6. What a Price Says

  1. Product Pricing
  2. Some Economics
  3. Pricing Psychology
  4. Pricing Pitfalls
  5. Advanced Pricing
  6. What a Price Says
  7. Pricing Checklist
  8. Bibliography & Credits

Prices are never neutral. They send signals. For example, a high price can signal that you have a quality product. Consumers assume that expensive perfumes and wine are better than cheap ones, even in the absence of much evidence.

A low price can tell customers that you’re value for money, or that you’re special. If your competitors are selling software at $10,000 a seat, and you’re selling yours at $100, then that says something about you. Of course, you might be saying ‘game changing’, but your customers might be hearing ‘toy’.

Copy your competitors and you could be indicating that you’re just a ‘me too’ product. If you’re a me-too product, with me-too features and a me-too price, why would people buy from you, especially if there’s already a strong, dominant product in your market?

Whatever price you choose, the signals it sends need to fit in with your brand, and your brand needs to fit in with your reality. There’s no point using a high price to signal that you have a quality product if you’re not willing to spend marketing dollars sustaining that brand, development dollars making that quality a reality and customer service dollars providing the level of service people expect from a quality brand.

In 1996, McDonalds launched the Arch Deluxe in an attempt to create a burger for a more sophisticated, adult consumer. To recoup the extra cost of the higher quality ingredients and the $200 million dollar marketing campaign, McDonalds priced the new sandwich 32 cents higher than a Big Mac. But the product they tried to create (high quality, premium) conflicted with the McDonalds brand (cheap and convenient) and the Arch Deluxe flopped. One argument could be that they priced the burger too low, and that a 32 cent premium did not send enough of
a quality signal.

Your business model and your strategy have to support your pricing model. If you have expensive sales people driving expensive cars, taking your customers’ CEOs out to golf, and end users who expect plenty of hand-holding and customization of the software you sell them, then you can’t sustain a low price point. Similarly, if you’re selling shrink- wrapped, mass-market software over the web then a high price point will be counter-productive.

When Red Gate tried to get into the automated web load testing market one of the reasons we failed (there were plenty of others, including a product that wasn’t up to scratch) was that we attempted a low-price, high-volume approach in a market dominated by high-price solutions. We figured that consumers would love a product that they could just download, try and then buy, but it turned out that our customers wanted much more handholding than we were able to provide. For the most part, they didn’t want a product, they wanted a people-intensive service and the reassurance that a big-name, expensive vendor could provide. Our load testing tool was moderately successful, but it achieved nothing like the success we had dreamed of.

The dotcom boom and bust contains plenty of illustrations of com- panies who failed to align their pricing with their business model. For example, Kozmo.com’s business was built around delivering snacks, DVD rentals and Starbucks coffee, within an hour, to city dwellers. Unfortunately, the low price, high volume business model it chose clashed with the reality of the expense of delivering small items by bike courier. This could have worked as a high price, low volume business model, as the butlers of English aristocrats will testify.

Switching strategies can be hard. For example, when Intel introduced the 8080 processor, it priced it at $340. Ultimately, it was selling for $2 a unit, but Intel found it very hard to shake the initial imprinting of the high cost in people’s minds.

Practice trumps theory

You’ve read a lot of theory here. Wherever I can, I’ve based it on my experience and sound research (you can find some of my sources in the bibliography later on). But your own circumstances are different to any of those described here, so never forget that practice trumps theory.

Product pricing is as much art and craft as it is science. Sure, it helps to understand the economics and psychology of pricing, but theory can only tell you so much. At some point, you need to make a decision and do it. Use the information in this handbook to make an informed stab at what a good price would look like, and how your customers will react, and try it out. The exact price almost doesn’t matter – get it broadly right, don’t screw up totally – and you can tweak it later.

You’re never going to know if you’ve chosen the exact right price or not, but you should experiment once you’ve set your initial price; not experiment in the scientific sense of forming a hypothesis, changing a single variable, and accepting or rejecting the hypothesis, but in the sense of changing something and seeing what happens.

Scientific experiments are simply too hard to do, and the results too ambiguous, to be much use in pricing. Too many variables change. When you change your prices, you’ll probably do it when you release a new version of your product, or it will coincide with a big marketing push, or some other variable you cannot control, such as the state of the economy or the reaction of a competitor, will interfere.

Although scientifically purer, it often doesn’t make sense to change a single variable at a time. Theoretically, you shouldn’t change the price of your product, your discounting strategy and the types of bundle that you sell, all at the same time. But practically, it can be the right thing to do. It’s more useful to fix the problem than to understand why it’s broken. When a scientist goes on a blind date that doesn’t work out then, in theory, he should fix one variable at a time, and re-run the date. First, he should change the partner but go to the same film and buy the same flowers. Next, he should keep the partner the same, vary the film and keep the flowers the same, and so forth. But the pragmatist in him will, or should, change the girl, the film, the flowers, and buy some new clothes and shave too. If it works, he might not understand why, but at least he’ll have a girlfriend.

In the old days, experiments were easy to run. You’d A/B test, splitting your customers into random groups, post each group a different leaflet with a different price and measure the outcome. Nowadays, this is risky. The Internet makes it easy for people to figure out what other people are paying.

You might be tempted to first run a survey, testing how customers might react to a proposed new pricing model, or change to an exist- ing one. However, surveys rarely work. There is always a disconnect between customers’ words and their actions. When McDonalds launched its Arch Deluxe burger (see above), consumers in focus groups loved it, and 80% said they’d buy it. Few of them did.

How to change your pricing

You might be worried about how your customers will react when you change your prices. Don’t be. For most of us, our customers have better things to worry about. If we shift our prices from $100 to $150 then most people won’t notice, and of those who do notice very few will care. If you bought a copy of SQL Compare from the Red Gate web site in 2000 it would have cost you $50. Do the same thing now, and you’ll find the price is $395. Buy the full suite of tools and expect to pay $1,595.

Of course, at Red Gate we’ve reached that price over the course of almost a decade. We’ve spent millions of dollars developing the soft- 64 ware, and tens of man years. The increase in value that our customers get from our software vastly outweighs the increase in its cost. But, of the hundreds of thousands of customers we have, only a handful have ever commented when the price went up.

It’s not what your customers say that’s important, it’s how they behave. Whenever you make a price change, pay close attention to what your customers do. If they stop buying, rethink.

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