"Issues in Shifting from a Product-Based Business Model to a Service-Based Model"

Rich Mironov

The shift from sales of software licenses to hosted Software-as-a-Service business models drives changes in core assumptions about selling approaches, usage-focused marketing, and customer

feedback mechanisms.

Submitted to Berkeley-Tekes Service Innovation Conference (Institute of Management, Organization and Innovation, Haas School of Business and the Finnish

Funding Agency for Technology and Innovation)

OverviewMost technology firms have traditionally built “product-based business models”. These business models portray the features and benefits of a product artifact, define ways for customers to use that artifact profitably, and create pricing mechanisms tied to upfront selling objectives. An increasing number of technology businesses, however, are replacing classic product selling and pricing with service-based models such as subscriptions and per-transaction pricing. This shift creates both obvious and subtle conflicts with product-based business models, and requires firms to evolve a “services-based” business model. The firm must take on responsibilities previously outside its scope (such maintaining operational systems), and encouraging product usage through continuous installed-base marketing.

The issues and opportunities posed by this shift to service business models are best illustrated in the software market. The classic product model involves shipping a piece of media that contains software, which the buyer installs onto desktop computers or corporate-owned servers. Along the way, the customer becomes responsible for operations, support and internal evangelism of the product. In contrast, a service-based business model (such as online applications, software-as-a-service and web services), requires the vendor to take on operational responsibility and ongoing internal promotion – while helping the customer successfully use the service. Product-based assumptions about technology marketing, selling and support of customers are undercut by service-based business models.

Over the last decade, I've held executive product/marketing roles at four technology startups, and consulted to two dozen other technology companies. An increasing portion of this work is with firms considering a shift to service-model strategies – where they host multi-tenant software applications and sell subscriptions or per-transaction services. This paper discusses the shift to software-as-a-service in four steps:

Rich Mironov is a product strategy consultant, serial entrepreneur and veteran of four startups. He holds an MBA from Stanford University and a BS Physics from Yale University. He consults on product strategy, pricing and product management to technology companies. He also writes a newsletter on early-stage product strategy called Product Bytes (http://www.mironov.com/articles/). Previously, Mr. Mironov was VP Marketing at AirMagnet Inc. and Slam Dunk Networks, and held product management/technology roles at HP, Tandem, Sybase, Wayfarer Communications, and iPass Inc.

I. Why Software-as-a-Service is good for customersII. How service models reshape the revenue cycle

III. The need for more focused upsell marketingIV. Gathering accurate customer usage information

Note that these are firm-level changes, requiring planning and resource allocation of company-wide resources, rather than product-level adjustments. Software firms moving from licensing models to service models need to involve more than just their Marketing, Product Management and Engineering organizations.

Executive teams must recognize their new service obligations to customers, and rethink functional groups to provide 24*7 operational systems support; expand analytical marketing expertise; shift sales staffing to lower-cost inside sales; redesign sales commission structures to handle slower customer value capture; etc. Delegating this structural shift solely to Marketing is a recipe for failure.

I. Why software-as-a-service is good for customers Technology companies with service business models are not new. Automatic Payrolls, Inc. (later ADP) was formed in 1949, partly driven by the high cost of early computing equipmenti. A wave of software-as-a-service companies started emerging in the late-1990's, supported by the spectacular growth of the Internet, ubiquitous browsers, and heavy venture capital support. Companies like SalesForce.com, WebEx, NetLedger and Ketera provide corporate services-on-demand, with a new generation of Software-as-a-Service (SaaS) infrastructure plays including OpSource and Cordys capturing the attention of venture investors and the popular business press.

The emergence of Software-as-a-Service has been intensely coveredii. Some of the most important reasons for enterprises to use third-party software-as-a-service include: Passing of responsibility for software, systems, operations, service levels and capacity

planning to an outside vendor Avoidance of large up-front licensing fees and capital equipment costs Ability to start with small increments of service, and ramp usage (costs) as value is

established Immediate access to standard, working applications (or faster access to slightly customized

applications) Vendor responsibility for software revisions and upgrades, which are no longer revenue-

driven events Buyer's leverage from vendors' efficiency and cost advantage (through supporting many

customers on a single multi-tenant application) Outsourcing of support for end users

In some cases, traditional software licensing or in-house application development continue to be the best alternatives for enterprises. Reasons for this include: Strategic applications that may embody a company's core intellectual property or market

advantage. For example, investment banking firms create their own sales-and-trading systems to out-trade each other. Logistics companies invest in proprietary shipping systems. Executive recruiting firms may use custom resumé-screening software.

