Wholesale Prices Make Biggest Jump in 27 Years

The US Producer Price Index rose 9.8% for finished goods for the 12 month period ending in July, the largest jump in 27 years. Businesses are stuck between the rock of rising costs and the hard place of weakening spending. Passing along price increases could further dampen demand, while not passing along price increases could put you out of business.

Surging energy costs fueled the increases (what a terrible and unintentional pun, but once it was there I couldn't take it out). Some of the companies we work with are facing double-digit cost increases in their supply chains, sometimes more than once per year.

What can you do?

Start by understanding what your customers truly value. Often, customers in different segments value different things. Some might love your products, while others place a premium on your responsive service. You can price more competitively on your product offering by unbundling the premium service that you may have thrown in for free.

Quantify your benefits for customers. If you sell a product at a premium price, even double the competition's, you might still be a bargain if your product is a small part of overall costs, but has a big impact on how efficiently other investments perform. For example, a machine on a factory floor that offers less downtime is extremely valuable. If you don't do anything better than the competition (include service, support, and other aspects of the overall customer experience) you have to compete on price. Or figure out how you can do something better.

Many companies lack the process, tools, and data to do this effectively. Now might be a good time to think about how to put those in place.

As a political aside, I need to insert a rant here: a lot of inflation comes not from stuff getting more expensive, but from the dollar getting cheaper. Over the past few decades, no one has had access to cheaper credit than Uncle Sam. Unfortunately, Uncle Sam is less trustworthy with credit than a giddy real estate speculator during the condo craze. Despite all the (hot) air time devoted to inane non-issues in the current presidential campaign, no one seems to be pressing for a meaningful discussion of the economy, the dollar, and our credit system. While many in the media noted that the Federal Reserve is now suddenly very concerned about inflation, no one wants to talk about the elephants in the room--massive growth in government spending, mainly on discretionary wars, the military-industrial complex, and entitlement programs designed primarily to benefit corporate donors, and the regressive nature of inflation.

How do you know your contract terms are unreasonable?

Tim Cummins, president of International Association for Contract and Commercial Management, recently wrote a post on his Commitment Matters blog about how courts had thrown out contracts related to software and cell phone contracts. While the court rulings, should they stand, may impact various niches of contract law, we might want to follow Tim's advice and not put unreasonable clauses in our contracts. I asked how companies can know in advance, without waiting for a court ruling, and Tim posted a thoughtful response.

Here's another tip-- talk to your sales people. If your sales people are selling around, under, or through your contract terms because they think the contract is unreasonable, you have a problem. We recently worked with a company whose sales force actively encouraged customers to sign on to contracts whose terms they didn't really meet, along with advice on getting out of the terms. In addition to creating suboptimal outcomes for the company and customers on contracts, the issue clouded the value proposition for customers who should be on the contract and interfered with the ability to develop new offerings that would better address the customers who shouldn't have been on the contracts. Getting out of this mess takes time, but at least they're on their way.

I Am Rich-- No More

We've had other discussions about how for some luxury goods, the exorbitant price is part of the value (see $300,000 watches that only tell you whether it's day or night).

Meanwhile, as some of you may have heard, Apple launched a new iPhone, along with the AppStore, which allows iPhone owners to install applications, much like you can buy music through iTunes. Prices for most apps range from free to $9.99 (see this post from Pinch Media with price distribution).

Bringing these two storylines together, someone wrote an iPhone application called I Am Rich, which simply displayed a ruby-like gem. The software cost $999.99, the highest price point that Apple currently permits in the AppStore. According the author, the I Am Rich application "always reminds you (and others when you show it to them) that you were rich enough to afford this." Nothing like a little humor.

It turns out that Apple does not find this amusing, and removed the application from the AppStore. ZD Net writer Jason O'Grady thinks the cause may be angry customers who did not really mean to buy the application.

