Everything Post-Sale

As subscription pricing models overtake perpetual licensing and maintenance, business success is determined not only by acquiring new customers through Marketing & Sales (M&S), but equally through retaining and expanding existing customers. To this end, Customer Success — as a conglomeration of all post-sales activities — is integral to the success of a SaaS business by delivering operating efficiency.

The Central Themes of CS

At a conceptual level in a SaaS model, the central themes are to acquire customers, followed by delivering customer retention and encouraging customer expansion. As we are aware, the typical cost to acquire customers is typically multiples of the cost to retain them (about 8X). While M&S spending has become operationalized, it is still difficult for businesses to understand how to fund customer retention programs effectively, to manage for growth. While we can all agree that conceptually it is imperative to have a post-sale Customer Success function, what is the impact of Customer Success in terms of ROI? If a business invests $1 on Customer Success, what should it expect in return based on customer revenue or profit? In this post, we explore post-sale metrics that combine to deliver a unified metric, helping answer these questions.

How Do We Measure CS?

When we review Marketing & Sales (M&S) efforts, a central guiding metric is Customer Acquisition Cost (CAC). If the CAC is high, SaaS businesses struggle to recover M&S investments and attain a path to profitability. If we pose a similar question to Customer Success, to identify a similar unifying metric that clearly encapsulates all post-sale activities, with a view towards establishing a return on investment thesis, there are a few nuances to consider. In a post-sale operation, there are multiple phases of a customer’s journey from a vendor’s perspective— on-boarding, adoption, expansion, renewal — that are impacted by differing vendor functions — services, training, customer success, sales, respectively. Across these post-sale activities there is related collection of metrics that corresponds to particular phases — Time to Live (TTL) for on-boarding, Adoption %, Customer Satisfaction (CSAT), NPS scores, Churn %, and so on. Some of the specific metrics are listed in the table below.

While there doesn’t appear to be an obvious unifying metric that aggregates across all the customer lifecycle phases and touchpoints, a powerful proxy that we can employ to measure ongoing customer revenue contribution is customer lifetime value, whose impact can be measured and narrated at an MRR level. The greater the customer lifetime length (in months), the greater their value and profitability contribution through their lifetime.

By definition, Customer Lifetime Value is calculated as annual revenue per customer (adjusted for gross margin) related to the churn rate.

Customer Lifetime Value (CLTV) = {(Average MRR) X (Gross Margin%)} / ($ Churn Rate)

In this equation, “Churn Rate” is the combined outcome of all customer interactions and touchpoints – i.e. on-boarding, customer support, product fit, services delivery, relationship management. Similarly, “Average Revenue per Account” is the combined outcome of customer revenue growth through cross-sells and up-sells. Customer Lifetime Value thereby is a function of both a customer experience metric as well as a post-sale expansion metric.

A dollar invested in Customer Success will thereby impact either the churn rate or the average revenue per customer, depending on the functional area the investment is in – retention or expansion. Tracking these metrics and narrating them to CLTV delivers a clear calculator of value creation. In order to increase CLTV, investments have to be made either in MRR expansion (account management) or MRR protection (customer success, support, services, training). As the ratio of CLTV to CAC improves, a SaaS business transcends towards profitability. (Note: In the desirable event that a SaaS company achieves negative churn (i.e. $ expansion > $ churned), the CLTV calculation ceases to be representative as the calc tends towards infinity.)

With regards to ROI, as investments are made in post-sale functions, ROI can be calculated based on the approach:

Return on Investment (ROI) = (Net Program Benefits / Program Costs) x 100

In terms of Customer Success data:

Return on Investment (ROI) = ((Net Revenue Retention) / (Cost to Serve)) * 100,

where Net Revenue Retention = $ARR (or $MRR) at start of period – $Churn + $Expansion; and, Cost to Serve = Aggregated cost of the post-sale operation.

Below, you will find a complete chart of the relevant metrics and KPIs that should be tracked by your CS team, and your CS platform, if they are relevant to your business use case.

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