High-volume customers can save money by licensing solutions rather than renting, leasing or paying per transaction

Security and privacy issues may force companies to keep their applications and databases inside their firewalls and under their direct control

Standardized applications may not exist in selected vertical markets, or a company may have unusual product requirements

Enterprises are risk-averse in their application choices, which has driven them to hold back on software-on-demand choices while vendors show early successes elsewhere. Now that SaaS successes are easy to find, and given application replacement timelines over the next decade, SaaS vendors will have growing enterprise opportunities.

II. How service models reshape the revenue cycle Historically, enterprise software vendors have focused their marketing and sales on large up-front licensing deals, where customers pay sizeable fees before getting any direct benefit. Prospects are wooed during long sales cycles, treated to software demonstrations on test systems, and pushed to use vendor-supplied feature lists as the basis for RFPs. Since the decision-making and purchasing cycles for software licenses are painfully long, customers are encouraged to sign licenses that cover additional users or capacity ("headroom") rather than revisit contracts as incremental licenses are needed. Much of this software becomes "shelfware" – unused licenses bundled into larger deals.

Driven by the overwhelming power of the Internet and increasing competition from upstart service-model vendors, we are now seeing many software vendors reconsider their fundamental business models. They are responding to their enterprise customers, who are now willing to consider vendor-hosted solutions for all but the most strategic applications.

This dramatically reshapes the software marketing and sales process. Most hosted service offerings are initially sold to a few pioneering subscribers (users). After signing up this handful of enterprise users, the SaaS vendor must immediately shift to a new phase of the marketing/sales process: upselling. Upselling includes encouraging the enterprise to add more users, trade up to expanded feature sets, buy more storage capacity, or otherwise increase its monthly subscription amount.

Software firms moving to service business models should expect their revenue streams to develop more slowly, needing one to three years of subscription fees to deliver comparable revenue to an initial licensing sale. This is the mirror image of their customers' reduced upfront costs and decreased commitment: enterprise customers pay over time, with less revenue to vendors in the first year. Customers like the lower commitments and timed spending of service models, which translates directly into lower initial revenues for vendors. With shorter sales cycles and annuity pricing, service models provide much more stable revenue streams, typically catching up in Year 2 or Year 3.

For service-model startups, this also increases their initial capital requirements. In addition to building software applications (as they did under licensing models), vendors must equip and staff an entire operational infrastructure for high availability on-demand applications. This additional investment includes redundant systems and network connections; disaster-resistant data storage; security auditors and intrusion prevention; first-line end user support; change control processes for software deployment; etc. The vendor's cost to bring up its first customer is significantly higher than for licensed-software competitors. Coupled with a slower initial revenue stream, this suggests a doubling (at least) of capital requirements to establish a service-model business.

Once established and running smoothly, incremental capital requirements are sharply lower. Service-model vendors can add new customers with almost no marginal costs: provisioning more

users on a multi-tenant application is a trivial database exercise. In addition, R&D efforts are focused on a single stream of software that serves all users (unlike licensed software firms, which maintain distinct product versions for many customers/platforms, diluting their engineering effort). Over the longer term (3+ years), a successful service-model business should be much more profitable and financially scalable than a similar license-model firm.

In a recent survey of product managers and product marketers (PMs), 95% of those selling 'products' identified their top incremental revenue methods as "selling new versions/major upgrades" or "selling more units" – versus 64% of PMs with service offerings. In contrast, 94% of PMs selling 'services' identified their most important upsell opportunities as "moving customers to higher-priced subscription tiers" or "adding more users to customer's subscription" – versus 57% of product PMs.

Service PMs also reported shorter average sales cycles than product PMs. The average subscription sales cycle was 23 weeks versus 35 weeks for products (35% faster). Transaction-model service vendors were even shorter: at 17 weeks, they were 51% faster than product sales cycles.iii

This reinforces the idea that on-demand services are easier to sell than traditional licensed software, although initial revenue is lower.

In addition to slower initial revenue streams, service-model vendors take on a variety of new risks. Unlike licensing vendors who can "drop the goods and run" after completing a sale, the service-model vendor always has subscription revenue at risk. Customers retain the right to cancel or curtail service payments for many reasons including: poor system availability; reduced numbers of users; unrelated application decisions; leakage of personal data; disagreements about invoiced items; changes in customer financial position; etc. In a subscription model, power stays with the customer – in stark contrast to product vendors, who have only marginal maintenance renewals at stake.

Thus service-model vendors capture initial revenue more slowly while also taking on new obligations. To justify this combination, they must forecast broader and faster adoption of their on-demand solutions (versus licensed strategies) and longer-term customer relationships.