Tricking someone into buying something they did not mean to purchase is not good, on a number of levels. (Reminds me of the Dilbert cartoon where the team discusses charging a million dollars with a $999,999 rebate. "We only need one person to forget to send in their rebate form.") At the same time, conspicuous consumption is a pretty big driver of the economy. Anyone know how many people actually bought "I Am Rich"?

Edit: Apparently, 8 people bought it. That means about $5,600 for the developer, after Apple takes a 30% take. My guess is that's a lot more money than most of the $1.99 apps have made.

How to get customers to understand value

We get a lot of queries from companies who say "our product/service/gizmo is so much better than the competition's, but our customers don't perceive it. How do we get them to see the value?"

It's a great question. The "envelope" of possible prices stretches between your cost and the perceived differential value of your offering. (That's almost always true; we won't go into loss leaders here.) A lot of companies think they have great value, and they work very hard to create it, only to be told that by customers that it's irrelevant.

One example is gasoline. Despite millions of dollars of advertising, no one really cares if Chevron comes with Techron while some other gasoline doesn't. Part of the reason is that customers never see the gasoline, let alone any additives that may or may not improve performance or engine wear.

So the first step in getting customers to understand value is to show them whatever it is you want them to value. Intel did a great job creating a brand and a hefty price premium for something that had previously been a commodity-- microprocessors inside computers. Corporate and home buyers saw the computers, but had no idea what was on the inside until Intel spent hundreds of millions of dollars convincing people that the CPU was the most important piece and putting little "Intel Inside" stickers on the outside of the case.

Nike offers another good example. When they introduced "Air" cushioning (it's not actually air but a much denser gas with a higher molecular weight that is easier to contain under pressure for long periods) in the early 80s, it was a revolutionary concept. When they made the "Air" visible in 1987 by cutting little windows into the midsole to reveal the cushioning unit, everyone could see that this was great technology. Nike did a lot of other clever things, too, but this helped convince people that they should spend $100 on a running shoe.

Have a fancy sports car? You don't want people to think you have regular non-sportscar breaks, do you? That's why companies like Porsche make bright yellow and red break calipers.

(From FleetRates.com)

They are reinforcing via a simple color choice that this is a premium product.

Of course, some things are more amenable to being made visible than others. What do you do with materials that are, by definition, embedded in walls? Dupont puts their trademark Tyvek in giant letters on their housewrap. You can't see it when the house is done, but during construction, everyone knows that the house or office building uses Tyvek.

The iPhone pretty much does what a Blackberry does, but it's got a slicker, more intuitive interface. Apple makes sure you know this by airing TV commercials showing people doing things with a few flicks of a finger that would require more complex menu navigation on a Blackberry. Sure Apple has a great hype machine, but they also make sure potential buyers understand the advantages that justify premium prices. (Full disclosure: your author is a former anti-Mac person who loves his iPhone and whose next computer will be a Mac.)

What happens when you have a visible differentiator and you take it away? Starbucks did just that, using high technology to churn out coffee faster, but removing the aroma of ground beans. As Starbucks CEO Howard Shultz noted in a now-famous leaked memo, that this caused the coffee giant to "lose its soul." Is it a coincidence that Starbucks is now closing stores? (Also possibly caused by other reasons-- we'll have a separate post on this issue soon.)

How can you help customers see the value? Anyone have any tough cases they'd like to take on in the comments? (Remember, the value has to exist!)

Webinar: 4 Ways to Accelerate SaaS Revenue

Next week I'll be the guest speaker as part of an interesting webinar on accelerating SaaS (Software as a Service) revenue. Customer segmentation and pricing are critical components to doing this successfully.

Register, or read on for more information.

4 Ways to Accelerate SaaS Revenue

July 30, 2008, 2:00PM EDT

Software as a service (SaaS) is a brave new world. While offering customers reduced cost of ownership and less hassle, revenues grow more slowly than in traditional software markets, putting huge pressure on cash flow. In this webinar hosted by ZDNet's Phil Wainewright with guest speaker Mimiran president Reuben Swartz you'll learn why the traditional 3 ways to accelerate SaaS Revenue don't work, and the 4th way that does.

