it later when its discounted" customers.
The classic example, that I was thinking of, is the revenue management strategies of airlines that attempt to optimize prices across presumed underlying segments of price-sensitive leisure travelers versus price-insensitive business travelers. Technically, it's the identical seat that's being sold for radically different prices (up to 10X different) depending on issues such as how the customer buys the ticket, when they buy the ticket, whether they book a saturday-night stay, etc. The result is that the business customers pay for the plane and the vacation travelers only pay for the fuel and variable costs. The ability to differentiate does benefit the business customers because the added volume of travelers means a more frequent schedule of flights, larger planes, and more destinations.
You are right, though, that true market segmentation involves much more than just price optimization.
Two wrongs don't make a right, but three lefts do.
Thats not how the cards work. There are two price tiers: one for non card holders and one for those with cards.
In fact, the scenario you described with the cards is exactly the same one you said customers wouldn't tolerate. It is also illegal in many places.
It's not just price optimization that's relatively easy to learn. There's also location theory and optimization (e.g., retail, essential and emergency services, noxious facilities), routing and scheduling, order and inventory levels, ... The math is relatively simple (most of the time) and if you can set up the problems there are some decent OS software packages with very good solvers. COIN-OR comes to mind but I'm sure there are several.
The real issues are getting the data and interpreting the results. I've got a land use decision model for urban fringe areas that's doing a reasonable job of presenting sets of potential solutions for decision-makers. The tough stuff is the pre-processing, e.g., defining what's feasible and desirable, and interpreting the results, e.g., what solutions are or aren't significantly different. For this type of work geographic data is readily available. I doubt that will be the case for most business decisions.
Why not save the cost of using software to calculate prices, and just ask the stockholders what they'd like to see it priced at? After all, ultimately they are the ones in control of the company. You might as well let them set the pricing so when profits drop, you can tell them "You wanted it, we did it. We're not to blame" and if profits soar then the stockholders can be pleased with their decision.
Still waiting on Serviscope_minor to wake up to fucking reality and realize that Jessica Price isn't going to fuck him.
The vendor then has to pass its cost to the consumer with higher prices, TNSTAAFL.
You assume that the vendor always charges the same price. Often, the vendor will pay for good shelf space and lower the price. It's called a promotion.
The vendor uses this as an investment to encourage new customers to try the product or people who've forgotten about the product to start purchasing it again. Some of those people then begin to like the product and purchase it when or where the promotion is not available (perhaps they purchase Coca-Cola on promotion at the store, and then ask for it in a restaurant later).
You're right: there is no such thing as a free lunch. The people who pay for the shelf space and the promotional prices are the people who purchase at non-promotional prices because they were reminded of (or introduced to) the product by the promotion.
Social scientists are inspired by theories; scientists are humbled by facts.
"The software never makes the common mistakes human beings make. For example, different "flavors" of the same size package of the same product should come out at the same price, and the unit price of a given item should go down as the amount bought increases. I can tell you that I have seen examples where humans have screwed this up this week. When there are two sizes of a given product, let's say a certain laundry detergent, then the price per weight of the larger package better be less than the price per weight of the smaller package, or there's never any incentive for the customer to buy the larger package. Still, I see examples where the pricers have gotten this wrong. I've even asked people at the stores if they were trying to move the smaller packages because of having too much of that size in stock or something, and they told me that no, they had no such problem."
Actually, this is quite common practice. A lot of people assume that just because the package is bigger, the "cost per gram" or "cost per ounce" MUST be lower - and they buy accordingly. Not only didn't the retailer screw up - he's making more by this "tax on ignorance."
A lot of people can't do the math in their head if one item isn't an exact multiple of another item. Others "can't be bothered" doing the math. And still others, they just make the aforementioned assumptions that "bigger == cheaper per unit". And in places where retailers are required by law to display the "per unit" price, people can't be bothered to look.
I've seen retailers take items that were dogs at $x per unit, bundle them 3 to a package and price them as "Clearance: $4x" and sell them out.
And I frequently see items that are cheaper when bought in smaller units. There's a whole "to-the-retailer" rebate thing you're missing in any such analysis - manufacturers or distributors will frequently offer retailers a rebate to promote a smaller size of an item as a way to get buyers to try out a particular brand as an impulse buy. The regular brand-loyal buyers just assume that bigger==cheaper, and don't stock up on the cheaper smaller size.
Last week, for example:
- 8 boxes of 36-bag tea worked out to the same price as the large 216-bag box, which holds 72 fewer
... (so I bought 10)
- 6 cans of 28 oz. tomatoes worked out a buck cheaper than buying the 160 oz jumbo can, which holds less
... (so I bought 30)
- 375 ml jars of sparerib sauce were less than half the price of the same brand at 500 ml - (so I bought 15 - and 6 had an added 30 cents off coupon attached, for an extra bonus)
- 475ml bottles of soya sauce were almost 70% less than the jumbo 900ml bottles (so I bought 5)
- 20 jars of olives, same scenario
- 10 jars of gherkin pickles, ditto
- same story for 6 bottles hunts of bbq sauce
- ... and mustard - 5 jars
- ... and relish - 6 jars
- ... tinned peaches, tinned pears, tinned fruit cocktail - same story (25 cans)
Added to the other stuff I bought on sale (10 kg of coffee, for example, at $2.60 less per kg), I easily saved between $100.00 and $150.00The manufacturers do their price optimizations, the wholesalers and distributors do theirs, the retailers do theirs ... and it all comes down to getting the consumer to give them the money instead of giving it to someone else.
Consumers who do their own "pricing optimizations" can save a bundle, especially if they're alert to the "bigger is not necessarily cheaper" scam, and are willing to buy a years' worth at a time. It gives a better return on investment (easily 25 to 50% per annum, tax-free) than any other investment you'll find out there.