III. The Need for More Focused Upsell Marketing Given the slower revenue ramp of services versus licensed software, service-model businesses must stay tightly engaged with customers to identify upselling opportunities. This implies the need for continuous usage-focused marketing and episodic sales contacts.

In the traditional software licensing model, vendor communications with enterprise users tends to be sporadic and poorly focused. The marketing process tends to focus on economic buyers (company executives) and a handful of potential users, rather than the broad community of potential users. In addition, there is a lack of specific contact information about actual users: software vendors may never discover the names of actual users, since the software is run at the customer site and managed by customer IT without externalizing user information. Vendor marketing outreach – newsletters, training, events, user group meetings, and other community-building efforts – thus normally miss the majority of actual software users.

The licensed software sales process is similarly sporadic. Enterprise sales teams tend to be "big game hunters" rewarded for closing large one-time deals. They often roll future upgrades and maintenance into current-quarter deals, offering customers dramatic discounts on future software and services in order to pull as much revenue as possible into the current fiscal period. Having extracted the maximum money from each customer, there is little reason for the sales team to return – until multi-year contracts expire or new products can be cross-sold into the existing customer base. Software licensing models align with sporadic, broadly impersonal marketing and single-transaction selling.

Software-as-a-service business models demand a different approach. As noted above, most initial service-model transactions are entry-priced subscriptions for a small number of users. These transactions turn a prospect into a customer, but not into a highly profitable customer. Marketing and selling must continue while the earliest users find value in the service. The service-model vendor must grow each account to its revenue potential – by finding new users and/or promoting more advanced features. .

Case Study: Replicate Technologies

A new Silicon Valley start-up, Replicate Technologiesiv (http://replicatetech.com) recently entered the marketplace with a subscription-based service for rapidly reconfigurable test systems. Using proprietary technology combined with available products, Replicate provides hosted servers that customers can quickly configure and reconfigure for software testing and technical support.

A typical client is a software company that needs to test its code on a wide range of operating system versions and patch levels, or with a variety of customizations, or with new software releases. In each case, the client can quickly load one system configuration and run required compatibility tests, then load a different system image for the next set of tests. Technical support teams can keep a wide variety of system configurations "on the shelf" and load them as needed to help identify customer problems.

By offering this as a service, Replicate competes with many vendors licensing virtualization software for customers to run on their own hardware in their own data centers. This gives Replicate's customers some clear advantages versus licensing: No need to hire or train skilled virtualization engineers No need to buy, maintain or manage dozens of servers No upfront capital expense Ability to add capacity (servers, configurations, storage) when needed, without long

ordering, purchasing or installation cycles Easily sharable test resources for geographically distributed teams Ability to "snapshot" systems with software defects and repeatedly "replay" the

defects for software development or QA teams

Customers can license competing virtualization software products for thousands of dollars, then acquire and manage all of the necessary system components to create a software test lab. Instead, Replicate delivers a turn-key service with pricing packages based on numbers of available CPUs and storage for specific numbers of instantly available system configurations. Pricing is less than 10% of the cost for a customer to acquire and install in-house software/hardware systems.

Nearly every one of Replicate's early customers had a specific testing project in mind. Each agreed to initial subscriptions sufficient for these first projects, but much less than Replicate's long-term revenue potential per customer. The marketing and selling process, therefore, continues well past the first purchase order. Replicate's marketing and support teams must keep in close contact with its existing users – keeping clients happy and reminding them of additional opportunities for Replicate to help them. Internally, they estimate that customers can grow to about triple their initial commitment as each uses Replicate for different kinds of testing, or as different groups within the customer adopt a common solution.

There is also a clear timing component to follow-on sales. Replicate's solution is most valuable at the beginning of a testing project or new software development effort, when QA infrastructure choices are made. If the customer has already implemented alternate virtualization approach or test system deployment, switching to Replicate could cause additional work and divert resources from other tasks. Replicate must therefore identify new projects at their inception, and focus on selling into existing customers when such projects appear. Since clients' project timelines are unsynchronized and unpredictable, Replicate must be very attentive to opportunities within its installed base.

As we see in Replicate's situation, marketing and selling of a hosted service does not follow the traditional "dump and run" licensed sales model. The hosted service vendor must find and close a "pioneer" user within the enterprise, help that user demonstrate success, and then evangelize the service to other potential users within that enterprise. Initial revenues in this model are much less than in software licensing, even while the vendor takes on more responsibility for satisfactory results.