To grow SaaS revenue, you have 3 options:

1. Raise prices. Unfortunately, this is next to impossible in the current climate.
2. Acquire more new customers. This is a key metric for software sales, but growing this number requires commensurate increases in sales and marketing expenditures that often don't yield positive cash flow for some time.
3. Improve customer retention. This sounds great, but how can you know when a customer will leave before they leave?

What if you could implement a 4th method that combined the other 3 methods, gave you better results than any of them individually, and was actually easier to do? How would this impact your ability to meet and even exceed your revenue targets?

Join us for this exclusive webinar with guest speaker Reuben Swartz, President of Mimiran to learn how you can use this method to increase your new customer acquisition, improve retention, and raise prices.

eVapt is the sponsor of this webinar as part of their continuing educational series on optimizing SaaS Revenue. eVapt VP of Sales Joe Tinnerello, an expert in software sales and SaaS business models, will chair the webinar. Mr. Tinnerello is also a contributor to the eVapt Blog.

Your webinar's host Phil Wainewright is an influential commentator and strategist on emerging software industry trends, covering the SaaS space for 10 years (back then it was called "Application Service Provider") and writes the prominent SaaS blog for ZDNet.

Guest speaker Reuben Swartz is president and founder of Mimiran, a leader in pricing strategy, process, and analytics. Reuben is the author of Dollars and Sense: The Pricing Blog.

Register online.

You Don't Have a Supply Problem, You Have a Pricing Problem

This is one of my favorite maxims for companies that say they can't keep up with business. (Granted, it's a great problem to have.) Seth Godin phrases it slightly differently, writing "scarcity is a choice" in a great post on Apple's poor handling of scarcity around the launch of iPhone 3G. The basic gist is that when companies do face scarcity, they often try to be "fair" and end up annoying everyone and leaving a lot of money on the table. Seth offers some creative alternatives, living up to his maxim that "there's no such thing as price pressure."

An Innovative Way to Sell $50 T-Shirts

Here's an interesting pricing model for t-shirts. 200nipples (yes, even the name is, umm, remarkable) sells limited edition runs of 100 tshirts. The first shirt costs $1, the second $2, all the way up to $100. This has the nice effect of rewarding your most loyal fans, who presumably will get some pretty cheap shirts, and spread the word. What you're really counting on is people willing to pay $90-100 for a tshirt. (Count me out.) Has anyone bought one of these shirts? Know someone who has? How much did you pay?

Experimental Economics: Finding Millions of Dollars in the Haystack

Wired recently ran a story on Experimental Economists, who model complex scenarios and attempt to optimize outcomes for large companies and government agencies. My reaction to the story was "wow-- that's what Mimiran does all the time, we just didn't have such a cool name for it."

Now let's walk through how many companies make pricing decisions and how enhanced modeling can help drive better results and provide metrics to gauge pricing success.

Making Decisions without Data
A lot of companies still make pricing decisions with their proverbial gut, rather than using data-driven approaches. This may work well for comedian Steven Colbert, but it can be costly when making pricing decisions. People make pricing decisions without data because:

• They lack adequate data.
• They lack the means of handling data effectively and turning it into useful information.
• Despite the financial ramifications of pricing decisions, many organizations are rushing to make a decision and do not have the weeks or even months required to make a fully considered decision.
  

Limitations of Traditional Pricing Decision Models
Rather than going strictly with the gut, most companies attempt to predict the outcome of pricing moves using simple models, often run in spreadsheets. This approach has the benefit of applying some data to a problem and usually results in better decisions than the gut. However, spreadsheet modeling suffers from a serious limitation. Spreadsheet models run on averages, often imported from financial reporting systems. The "average" response to a pricing move is different than the response of the "average customer".

