LeveragePoint Value Management Blog

Are Software as a Service Vendors Innovating on Pricing Metrics?

Pricing metrics are the unit that something is priced in – we buy bread by the loaf, hamburger meat by the pound, frozen hamburgers by the patty. Choice of a pricing metric is one of the most subtle yet powerful decisions that a company can make, and those companies that successfully introduce a new pricing metric can transform an industry. Pay-per-Click advertising, originally introduced by Goto.com in 1998 but popularized by Google in 1999, has disrupted advertising across many media. When GE introduced its innovative GE90 jet engine in 1990 there were questions about the cost of maintenance. Instead of compromising by offering a lower price to compensate for the perceived risk, GE effectively rented aircraft engine for a fee per hour flown (it shifted the metric from ‘engines,’ what it makes, to ‘hours flown,’ what matters to its customers). Without the uncertainty of maintenance cost, GE90 engines quickly became popular even with the price premium (see Strategy and Tactics of Pricing pg. 60).

SaaS vendors have a big opportunity to innovate around how they price services. SaaS solutions are easier to meter (measure the many different types of use), configure and integrate than is conventional software. This makes it possible for SaaS vendors to offer new pricing metrics to their customers.

In The Strategy and Tactics of Pricing, Tom Nagle and John Hogan propose a framework for choosing pricing metrics, see Figure 1. How are SaaS vendors doing when it comes to finding new pricing metrics?

 Most SaaS companies have moved away from the traditional enterprise software model of licenses + maintenance fees+ services + license upgrades. Buyers have been pushing back against this model for years as it does not map well to how they get value from software and it locks them into long-term commitments on terms not to their advantage. SaaS vendors are providing different options. In general, SaaS vendors sell some form of subscription in which the buyer always has access to the most current version of the system, and systems are typically updated more quickly than the 18-plus month cycles common with enterprise software (for SaaS customers upgrades are part of the subscription and are a positive, for installed systems upgrades are sometimes seen as a way to extort additional upgrade fees). Best of breed SaaS companies have figured out how to maintain configurations and integrations with other software across these upgrades.

Four general types of metrics have been adopted by SaaS vendors: Access, Users, Usage, Performance. These can be blended to create many unique solutions.

Access	A company pays for access to the application and data, regardless of how many users there are or how much usage is made. This metric makes sense for applications with a large differentiated value that have relatively few users or intermittent use, and whose value generation depends on relatively unfettered access. A refinement of this is to breakdown pricing by function. Examples:   salesforce.com charges different per user fees for its Group, Professional, and Enterprise licenses. LeveragePoint’s Group, Division, Enterprise pricing.
Users	The number of users that can access the application is a common metric, this can be the absolute number of users or the number of named users (when people need to personalize their data). Per user metrics make sense when the value created by the application is primarily at the individual level or there are operating costs that scale with the number of users. This is the most common pricing metric for SaaS vendors and is used for many services by industry leaders salesforce.com and NetSuite.
Usage	In some cases it is how often the software is used, or how many resources that are consumed, that maps best to value or cost. This approach is especially relevant to commoditized services such as cloud computing. Example: Basecamp has different charges depending on how much storage you need. Doczone, an XML content management system, charges by the page.
Performance	The ultimate pricing metric is to link price to outcomes. Typical examples are a percentage of savings, or a percentage of new sales, or a percentage of margin improvement. These pricing metrics are rare because outcomes usually depend on multiple inputs and it can be very difficult to untangle these. Example: Pay-per-Click in Google’s Adsense is the classic SaaS example.

One start-up has used LeveragePoint for Value Management to uncover an interesting pricing metric. This company provides a service that tracks how messages propagate across social media such as FaceBook, Twitter and LinkedIn. The application is used by marketing companies to track social media campaigns and the pricing metric is per campaign. At some point this company may want to find a performance metric in which they get paid based on the effectiveness of the campaign!

SaaS Pricing is a rapidly evolving topic, here are some other informative posts.

• Linking SaaS Software Pricing to Value
• As SaaS Evolves so will SaaS Pricing
• Some Thoughts on SaaS Pricing
• SaaS Pricing Evolves: Should we be Worried?
  

