Key Tenets of SaaS for Startups

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Earlier today I was emailing with an entrepreneur seeking advice. After a few emails back and forth about pricing he asked if he could charge more to customers who got to use the latest version of the software. Wow, I was taken aback as we’re talking about a Software-as-a-Service (SaaS) application where all customers should use the same version. That got me thinking about some of the most important aspects of a SaaS startup. Here are a few key tenets of SaaS:

  • The application should have a multi-tenant architecture where all customers use the same version of the product on one or more shared databases
  • Product enhancements and fixes should be pushed on a frequent basis
  • The most important word in software-as-a-service is “service” and not “software”
  • Customer acquisition costs and on-boarding costs should be appropriate for the monthly/annual fee
  • Churn should be studied as closely as sales and marketing

SaaS is a phenomenal business model once it is up-and-running but presents its own unique set of challenges. Entrepreneurs should understand these key tenets of SaaS and work to incorporate them into their startup.

What else? What are some other key tenets of SaaS?

6 thoughts on “Key Tenets of SaaS for Startups

  1. David, what about live testing features & other code changes on small subsets of users? Technically, that is a different version of the software.

    Perhaps, that entrepreneur can have a-la carte offering of advanced resource-intensive and/or rarely used features if he wants to generate more revenue.

  2. Another key tenet for SaaS is continuous updates. Not just hotfixes, but new and improved features. At Salestrakr we sometimes will get a feature request and push it out the same day. Great way to delight your customers.

  3. We really like the flow of ideas from our customers. Any one customer might only contribute a little, but in the aggregate it makes the product better for everyone else.

    I’m interested in hearing any thoughts on pricing models … what’s worked well and what has not.


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