Pricing Models for Web 2.0 Software as Services

The recent advent of Web 2.0 no-software start-ups like 37signals, salesforce.com, Writely, etc. is getting plenty of attention by the media and VCs alike, but I have not seem much about the pricing model of these no-software business models.

The basic idea, repeated all over the place in Web 2.0 start-ups, is that one can develop very rich user interfaces using thin client technology. Instead of installing a local copy of Microsoft Word, you use Writely. Instead of installing Siebel in your enterprise as a CRM solution, you use Salesforce.com. And so forth. Even Microsoft’s Bill Gates, highly concerned about the future of Microsoft in a world of “applications built from the grassroots” is putting forward an online Microsoft Live CRM service.

The advantage of using online solutions are allegedly savings in infrastructure and support costs. But is this really true? Will individuals and business of all sizes alike chose online services versus an offline dedicated solutions? Obviously not, so who is then the target customer? Or rather, when will a consumer chose online vs offline applications?

An informed consumer (be it a home user, a web designer, or a CIO) will make a choice based on the expected utility he gets as a consumer from the software. He will compare the utilities and chose the one that seems most likely to suit his needs. The expected utility for each option, online or offline, will surely include quantifiable factors, such as software price, downtime costs, support costs, infrastructure costs, etc. as well as perceptions such as privacy, reputation, etc.

I prepared a highly simplified utility model that I could use to bring some light. In this model the only factors I considered were:

  • Software price, for an offline solution, expressed as a monthly depreciation cost as a function of the number of employees. For solutions that require systems integration and professional services, I have diluted the cost of consulting in the total price of the solution, which then gets expressed as part of the monthly depreciation costs per employee.
  • Service price, as a monthly recurring charge by the provider as a function of headcount.
  • Infrastructure costs, for the offline solution, usually comprising storage, servers, backup, etc.
  • Service support costs for the offline solution, to support the local infrastructure costs.
  • Cost of downtime. I have assumed local class 4 availability in each domain. This translated into 0.01% downtime for offline software, 0.01% to local network, 0.01% to the local ISP, 0.01% to the provider ISP, and 0.01% to the service itself.

I have run the model with existing data for both “consumer applications”, using 37signals Basecamp and Microsoft Project for pricing data, and for “enterprise applications”, using Siebel and Salesforce.com for pricing.

The model yields interesting results:

  • For both consumer and enterprise applications, the break-even point where the software-as-a-service is not competitive anymore is somewhere around 500 employees.
  • The key differentiation between the utilities derives from infrastructure and support costs. For small to medium businesses, the cost of a dedicated and under-utilized infrastructure and service support personnel is prohibitive, and only large companies are able to realize economies of scale to make offline support viable.

We can clearly see the validity then of these start-ups, since in 2003, there were 5.7 million businesses in the US with less than 500 employees, at an average of 10 employees per firm; and 16,926 businesses with more than 500 employees, at an average of 3,300 employees per firm.

These 57 million businesses with 10 employees cannot afford the costs of dedicated infrastructure and service support, and are better off to chose an online application. For an average of 10 employees per firm, the model yields a cost of approximately $5,000/month for an offline solution, versus a $150/month for an online solution. $4,850/month of infrastructure and support savings surely justify the consumers choice.

As a side effect, the model yields a potential market size of approximately $10 billion for the Office applications, possibly close to $50 billion for the standard applications used currently in small and medium-sized businesses.

To conclude, it’s interesting to note that the online software-as-a-service business model is a side-effect of an underlying consumer pain: lack of secure shared infrastructure.

12 Comments

  • August 17, 2006 - 9:58 am | Permalink

    Web 2.0 is not an offshoot of a lack of secured shared infrastructure. By focusing on hard costs your utility model is missing some of the main benefits of Web 2.0 – like ease of use and low barrier to entry. <BR/><BR/>The true cost benefit for Web 2.0 applications comes in a) the reduced learning curve and b) the fact that an organization can try out the software without making a significant investment in time or money. <BR/><BR/>You might find my post at http://www.vertabase.com/blog/the-feel-of-web-20-software/ interesting. It doesn’t go into the economic benefits of Web 2.0 but does touch on some other intangibles which your utility model misses.<BR/><BR/>You could make your model more comprehensive by including things like training time, reduced productivity while users get up to speed, time spent on internal politics to get budget for software with a higher entry point and the size of the downsize risk associated with higher dollar entry point type software.

    • May 22, 2012 - 1:46 am | Permalink

      be able to own and control your own data,and you will be crhegad for everything you do and you will also be tracked even more so than you are now, this is a nightmare and with the google laptop you can get 16tb of cloud storage for the low low price of 350$ .per month!they have other pricing but you have a better chance of figuring out how derivatives or credit default swaps work than understanding 2 words of their so called pricing structure

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  • November 24, 2012 - 5:48 am | Permalink

    I hadn’t seen the the split by number of employees for saas versus dedicated infrastructure before.

    Your focus is primarily on cost, though in my experience the decision factors are often more subjective. How long will in take to teach my staff new technology? What is the impact on existing IT support staff? How do I transfer my data from old to new systems? What about privacy and security concerns? Friction caused by sunk costs.

    However, as more people become comfortable with these services at home, and saas service offerings outstrip in-house infrastructure offerings, I think your financial analysis will support the tsunamic switch to these saas services.

    Thanks.,

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