The reward for service-model patience and lower up-front fees comes later. By Year 3, the vendor should have captured total revenue similar to an initial license fee. This annuity income is also more consistent than product sales models, giving the firm some stability in its sales forecasts. Service-model firms that can survive and grow eventually become highly profitable.

IV. Gathering accurate customer usage information As noted above, service business models drive the need for more effective upselling to existing customers. This usually requires deeper insights (and information) about what existing customers are doing. Historically, licensed software vendors have been unable to accurately gauge customer behavior. Service businesses have an important advantage versus their product-model competitors: they can gather actual usage information and determine with precision what their customers are doing.

Technology companies have traditionally relied on a variety of second-hand information sources about their customers' product usage and satisfaction. These tend to be incomplete, biased, subjective or otherwise qualitative – including small numbers of live sales calls, tech support cases, key customer meetings, user group surveys, formal enhancement requests, industry analyst findings, and independent product reviews. Overall, these feedback mechanisms are based on scant input and may include "gaming" of the process: PMs and marketers are appropriately suspicious of feedback channels where participants bring their own agendas.

Hosted service models create a huge opportunity for service companies (and specifically for PMs) to see precisely what each customer is doing. They suddenly have access to transaction logs,

online help queries, and other hands-on information of how users interact with their systems. This allows quantitative research into which portions of the application are being used – successfully and unsuccessfully.

In addition, the service firm can target sub-groups of customers based on their behavior. It becomes straightforward to segment for customers reaching capacity on their existing service packages dormant accounts (with no usage) that need refresher training and reminder emails power users stretching the capabilities of the existing system application areas that generate too many technical support calls or operational errors smoothly operating clients that may be candidates for marketing success stories

In our PM survey, 21% of service PMs reported using transaction logs to identify which features/functions their customers use, versus 1% of product PMs. This is a huge increase, but still disappointing – the vast majority of service PMs should be spending time every day reviewing end user behavior. The lack of transactional insight is probably due to poor analysis tools, lack of experience among PMs as they shift from products to services, and a failure of enterprise marketing management to demand good metrics.

Consumer-focused service firms such as Google have pioneered quantitative user analysis. Google often introduces new services as "beta" offerings, or to selected subsets of its visitors, gathering a few days of actual user experience for each of several service configurations. Google usability experts and PMs can then compare actual results, contrast alternate versions, watch click streams, and generally do "live" service testing. PMs can get near-real-time results, replacing traditionally old and inaccurate survey/interview techniques.

Access to live application usage data can provide some of the marketing infrastructure for focused upsell marketing. Our survey data (and my experience) suggest that another kind of improvement is even further from widespread adoption: pruning of applications to remove unused features/functions. Both service-model and product-model PMs reported that their typical customers use roughly 50% of available features. As service-model companies begin to mine their own transaction logs to learn what users do, they have an opportunity to identify what their users don't do – and remove obscure features in favor of more mainstream value.

Implications for Technology CompaniesMost software firms see the success of some early SaaS vendors and the emergence of new service-model competitors. Each firm must decide if it should refit existing licensed software products into hosted services. In addition to the broad strategic risks inherent in changing business models, companies need to gauge their ability to invest in the new thinking that a hosted software service requires.

Once the firm decides to adopt a service business model, it will need to reshape marketing and sales processes to fit continuous installed-base upselling. It will also need to manage a sizeable slow-down in service/subscription revenue during the transition period, coupled with continuous lifecycle marketing to identify upsell opportunities within its installed base.

Appendix: Product Management/Marketing Survey We surveyed 204 product managers, product marketers and corporate marketers to determine how their upsell models, customer outreach and communications approaches varied across different business models. Product Bytes readers and members of the Silicon Valley Product Management Association (SVPMA) were invited to participate. Results were gathered between from 31-January and 5-April07. Statistically significant differences are marked in blue italics.

Pricing and Product modelFocusing on my core product or service, it is primarily priced (sold) by... Responses ...of total  

One-time fee/license plus annual maintenance 99 49%

Subscription, such as monthly fee per user 47 23%

Transaction [per fax, per download, per transplant, per report, per hour, per update...] 38 19%

Free, advertising-supported or other 20 10%

My primary product/service consists of...Product Model

Subscription Model

Transaction Model

Hardware at the customer site 38% 11% 21%

Software at the customer site (other than browsers and plug-ins) 82% 30% 21%

Shared, hosted software and hardware at our site 12% 64% 18%

Dedicated software and hardware at our site (used by individual customers) 6% 13% 16%

Intangibles (advice, contracts, IP licenses) 12% 19% 45%

None 0% 0% 8%

Targets and Upsell ModelThe main target market(s) for this product/service...