For example, a financial services company wanted to make some pricing changes to bring them closer to competitors' price points and price positioning. Spreadsheet simulations indicated that the move was feasible and desirable. The average customer would not experience too great a change. Unfortunately, this model had no way of showing, or even knowing, that the "average" customer came from aggregating a wide spectrum of individuals. The average of all of these customers seemed like it would react reasonably well to the proposed pricing change. Looking at the customers as individuals, and then aggregating their responses gave a very different view. High end customers would experience an awful lot of consumer surplus, while low end customers would have to take too big a price increase.

Experimental Economics
Experimental economics allows companies to model the possible outcomes of a pricing decision at the level of an individual customer, then aggregate those results to product an expected outcome.

Nuanced data models allow prediction of customer behavior based on customer benefit. In the financial services example, we were able to show that certain pricing discounts had a far lesser impact on customer behavior than first predicted. We were also able to show that certain pricing incentives and bundles encouraged customers to consume services in a way that was unprofitable for the firm. By rearranging some of these bundles, we helped the customer achieve positive return on investment in the project before we had even generated final recommendations.

Another example involves a high tech manufacturer looking to take advantage of list pricing opportunities and tighten discounting variance in the field. Preliminary analysis showed an opportunity of over $20M, which provided justification to bring in external expertise. More detailed modeling that we performed, however, revealed several obstacles to achieving the $20M savings. First, list price opportunities were impossible to capture reliably because of the maze of contracts and negotiated discounts. The first look at the list pricing opportunities suggested that list price changes correlated strongly with actual prices. When we looked deeper, however, we found an almost random scatter of relationships between list price changes and final price outcomes. The average outcome may have born some resemblance to the change in inputs, but it was as likely to be caused by general market forces and inflation as pricing moves, despite a huge effort put into the annual price review process. Using this information, we could focus the pricing team more productively on managing the final price. Here we saw that many underperforming customers targeted for margin improvement were under contract and would not see price changes for some time. Some others bought primarily low margin products. The problem for these customers was not the pricing, but the product mix. We were also able to find customers getting discounts far beyond expected ranges for premium products. Focusing on these customers, there was an immediate, actionable $3M opportunity. How does turning a $20M opportunity into a $3M opportunity constitute success? First, the larger opportunity was not actionable. Without more granular detail, there was no way to capture it. Secondly, it was not actually there. There's a pricing joke "what is the difference between getting a promotion for capturing a $3M pricing opportunity and getting fired for capturing a $3M opportunity? Promising $20M and promising $2M."

Merging behavioral data and pricing data can provide even more insight. For example, looking at pricing and usage data for a software company helped us design a pricing model for a new edition. We were able to assess at the level of an individual customer who might downgrade from a more expensive edition, and whose usage patterns would justify higher price points than the company had originally intuited. This led to appropriate fencing between editions and pricing that addressed both "casual" and "hardcore" users separately. The company could provide great value at a good price to the hardcore users and good value at a great price for the casual users. Aggregate information would have led to a single price point which would have left money on the table for the hardcore users and still not provided compelling value for the casual users.

Many of these models depend on inputs whose values are not exactly knowable. However, detailed models help you infer ranges for inputs, such as the percentage of customers who leave over a price increase versus the percentage who opt for cheaper substitutable product. In addition, the models can run with a range of inputs, based on customer feedback, surveys, market data, and expert opinion. Any one of these sources could be wrong, but by combining multiple sources, we create a distribution of inputs and a distribution of outputs, which leads to worst-, best- and likely-case scenarios.

Putting Theory into Practice
While the benefits of detailed experimental economics are compelling, few customers undertake such activities. There are several reasons for this, foremost among them a lack of awareness that such capabilities exist (hopefully writing this piece will help). Many companies also lack time, data, expertise, and money. As the Wired article notes, developing these capabilities can require 6- and 7-figure annual investments. However, we have been able to deliver these projects in many cases under $100K. In addition, our software not only provides the models, it also tracks performance against the predictions of the model, enabling you to tweak pricing if needed, and providing built-in proof of value. Plus, creating these models is a lot of fun and is certainly an eye-opening experience as our customers get a much deeper view into the performance of their businesses.