Software is licensed and centrally hosted (vs. hosted by the customer) available through digital interface (app, browser, device).
Less IT infrastructure and support needed
Delivered digitally, lower setup and maintenance costs
Overcome benefits of ownership
Risk managing security in cloud-based data
Integration across multiple SaaS and on-prem solutions
Total cost to breakeven vs. on prem offering
Cost of ownership and maintenance vs. usage
Low friction shorter sales cycles move to departmental buyers
Click to ship vs. costly installs
No need for multiple versions of the software
Often need a two-step value proposition
1 for user (first) 1 for manager; or third value prop for data security
Net Promoter Score
Ratio of CAC (cost of customer acquisition) to LTV (lifetime value)
Delivered digitally, hosted for all
Before SaaS methods of delivery, software was sold as a perpetual license with an up-front cost. For example with Microsoft Office, customers paid an upfront licensing fee and bought a boxed set of floppy disks and uploaded the software to their personal computers.
Now, you have a choice for how to buy Microsoft Office – either as a one time fee for one personal computing device, or as Microsoft 365 – a set of licenses for PCs and other devices sold as a yearly subscription. The software resides on the host server from which all users access it.
Delivery via internet enables this method of subscription, and the proliferation of mobile and multiple devices increases the value of having the software available on multiple devices.
Low initial setup costs, lower maintenance costs for the customer
The initial setup cost for SaaS is typically lower than the equivalent software for both the customer and the Saas company. Companies typically price their software based usage, such as the number of users using the application, the number of devices, or the the volume of data being accessed. The low cost to set-up creates an opportunity for companies to offer a freemium model. Successful SaaS companies have been able to disrupt incumbents by pricing their total cost of ownership at a price substantially lower than “on-prem” or on-premises software, with demonstrated return on investment.
Naturally noisy user adoption
Many SaaS applications offer features that let its users collaborate and share information, thereby increasing the network effects and rate of user adoption. For example, project management applications delivered in the SaaS model such as Basecamp, Asana, and Slack offer collaboration features letting users comment on tasks and plans and share documents within and outside an organization.
Two-step value proposition
Tom Tunguz, a prolific Venture Capitalist scribe on the topic of SaaS, advocates for SaaS business targeting small and medium sized businesses to have a two step value proposition:
1/ An initial value proposition to the end user
2/ A longer term value proposition to a manager/decision maker
The proliferation of enterprise applications designed with the ease-of-use and addictive quality of consumer applications drives this point home – companies such as Slack, Evernote and Dropbox created free and easy-to-use versions of the software. When the manager of the early user adopter is made aware of the productivity advantages of whole department, or whole company adoption, the longer term value proposition kicks in.
Monthly recurring revenue (MRR)
In subscription-based SaaS models, customers tend to stick around for a while (the customer lifetime) and deliver steady streams of predictable revenue. Revenue is smoothed vs. lumpy, as the company does not have to worry about pushing for one-off sales and can better control marketing and sales costs. Instead, focus shifts to retaining customers, and reducing churn or loss of customers. Happy customers even increase their service and stay even longer as a customer, positively affecting the profit that can be made.
Shape go-to-market to the size of the enterprise customer
If the SaaS company is not clear about the different economic models involved in serving different customer segments, profitable scale is difficult to attain.
Successful SaaS companies pick a target and stick with it: enterprise customers, SMBs (small to medium businesses, or SOHO (small office, home office). When targeting large enterprise customers, the SaaS company can afford a direct sales staff to hunt new business and an inside sales team to nurture, as long as they land large enough price points for their cost model to work. These same companies however may be unprofitable for the first 12-24 months of a given customer’s life, and adding more customers in a growth curve may put further strains on profitability.
Companies targeting the smaller sized firms need to attract much higher rates of new customers through freemium and effective marketing strategies without relying on a salesforce as the primary acquisition channel. However the customer service team can function as effective inside sales – or sales made from a desk (vs. out in the field). The inside sales team’s job is to contact leads generated from the freemium side of the business and convert those users into paying customers..
Risk of becoming a professional services model
Another key risk for a new SaaS company is when founders lose discipline and never break out of a keep-the-customer-happy professional services business model. Customers often have unique needs when adopting software, and the growing SaaS company cannot respond to every request or need. The purpose of SaaS is to find the common denominator of need among a large customer base, and translate those pain points and needs into a common solution, delivered primarily through a software experience.
SaaS companies often have a small consulting services arm to handle requests that are not solved in the software alone. For example, when professional social media management suddenly became a need in the workplace, companies like Radian6 and Buddy Media (both later acquired by Salesforce.com) built small consulting services groups to train customers on how to manage social media, and extract insights from data. But these companies were careful not to build large consulting arms, and kept the types of problems solved limited to those needs that arose in adopting and using the software.
Risk of not understanding unique customer needs
SaaS companies lose out to incumbent competitors when they are perceived to be out of touch with their customer needs, and unable to solve core IT and strategy problems.