Product Model

Subscription Model

Transaction Model

Consumer 11% 15% 21%

Small/Medium Business 35% 57% 42%

Enterprise 65% 56% 57%

Government 28% 15% 5%

Other 10% 4% 8%

Important/Very Important sources of additional revenue from existing customers...

Product Model

Subscription Model

Transaction Model

Selling new versions/major upgrades 77% 45% 39%

Selling more units (boxes, copies, devices) 81% 47% 50%

Moving customers to higher-priced subscription tiers 29% 83% 42%

Adding more users to customer's subscription 44% 72% 32%

Professional services 63% 53% 50%

Selling supplies and consumables 7% 4% 8%

Sales ToolsDuring the sales process, which tools for prospects are Important or Very Important?

Product Model

Subscription Model

Transaction Model

Presentations and marketing materials 84% 94% 68%

Data sheets and feature lists 78% 72% 58%

Full documentation 48% 38% 29%

Demonstrations, where we show the product/service 74% 85% 55%

Limited-time free trial (all features/functions) 53% 55% 32%

Limited-time paid trial (all features/functions) 25% 26% 16%

Free version or trial with reduced feature/function 22% 32% 20%

Third party reviews and product comparisons 63% 70% 53%

Press releases 63% 68% 47%

Blogs and word of mouth 61% 74% 68%

References from existing customers 80% 87% 84%

Competitive ComparisonsProspects typically compare us to the competitors using...

Product Model

Subscription Model

Transaction Model

Direct trial of the product/service 51% 40% 26%

Crippled or feature-limited versions 6% 4% 3%

Feature matrices or lists of requirements 65% 45% 29%

Analysts and third party reviews 46% 40% 34%

References 54% 60% 47%

We have no direct competitors 1% 4% 8%

Our average sales cycle is...Product Model

Subscription Model

Transaction Model

Less than a week 5% 5% 9%

One to ten weeks 1% 0% 0%

One to two quarters 15% 32% 50%

Three to six quarters 37% 45% 28%

More than six quarters 42% 18% 13%

Average time (weeks) 35 23 17

Post-Sale Features and UsageWe know which features/functions our customers use via...

Product Model

Subscription Model

Transaction Model

Personal discussions 54% 47% 50%

Tech support calls/cases 35% 32% 24%

Enhancement requests 27% 17% 11%

Transaction logs, web logs, activity logs 1% 23% 18%

Sales team feedback 28% 23% 32%

User surveys 8% 19% 16%

User groups 12% 2% 3%

Mechanisms to turn on/off specific features 1% 2% 3%

I think my typical customer uses...Product Model

Subscription Model

Transaction Model

...% of available features 49% 48% 52%

Customer Contact Info

We know which companies buy our product via...Product Model

Subscription Model

Transaction Model

Sales reports 69% 60% 45%

Channel/reseller reports 29% 15% 13%

Product registration 28% 19% 13%

Online user profiles 5% 17% 3%

Tech support 19% 15% 8%

We sell only to individuals/consumers 8% 15% 5%

We know who our individual users are through... Product Model

Subscription Model

Transaction Model

Product registration 20% 32% 24%

Online user profiles 5% 17% 3%

Tech support 19% 15% 8%

Sales reports, sales team feedback 30% 28% 34%

Channel/reseller reports 14% 6% 0%

Telepathy 13% 9% 8%

Contacting UsersWe notify users of new features and functions via... ("almost always" or "sometimes")

Product Model

Subscription Model

Transaction Model

Email newsletters 60% 70% 55%

Website postings 64% 62% 56%

Paper newsletters/mailings 14% 21% 13%

Alerts within the product/service 31% 32% 24%

Press releases 58% 43% 37%

Phone calls 27% 34% 32%

User groups 26% 17% 11%

i "Fifty Years of Business Excellence: The ADP Story," http://www.adp-es.co.uk/files/site/f/e/ferrierpearce.eu.adp.com/ftp/contentpdfs/50Years.pdf

ii Timothy Chou, The End of Software: Transforming Your Business for the On Demand Future, Sams 2004; Paul Allen et al, Service Orientation: Winning Strategies and Best Practices, Cambridge University Press, 2006; and many others.

iii Survey of 204 product managers and marketers by Mironov Consulting, fielded Jan 30 – April 5, 2007. Selected results are provided in the Appendix, with fuller and ongoing results at http://www.mironov.com/more/survey_results/ .

iv Replicate Technologies, Inc., 190 Southwood Drive, Palo Alto, CA 94301. Main phone is 650-289-9518. CEO is Ken Novak, ken@replicatetech.com.