The Marketer's Dilemma

Where should a marketer put his or her effort? Top-line revenue or bottom-line profit? How can you do both? Michael Krauss of Market Strategy Group wrote an excellent column in this month's Marketing News that nicely summarizes Tom Nagle's keynote at the Professional Pricing Society Conference in May. Download pdf of article here.

The gist of the answer is to balance top-line growth with bottom-line cost cutting in ways that drive revenues up while bringing costs down. As examples, Dr. Nagle cited a number of well known success stories such as Walmart and Southwest Airlines and shared in detail a lesser known, but fascinating case study of Quad/Graphics. It's the story of a charismatic owner named Harry Quadracci who established a set of rules that balanced operational efficiencies with customer needs. Customers didn't get everything they wanted whenever they wanted it. They got lower prices in return for handing scheduling control, paper choice and other variables over to Quad/Graphics. These rules reduced costs for the printer and for certain customer segments, who were not as time sensitive, did not impact business outcomes. Quad/Graphics also helped its customers streamline their own production in ways that reduced costs on both sides. This built tremendous customer loyalty, and helped Quad/Graphics grow into a billion dollar printing empire. 

In a word, the key ingredient to success is: collaboration.  Collaboration between the internal operations and the external customer-facing parts of the business. Clearly, Harry Quadracci broke down the silos inside his own company. At the same time, he created a collaboration platform with his customers.

Today, LeveragePoint helps B2B companies communicate across the silos of product development, pricing, marketing, and sales with its LeveragePoint for Value Management collaboration platform. Using this platform, companies can create compelling value propositions and arm sales people with the best data and tools to negotiate with customers.

Ed Arnold
[email protected]

A Value Model for BP

Kenneth Brill's recent commentary in Forbes, The Real Cause of BP's Oil Spill, frames an interesting economic trade-off of "mostly working" solutions versus "never failing" solutions. The gist of his argument as I understand it is: a) often the cost of "never failing" solution are not economically justifiable; and b) although BP came to this conclusion with its Deepwater Horizon oil rig, they in fact made a horribly wrong decision because they overlooked the true potential costs.

Had BP the benefit of building a value model, it may have avoided its ugly fate. Here is what the value model would have looked like. 

It's based on the cost impacts of dealing with the aftermath of the explosion as reported in the news media and includes the efforts to stop the leak, clean-up, liability and fines.  We've also included other costs relevant to BP’s business model such as the lost market capitalization and lost oil revenue.

Within the value chart, the large green bars demonstrate that "never failing" solutions provide a tremendous amount of value by avoiding billions of dollars of cost. The small blue sliver at the bottom shows the estimated cost of BP's Current Spill System, i.e., the "mostly working" blow-out preventer (estimated at $500,000 from what was gleaned from the news).  Some experts claim that an additional investment of $500,000 for a remote control shut-off valve would have prevented the initial explosion, but BP declined because of its cost justification criteria.

I cannot judge whether the remote control device can be considered "never failing" or even what the full cost of a "never failing" solution really is. Regardless, this value model clearly indicates nearly $32 billion worth of value to be had in considering such a solution.  Makers of remote control shut-off valves and other oil rig safety equipment should definitely take note of this.

Value models are therefore useful to frame these types of strategic decisions. Of course, one can challenge the specific cost calculations. Yet directionally, the value model supports an obvious conclusion that none can deny - BP's decision making has cost them dearly. Too bad for them (and many others) that they didn’t see it before.

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Note: this is the first of a series of value models to illustrate current business topics using the LeveragePoint for Value Management solution. For more information, visit us at:  www.leveragepoint.com

Let Them Build It and They Will Come

When a landscape architect is designing a park or campus, a decision must be made where to put the sidewalks. A favorite trick is to simply plant grass everywhere and wait. In a month or two it will be obvious where the sidewalks should go.  

