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.

The Psychology of Price Increases

In last week's post How to Raise Prices, I referenced two interesting articles on techniques for raising prices, and also suggested using unbundling to differentiate between customers who want maximum value and customers who want minimum price. Today, let's look at three interesting price increases-- Oracle's list price increases, Apple's iPhone price "decrease", and airline surcharges.

Oracle raises list prices by 15% or more
Oracle is making waves with double-digit price increases (see "Oracle increases prices 15 to 20 percent: The joys of pricing power" on CNet), but what does this really mean? Are they really getting customers to pay 15-20% more? Probably not.

Oracle is unusual in the software industry in that they publish a global list price. Most enterprise software companies (Mimiran included) vary pricing by region and don't publish prices to avoid focusing on price early in the sales cycle. Oracle's prices and earnings are dollar-denominated, meaning that overseas software sales have been getting cheaper for customers in Europe and Asia, while Oracle's local expenses have gone up in dollar terms. In other words, a nominal price increase was necessary just to reverse the price decrease brought on the falling dollar.

Second, enterprise software deals rarely close at list price. The price increases provide more room for negotiation. One of the most important aspects of list price changes in B2B environments is how much of the price change flows through to the actual price the customer pays.

Third, the move serves as a nice signal to SAP and other vendors to stop driving prices into the ground.

The software industry is consolidating, especially around Oracle, which has been gobbling up competitors, but they won't get a real 20% price increase. However, if they end up netting 1 or 2%, that's still a few hundred million dollars in incremental profit.

Apple's "Cheaper" iPhone 3G
Apple made a big splash by announcing that their new iPhone would not only support faster 3G internet access and GPS, but would also sell for the magic price point of $199. This represents a $200 price drop, along with more functionality. Isn't the rapid march of technology amazing? Not so fast. At the same time Steve Jobs announced that he was making the iPhone more affordable, AT&T upped the price of data plans for the iPhone by $10/month. To get the discounting price, customers must commit for 2 years. So you might save $200 up front, but you spend an additional $240 over the next 2 years, and an additional incremental $10/month after that. Basically, Apple and AT&T are financing your iPhone purchase for you with a very high interest payment plan. The beauty of it is that the lower upfront cost only happens once, while the ongoing revenue stream stays as long they can keep the customer. And while everyone who does the math knows that this is actually a price increase, what sticks in consumers' minds is "wow, an iPhone for $199."

On the backend, AT&T's payments to Apple make it a strong pricing move for Apple, as well, and analysts seem bullish on the revenue potential.

Airline Surcharges
And now let's get to everyone's favorite pricing punching bag-- the airlines. American, United, and other carriers have introduced fees on checked luggage to go along with fees for fuel prices, talking to a person, using curb-side checkin, and buying inedible snacks on planes. Delta also announced fuel surcharges on redeeming frequent flier miles. Naturally, travelers are unhappy. Checking a bag on some carriers will now cost you an extra $15, while the second bag will cost $25. And it's an extra $50 if you actually want to pick it up at your destination. (Just kidding about that last part.)

While this is irritating for fliers (I've heard some say "why are you nickel and diming me?") the alternative would be to raise prices across the board. Airlines are hemorrhaging money (what else is new?) because of higher fuel prices and the slowing economy. They need to do something, and price increases are an inevitable part of the mix. Flying is going to be more expensive for a while, until jet makers can create much more efficient planes. The next generation will help, but not enough to offset the rise in fuel prices.

Of course, airlines are good at slapping on surcharges. They are not good providing a good customer experience. They haven't done anything to address the ridiculous "security" procedures. (I'll save the story of how I accidentally took a swiss army knife in a carry on bag that was hand searched by TSI for another time.) They have taken pillows off planes and charged for "snacks". Why not work with the government to reduce the unnecessary elements of the security burden? Why not team up with airport restaurants, or even bring in Starbucks or someone similar to allow customers to order onboard food when they checkin? The system might take some work to implement, but it would allow the airlines to bill customers immediately instead of worrying about making change on the plane, allow customers to get some halfway decent food (depends on the airport), and the revenue sharing would probably bring in more incremental profit than the current program. The partners would drop food off before the flight, the airline could keep the hot food hot and the cold food cold and deliver it after take off. The passengers waiting inline for 15 minutes at Starbucks would save 15 minutes. Food revenue per customer would probably go way up, even if the airlines turned the bulk of the revenue over to the partner.