Maybe the most important metric in a SaaS world is “ACV” – annual contract value. It answers a lot of questions: What is the “book of business” in your company – i.e. if we never made another sale, what would the annual revenue of the company be once all currently signed deals are implemented? What is the price point of the product? (The ACV divided by the number of customers)? What are the growth-rate trends the company experiencing (rate of growth of ACV)? What can churn tell you about the company (ACV losses)? But the first two letters in ACV might be the most revealing: “Annual” and “Contract.” Those two letter make a fundamental assumption – that customers are willing to make longer-term commitments to software providers without meaningful proof of value.
That’s where the world has changed. In the 1990s, the leading software providers – Oracle and SAP – sold on-premise software. There was no notion of term for the software – you paid millions of dollars for the software and on an ongoing basis for support. The software provider realized revenue regardless of whether the customer realized any value from it and life went on. Let’s call that the age of “You pay no matter what.”
In the first decade of this millennium, the world moved to SaaS. Let’s use Salesforce as the prototypical example of that software. Salesforce will demo its software for you. It will agree to annual contracts and push you to commit to as many years of contractual obligation as possible. It only will recognize revenue when you start using the software. Enter ACV: the value of the business is a function of how many dollars you have under contract. CRM software along with HR Software (Workday) have made a living replacing on-premise software offered by Oracle and SAP. The entrenched software goliaths recognized this threat, positioned themselves as adaptable and many went on buying sprees to acquire their way to protect market position. They largely relied on the same business model as their predecessors – but they did it by hosting the software in the cloud and charging annually. Software 2.0 was a “Pay as you go, but commit” world.
That brings us to today – a world where the new, leading application companies follow the “Show Me” software business models. Go to the home page of Dropbox or Box, and you’ll prominently see a “Free Trial” offer. Tableau will give you a trial of its business intelligence software and leverage usage to grow their revenue as you exceed the number of free user licenses. Demandware follows the Gross Merchandise Value (GMV) – in effect tying Demandware’s revenue to its customers’ revenue. These business models are a reflection of the reality of customer buying behavior – customers want proof of value and real ROI for software purchases. They don’t just want business cases; they want provable ROI.
When people buy this type of software, they expect it to work, and they expect it to deliver the intended value. Building a company in the “Show Me” age requires both an exceptional product and a highly analytical go-to-market model, with a thoughtful integration between the two. Founders and executives who attempt this challenge are best placed ensuring that their teams reflect both sides of the coin. The “Show Me” age requires entirely different competencies than companies of prior generations, and many executives at startups and large tech organization alike don’t understand which keys and costs are most important to employ, especially at scale. The top examples include:
Achieving a Great Pilot or Proof-of-Concept Program (POC): Great “Show Me” applications should win POCs and Pilots. At BloomReach, we run multiple types of pilots or POCs – those that demonstrate real revenue results and and those that demonstrate user engagement. For the “Show Me” software buyers, a good pilot and POC program should have an extraordinarily high revenue opportunity, accelerate the upfront sales cycle, have clearly defined success criteria, and require the customer to make a commitment of some kind (time or money typically).
An Analytical Account Management Team: If customers are looking for “Show Me” software, that orientation will extend well past the initial sale into the long-term relationship. One of the biggest issues that many tech leaders don’t understand is that your account management team should have individuals with strong analytical skills, often from quantitative consulting backgrounds – supported by a “Data Analyst Team” that can work with customers to quantify ROI. The account management team will often track the customer’s ongoing usage of its software or the other key performance indicators (KPIs) that justify the business case, knowing that a decline may portend customer dissatisfaction. Account management isn’t just about taking people to dinner or mitigating issues; it’s about being a partner that adds business value – creating stronger internal champions – every day.
Customer Satisfaction Metrics for Everything: Many companies measure overall customer satisfaction, but miss out on pieces of the sales and customer engagement process. For example, an oft-ignored part of the customer engagement process is implementation often because it comes after a deal has been signed – but good implementations lead to good customer satisfaction, which is a key ingredient in “Show Me” software.
“Show Me” Products: Many SaaS Companies include dashboards that help a customer understand the value they receive directly in the product itself. I recently downloaded the MyFitnessPal app. In addition to showing your caloric intake and exercise, it’s constantly providing trending information – reinforcing the idea that each additional data point they record for you is essential to your future fitness program.
A “Show Me” Business Model: Everything we know about SaaS metrics is challenged by the “Show Me” paradigm. What is the idea of “contracted” value in Demandware’s GMV model? Should the CAC ratio be calculated pre-POC or post-POC? How do we measure lifetime value in a world where accounts can grow or shrink rapidly based on customer satisfaction? Designing a business model for profitable and rapid customer acquisition, while ensuring the level of revenue predictability that investors desire, requires significant innovation. Forecasting in a world of customer-deal variability can require a different financial competency.
Taking Risk: The competitive and crowded market of disruptive technology in today’s landscape forces software vendors to assume more risk – risk that previously was shared more equally by the buyer. In addition, there’s an ever-growing movement even now within the “Show Me” software age to bring the best data chops to the table first – both people and data sources. Buyers are gravitating toward companies that offer unique data that proves and advances their business case and are willing to share the risk to achieve that business case.
A lot about the “Show Me” software world is very positive because it rewards the nimble start-up over the big, entrenched software company. It creates significant business-model challenges for those larger software companies. In particular, large software companies live in a world of rigid processes with rigid financial models and the rigid requirements of Wall Street. A “Show Me” world totally permits exceptional financial performance, but does not reward rigidity. The “Show Me” world also produces better-quality software – because that’s the only type of software that customers will really buy and stay engaged with, enabling the upstart with the better product to challenge the large software company with a distribution advantage. It also intricately ties the sales process and the customer-success process together – creating a more sustainable basis for customer engagement. It favors a cross-sell, up-sell model of selling – enabling software companies that deliver to grow even faster. Of course, not everything is positive. We can take the “Show Me” orientation to an unnecessarily absurd level – turning down projects that make obvious sense because the supporting data may not be crystal clear (data analysis can be murky). The idea is that some things so obviously provide a benefit that the specific ROI is irrelevant. This may sound counter-intuitive coming from the CEO of a big data company, but when our data obsession makes us miss the forest for the trees, it reminds me of a line from my friend Robert Chatwani (former eBay Marketplaces CMO and current CMO of Teespring). “What’s the ROI of your Mom?”