 

Now the same concept is being applied to the design of online tools to help people do their jobs. For the longest time such tools were designed by people far from the trenches. Those designers had an array of academic skills but lacked the hands-on expertise that only comes from “being there.” As a result, many online tools and eLearning programs were seen by the intended user group as “yet another thing from corporate” that got in the way of doing their job.

 

The problem is that the complex models developed by experts and consultants often don’t fit into the users’ world. People in the trenches understand more than they are given credit for and will resist adopting new methods and tools that don’t actually help them to get work done. They will be receptive to new tools if the tools respect the already overwhelming demands on the time and attention of knowledge workers, and if they help them do their jobs better and measure things that are meaningful.

 

The outcomes from conventional consulting solutions and the methods used to activate and embed those methods in organizations have often been underwhelming, because it has proven difficult to achieve widespread adoption and alignment. I often reflect on the comment made to me by a vice president of one of the world’s largest companies regarding the stacks of PowerPoint decks in his office. “I have eighty-million dollars worth of consulting sitting on those shelves,” he said, “and no way to get it out there.”

 

The solution is to turn the whole problem on its side and examine it from the end-user’s point of view. What busy professionals need is something to help them do their jobs better and faster. There is simply not enough time to learn everything that needs to be known, so needed knowledge must be made available in context on the fly. The people who know best what kind of tools will get the job done are the people who need to use them, so the design process needs to reflect that reality. The solution needs to come from them. Pull, not push.

 

Recently a large industrial company asked LeveragePoint to address the need for simple, elegant tools that treated their Intellectual Capital—the tacit expertise of their own people—as a commodity that could be captured and shared among their professional marketers. The idea was to give the end-users the ability to not only help design the tools they would use—based on their experience—but also the ability to refine and change the methods and practices that were being prescribed by corporate leadership so they would be more effective.

 

The trick was to find the appropriate balance between hierarchical knowledge and “open source” (collaborative, networked) knowledge. Too much of the former and the resulting rigidity gets in the way of an adaptive solution; too much of the latter and there is chaos. The LeveragePoint platform was employed to balance the two, facilitating rating of solutions, feedback on tools and methods, and sharing of best practices. Needed knowledge was embedded into the tool but was not an obstacle to getting the actual work done; it was available if needed, in the smallest coherent chunk and in context, but was not a required part of the process. Collaboration in product groups was facilitated in the online environment, and the tool was iterated again and again, each time capturing suggestions and improvements from the field. Powerful metrics were established to measure use, collaboration, virality, and most importantly, output and business impact.

 

At the end of three months, the tool had been used by a large percentage of the intended audience, far more than we or the company had ever seen previously, and user interest in it was spreading by word of mouth. People, given the chance to design their own solution, liked and used it. While we started out with a design mandate for a simple and elegant solution, the users further simplified it during the pilot phase, and in doing so made it even easier to use. Expertise became something that could be captured and transferred from one person to another, and it remained in the system even when people moved to other jobs or outside the company.

 

Moving from a static solution to a dynamic solution and allowing the end users to participate in the design of their own tools was an important breakthrough, one that moves the corporate competency model from a dry academic standard to one directly related to feet on the ground performance. And it became clear that competency is not just an individual metric—it is a collective capability that can be tapped into by each member of the team when the appropriate tools are made available.

 

Jonathon Levy

President and Chief Strategy Officer

Freemium – How to Price Your Product for Free

Can you believe that there is a wrong way to price a free product?  That premise sounds a bit counter-intuitive.  Giving it away should be the easiest pricing strategy to implement.  Actually, it isn’t. 

Recently, a group of executives shared their insights about so-called freemiums at the annual MassTLC unconference. By the way, the term “freemium” as defined by Wikipedia refers to the marketing strategy of using a free offer to build a base of users who can be converted into paying customers (free + premium = freemium).  Freemium is often used in the context of web 2.0, but when you think about it, the general concept has been around for ages.  We've all seen those “try if free – cancel (or send it back) at anytime” type offers.   Like many, I tend to be suspicious of such deals, particularly the ones that credit cards companies have tried to hard-sell me.

