Creating Moments of Impact for SaaS Growth

Mark had previously focused on sales, including SDRs, account executives, and sales engineers. For his next role, he required ownership of the full customer journey. He wanted to design an experience that increased customer value and revenue, instead of controlling one part of that journey.

His wider remit included post-sales functions where he had less traditional software experience. He saw value in that perspective because he viewed many existing systems as broken. Post-sales often mixed support, training, and firefighting instead of proactive value creation. At Catalyst Software, he focused on fulfilling sales promises and developing post-sales as a deliberate revenue function.

Mark views acquisition and post-sales as two sides of the same revenue discussion. Acquisition teams generate revenue through prospecting and deal management. Post-sales teams ask how growth continues after a customer signs. When buying becomes harder, he advises leaders to examine their customer base instead of treating the funnel as the default answer.

He sees an imbalance in executive attention: acquisition receives substantial effort, while post-sales remains less developed. Initial contracts can lead to renewals and growth across several years. His orange-squeezing analogy illustrates leaders pressing an acquisition system with little yield while leaving greater post-sales opportunities untouched.

Mark contrasts SaaS with perpetual licences. Under the older model, buyers make large upfront commitments, own software indefinitely, and face high switching costs. The burden of extracting value therefore rests largely with them. SaaS lowers initial costs and makes switching easier, while providers gain recurring revenue that becomes more profitable over time.

That benefit requires providers to deliver recurring impact if they want recurring revenue. Mark says many businesses adopted SaaS pricing without establishing a rhythm of continuing customer impact. They still equate growth with signing more customers, reflecting perpetual-licence habits. A SaaS operating model instead makes post-sales value creation central to retention and expansion.

Onboarding often produces a concentrated rise in perceived value. Teams configure the product, add users, and provide training. They then relax after implementation, expecting customers to find value independently. Mark says this causes value to plateau. Without further progress, customers have little reason to expand, and the product becomes an ordinary part of their work.

By renewal, perceived value can decline, prompting customers to ask what the provider has done recently. Early work carries less weight over time. Mark cites variable-ratio reinforcement: smaller, intermittent rewards can cumulatively feel more valuable than one predictable event. Post-sales should create frequent value increments instead of relying on onboarding or occasional business reviews.

The process begins with the outcome behind the purchase, such as reducing churn, increasing expansion, launching a product, or changing pricing. That initiative must map to a job the software performs; otherwise, the team should reject the opportunity. The job then maps to relevant features and functionality. A moment of impact occurs when the customer uses that solution to advance the desired outcome.

For proactive risk management, dashboards, playbooks, and automation can form the solution. Someone starts the week, sees three newly risky accounts, and finds meetings scheduled through an automated playbook. Mark recommends starting with the solution tied to the leading initiative. Teams should guide customers toward specific experiences and confirm that customers recognise the resulting value.

Mark defines a value sprint as bounded work designed to produce a specific moment of impact. The team configures the solution and playbook, monitors the intended experience, and reports results to the business owner. It then asks the customer to acknowledge the value. Without that recognition, creating value leaves the commercial work incomplete.

After each sprint, the team asks what matters next. The same initiative can remain the priority, or an external event can shift attention elsewhere. This creates recurring steps of impact without overwhelming users with the full product. Mark compares software to an elephant that customers need in digestible bites. Excessive onboarding can widen the gap between value delivered and value absorbed.

Mark challenges the assumption that effective post-sales work requires senior people. He says that perception reflects unclear, poorly designed processes. His team holds weekly meetings where each CSM and manager reviews every account, starting with the largest. They focus on the next step for creating value, not only on problems.

For each account, the CSM identifies the initiative, deployed solution, current impact, next meeting, intended outcome, and subsequent request. This sequence teaches consistent thinking, produces focused weekly actions, and reinforces strong execution. Mark says early-career employees can learn this progression, as SDRs learn structured processes. The alternative depends on individual heroics and playbooks that teams use inconsistently.

Mark says post-sales teams have lacked tools and visibility connecting actions with outcomes. Measuring an at-risk account playbook only against churn creates problems. Churn is a lagging metric influenced by multiple variables. A playbook can work as intended without immediately changing the overall churn rate. Direct attribution can therefore lead teams to false conclusions.

Instead, teams should connect each playbook to a relevant leading indicator. If logins decline, they can target improvement and measure how quickly the playbook changes that behaviour. Monitoring should continue after the playbook ends to test durability. Without this discipline, organisations replace strategies each quarter, employees ignore temporary initiatives, and individuals adopt separate methods. Standard execution and relevant leading data support shared learning.