Controlling cost of customer acquisition in growth phase
Successful SaaS companies often experience hyper-growth as they reach scale, but some struggle to maintain profitability through growth. The investor rule of thumb: customer lifetime value should be three times the value, or more, of acquiring a new customer. A number of public SaaS companies have struggled to reign in cost of acquiring new customers while in growth phase, particularly in competitive sectors.
Because data is being stored on the SaaS company servers, data security becomes an issue. When SaaS applications require access a customer’s current data (such as an end users’ personal information), integrated on remotely hosted software can conflict with data governance. For example, healthcare organizations often have their own data governance policies that severely limit the integration of patient data into cloud-based software hosted off premises.
SaaS Integration Platforms
Because there are so many fragmented SaaS providers, SaaS integration platforms (SIPs) are emerging. Subscribers are then able to access multiple SaaS applications through a common platform. For example, both Salesforce.com and Slack provide an Application Protocol Interface for SaaS developers to deliver on their platforms.
Consumerization of IT
An ongoing trend is the consumerization of IT. The proliferation of the iPhone and well designed apps within the app store for consumer experiences raised expectations for software in the workplace. Why was business software in systems like Microsoft Office, SAP, and Oracle so clunky and hard to use? This created a window for design-led products to tap into a growing demand for easier-to-use apps like Dropbox and Evernote that were designed to be adopted by individual users, first, before being adopted and paid for by the company’s IT department.
As a result of the consumerization of IT and “bring your own device” trends, employees take matters in their own hands, tired of waiting for IT organizations to catch up, and use their own solutions to fill the void. This leaves C-Level execs, VPs and other managers unaware of how work is getting done and how data is being used inside their companies.
Data-as-a-service (DaaS) is a newer form of delivering the core utility of SaaS in the form of valuable data served via the cloud for a fraction of the cost (vs. hosted in company-owned data repositories).
Key SaaS Mechanisms to Test
KPIs depend on your unique business attributes and business model combinations. However there are heuristics when investors evaluate a software-as-a-service model.
Special note for SaaS in the seed stage: test the ideal customer type for your service – you will later form your sales ramp-up strategy this way (revolves around size of customer from consumer to SOHO to SMB to Enterprise).
- How do you go about purchasing and using this solution today? (Probe for primary issues, determine if there is a hidden cost of ownership, understand other pain points involved in purchase and use).
- Test for jobs to be done, level of pain on the pain scale. How much of a priority is the defined problem or pain?
- Is this a balance sheet capital expense, or is it expensed on your income statement? If balance sheet, would you benefit from shifting ot a lower expense on the income statement?
- How does the customer handle cloud-based and on-prem software decisions? What are the pain points of integration?
- What is the total cost of ownership of comparable solutions?
- Arrange features, services, and benefits into key elements of your offer and have the potential customer arrange the elements of the larger solution in order of priority. Then take away the lesser priority elements until you determine what would make an MVP (minimum viable product).
- Determine the minimal offering that would be compelling enough to have the customer pay for the offering.
- Can you design an MVP that has high usage and engagement with a minimal feature set?
- Is there a user proposition that does not require sign-off from IT or a long buying cycle?
More on SaaS
The Business Model of “Software-As-A-Service” by Dan Ma, IEEE, 2007 (academic paywall)
Evaluating the Software as a Service Business Model: From CPU Time-Sharing to Online Innovation Sharing, by Markku Sääksjärvi, Aki Lassila, and Henry Nordström, IADIS International Conference e-Society, 2005 (PDF)
Bessemer’s Top 10 Laws of Cloud Computing, by Byron Deeter,Bessemer Venture Partners, 2016
What’s in a Name? Distinguishing between SaaS and SOA, by Phillip A. Laplante, University, Jia Zhang and Jeffrey Voas, IT Professional, 2008 (academic paywall)
Ten Year’s Worth of Learnings About Pricing, by Thomas Tunguz, LinkedIn, 2018.
SaaS Metrics 2.0, by David Skok, 2019
What the Second Time SaaS CEOs are All Doing, by Jason Lemkin at SaaStr, 2014.
Design Choices Underlying the Software as a Service (SaaS) Business Model from the User Perspective: Exploring the Fourth Wave of Outsourcing, by Anton Joha and Marijn Janssen, Journal of Universal Computer Science, 2012 (PDF)
SaaS Financial Plan 2.0 by Christoph Janz, Enterprise Irregulars, 2016
SaaS Metrics for Entrepreneurs by David Skok, For Entrepreneurs, 2013
The 8th Do for SaaS Startups: Stay on Your KPIs by Christoph Janz, The Angel VC, 2013
The Most Important Trends in SaaS by Bubba Page, Inc.com, 2016
The Unprofitable SaaS Business Model Trap, by Jason Cohen, VentureBeat, 2013
ADP vs. Zenefits and SaaS Business Models Edition, by y Jon Reed, Diginomica, 2015
Themes in SaaS in 2016, by Jason Lemkin, Enterprise Irregulars, 2016.
Is it SaaS? Is it ARR? by Jason Lemkin, Enterprise Irregulars, 2016
CAC Payback Period: The Most Confusing SaaS Metric, by Dave Kellogg, Enterprise Irregulars, 2016