Web 2.0 freemiums have evolved from aggressive promotional tactic into a legitimate business strategy.  Provide users with a taste of real functionality in order to establish credibility, build trust and then let it blossom into a customer relationship.  For SaaS companies especially, freemium is an essential part of a pricing strategy. At the unConference, we identified two freemium models that trade-off functionality versus volume.

ConstantContact, a leading email marketing firm, has had success by providing full functionality, but limits volume to 100 email addresses.  Beyond that threshold, charges kick-in.

SurveyMonkey, an online survey tool, allows users to create any number of surveys and participants, but limits the functionality – number of questions, types of questions, branching, etc.   More sophisticated surveys require an upgrade.

Both models are viable because they cleverly take into account the user’s economics.  That’s the key take-away: to establish a reasonable threshold where a free customer is willing to pay a little more to get more.  

And what about “freeloaders”, those users who will never cross the paid threshold?  They can turn out to be an important referral base to other paying customers. Speaking from my own experience, this has certainly been true for ConstantContact and SurveyMonkey.

I’d welcome other great examples of freemium.    Feel “free” to comment!!

Ed Arnold
Director of Products
LeveragePoint Innovations

A Tough Year For Software: Thoughts on Driving Growth and Margin

A Guest Post by Tom Lucke

It’s been a tough year for the software industry.  Enterprise IT budgets have been slashed, corporate layoffs have reduced the need for incremental seat licenses, and consumer PC sales are off. Even the supposedly recession-proof consumer video game market has been hard hit. 

A few statistics show just how difficult the last 12 to 18 months have been for the software industry. Among a representative global group of 259 software companies  I recently analyzed: 

•  From Q1 2008 to Q1 2009, aggregate revenue grew by only 6%, down from annual growth rates of 16% in 2006 and 18% in 2007
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• Fully 45% of the software companies in this group saw their revenue fall between Q1 2008 and Q1 2009 – with an average drop of 17% over this period

Certainly the global economy is challenging, and will remain so for some time. However, my recent work in software has made it clear that the current environment presents software companies with a unique set of short- and long-term opportunities to increase profitability and growth by: 

(1)    Improving near-term price realization; 

(2)    Restructuring existing products; 

(3)    Preparing for the inevitable upswing in larger deals; and, 

(4)    Moving aggressively to investigate new software business models.

Improving Price Realization

Given the relatively high gross margins of the software business, there’s always a temptation to engage in ad hoc discounting to ensure a sale. Even in companies with relatively strong controls on discounts, it’s not unusual to see wide variations in net prices. For example, I’ve seen many clients with ASPs that vary by 20% to 40% across similarly situated customers – even after adjusting for both the size of the deal and the size of the overall relationship.  While this type of discounting certainly does drive some amount of incremental revenue among price sensitive customers, it also fuels an ongoing decline in ASP, damages long-term customer relationships, and unnecessarily reduces margins. 

My experience is that a coordinated program to improve price realization can produce significant near-term increases in the bottom line. This isn’t about just tightening discount policy – the key is to understand the magnitude and pattern of unneeded discounting, and then identify and address its root causes. 

For example, in one case, analysis of discounting patterns revealed that many of the customers who had received particularly high discounts had evaluated my client’s product against a less functional (and less much less expensive) competitive offer. Isolating this issue and developing sales materials that provided appropriate point-by-point comparisons substantially reduced the problem. Very often, careful analysis will reveal groups of customers who game the system to win discounts that are large relative to their peers. In this case, the solution is to use a combination of non-price incentives and account-specific programs to retrain these customers and wean them from additional discounts.   

Even in a market as challenging as the one we are in today, approaches like this can rapidly improve margins.

Restructuring Existing Products

The slowdown in global software sales is the result of a complex set of forces.

• IT departments have cut their budgets and focused their remaining funds on projects that deliver significant near-term business results
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• Deployments are generally smaller, and customers have made it clear that they want to buy in more relevant and “bite sized” functional increments
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• Finally, changes in both company economics and their IT environment are making customers think long and hard about the value of high-end software features

In short, customer’s perspectives about what is valuable have shifted. And for many customers the price-to-value relationship for existing software packages is no longer compelling. Importantly, many of these shifts are likely to be durable, lasting well beyond the end of the current economic downturn and requiring fundamental changes in how software companies configure their offers.

The solution is to adapt existing suites of products to these new customer requirements. This means developing a clear understanding of which specific elements of the software offer create economic value for different types of customers. These elements could be specific features, or they could be aspects of the business relationship (e.g., availability of different license types, flexibility of upgrades, ability to select appropriate support levels).  Understanding value in this way allows a company to selectively reshuffle offer elements and provide specific groups of customers with new, more appropriate combinations of price and value – increasing growth and improving margins. Importantly, it’s usually possible to make many of these changes without the need for complex and time-consuming development efforts. 

In one case, the solution was to recombine existing functionally-defined software modules into packages that were structured around important and well understood business activities. In another case, the answer was altering the licensing metric (which had been $ per server) to a different one ($ per port) that created better alignment between price and value across a broader range of customers. Of course, there are often longer-term product restructuring opportunities that can be identified as part of the process – the key is to pursue the best near-term options, while developing a prioritized roadmap for longer-term changes in product architecture.

Preparing for Larger Deals

One factor in the downturn in the software industry has been the relative absence of large enterprise deals.  But corporate IT budgets will recover, and large-scale deployments that have been on hold will eventually move to the fore. Unfortunately, the return of these large deals will place significant pressure on ASPs and margins. As always, the largest deals will be highly competitive with multiple suppliers vying for the business. At the same time, corporate procurement organizations will aggressively bargain for the lowest possible prices while refusing to acknowledge differentiation among vendors. 

Simply put, now is the time to prepare for the return of these larger deals. Success in large account sales stems from the ability to develop, price, and defend a differentiated offer that produces clear economic benefits versus the competition. The key is to develop a superior understanding of the customer’s economics and the competitor’s capabilities – two areas where vendors often find themselves outmatched by procurement. 

For example, in a recent case a client was told by a prospective customer that a competitor could provide essentially the same benefits at roughly half the price the client was offering. By digging in to the customer’s economics, it became clear that while this was narrowly true for one functional element, the overall economics favored the client’s solution. Using this insight, we crafted a revised offer that resulted in the client winning a greater share of the customer’s business at a higher aggregate margin. Developing this type of information – and drawing implications for potential deal structures – takes time and focused effort, but typically yields substantial rewards.

Investigating and Testing New Business Models

Across the industry, the traditional software model of perpetual license plus maintenance has remained relatively strong. Nevertheless, cracks have recently begun to appear:  Renewal rates for maintenance are down for some vendors, and upgrades are lagging in other cases; some vendors have also reported more interest in subscription models, and several companies offering SaaS have seen significant growth. A combination of tighter IT budgets and a lower tolerance for risk is forcing companies to fundamentally rethink how they acquire, use and maintain software. The current economic turmoil, then, seems likely to spark a broad and sustained re-evaluation of software business models, as both customers and vendors look for alternatives.

Going forward, multiple models will co-exist, even within individual vendors. That is, some customers will best be served through a SaaS model, others via subscriptions, others through new models of licensing and maintenance. The key for software companies is to understand which segments of the market will benefit most from which models, and then structure their business accordingly. Analytically, this means understanding the economic benefits that customers obtain from different models, and comparing that to the benefits that accrue to the vendor (e.g., access to new market segments, increased growth, and higher margins). Operationally, vendors need to develop a thoughtful transition plan that takes into account the impact of new models on revenue recognition, revenue mix (e.g., license, service, other recurring, etc.), profitability, and company valuation.

The Path Forward

Despite the challenging state of the economy, my recent work in software suggests that now is the time to position for improved growth and profitability. In particular, there are substantial near-term returns that will accrue from better aligning market price, offer structure and value, and there are significant longer-term opportunities that will arise from identifying and deploying an optimized set of software business models.

About the Author

Tom Lucke works with clients in software, IT, technology, and telecommunications to develop and implement competitive marketing and sales strategies. 

He can be reached by email.

This post copyright (c) 2009 by Tom Lucke. All rights reserved.