Growth Arithmetic: The Fundamentals of Traction
Now that software is “eating the world” and transforming every industry, the number of new SaaS, ecommerce, marketplace, mobile and consumer software apps hitting the market are increasing exponentially. Due to lower barriers to entry and increased competition, the drivers for investment are shifting from qualitative to quantitative as investors look for ways to leverage data to identify potential winners early. The question early-stage investors ask has changed from “can you build it successfully,” to “can you acquire customers and grow it.” Consequently, for early-stage startups looking to raise capital, the conversation starts and ends with traction. Given the dynamics of this new data-driven funding environment, VentureFund.io has created the platform for measuring and sharing traction in real-time between startups and investors. In doing so, it is important to be clear about the growth fundamentals on which traction is measured.
What is Traction?
Traction is quantitative evidence of customer demand and is the earliest indicator that you’ve achieved product market fit — which is arguably the most difficult phase of startup building. Early traction not only proves that you’ve achieved product market fit, it proves that your team can execute — which substantially reduces risk for investors. So traction has become the quantitative indicator that investors use to assess your startup’s potential. Startups that are successful at gaining traction, have no problem raising capital.
Measuring Traction
Measuring traction is not new but until recently, investors and founders have had no consistent framework available to measure growth and align their understanding. However, Jonathan Hsu at Social Capital recently introduced a way to apply “growth accounting principles” to a broader range of activity metrics. By making this framework publicly accessible via the 8 ball, Hsu made a large contribution towards generalizing a framework for measuring traction.
In this post entitled “Growth Arithmetic: The Fundamentals of Traction,” we use a simplified set of measurements that can be understood visually to lay the groundwork for understanding traction for both B2B and consumer-based software startups. For founders that have built at least an MVP, traction can be calculated simply by connecting their startups’ data to VentureFund.io. From there, it can be shared individually with potential early investors in real-time as a direct way to introduce your startup.
Customer Traction
To understand the fundamentals of traction, we begin by considering a fictional SaaS company which is experiencing a consistent increase in total monthly recurring revenue (MRR) from one month to the next. We assume that this company only allows the same fixed payment amount so that measuring their total amount of MRR is equivalent to tracking their total number of paying customers. The area of the larger circle in the diagram below shows the total customers that paid in the most recent month “t” labelled with the value X(t) while the the area of the smaller circle signifies the total customers paying last month, X(t-1).
In this case X(t) > X(t-1) , which means that the number of paying customers increased from month t-1 to month t. We quantify this increase by the ratio of the two quantities X(t)/X(t-1). By subtracting 1 from this ratio we define a paying customer growth rate, G(t), as
which is positive when X(t) > X(t-1) and negative when X(t) < X(t-1). This quantity represents the fractional increase in the paying customer base from one month to the next.
Knowing that our growth rate, G(t), is positive indicates that the paying customer base has grown. However it does not answer questions about the rate at which this company is also losing old customers, a.k.a. their churn rate, or the rate at which it is acquiring new ones, acquisition rate. To understand these numbers consider the following diagram that shows the overlap of customers who paid in both months t and t-1.
The intersection of these two groups of customers is referred to as the retained customers, R(t).
The churn rate for month t is defined as C(t)/X(t-1) where C(t) is the number of paying customers who churned (did not return to pay for month t in darker blue). Similarly the acquisition rate for a month t is defined as N(t)/X(t-1) where N(t) is the count of new and resurrected customers paid in month t but did not pay in month t-1 (in lighter blue). Keep in mind that in order to measure, C(t) as well as N(t) and R(t) we need to wait for the month t to end to ensure we accounted for all potential customer types. For the remainder of this discussion, we will use this diagram to discuss growth arithmetic.
Consider the previous diagram with the retained customers, R(t), removed so we can focus on the other two pieces, C(t) and N(t):
Comparing these two parts directly by the ratio N(t) / C(t) has been recognized for some time now as the Quick Ratio, QR(t), which quantifies the relative amount of customers gained to lost. This quantity is important because the overall growth rate G(t) may result from very different underlying acquisition and churn mechanics. A high QR means that N(t) >> C(t), and the relatively low churn rate should encourage a larger investment in marketing optimization. On the other hand, if the company has a QR closer to 1 so that N(t) ~ C(t) , the increase in paying customers can only be explained by generating a large amount of new customers strongly diluted by churn. Such a scenario would warrant a more conservative investment strategy.
Activity and Engagement
In this section we will review how the growth framework we have used to measure traction in a SaaS business can be applied to deferred revenue business models as well. Consider another fictional startup that is a consumer software product whose goal is to acquire and engage users far in advance of monetizing (think Instagram, WhatsApp). In our previous model engagement was measured by payment retention. In the case of deferred revenue, the customer’s payment activity is replaced with a core customer action representative of engagement. As referenced by others, core actions include pinning on Pinterest, tweeting on Twitter and uploading a video on Youtube. After identifying the “core action” to measure growth, we use our framework to determine the users that are active over two time periods such as months t and t-1. From these sets, we can measure the growth rate G(t). But we can also determine the overlap of retained users and by default churned users, new users and the Quick Ratio. We recognize the convenience of these growth metrics to be used internally by startups as their KPIs.
For a deferred revenue product, these core actions directly associated with delivering value are the most important data to capture and measure. The diagram shown below shows how growth metrics can also be applied to core customer actions.
At VentureFund.io we seek to capture both forms of engagement based on your business model so that growth can be transparent within your team and to potential investors you choose to share your data with. If you are a SaaS startup connect your revenue data (Stripe, Braintree). If you are a deferred revenue startup connect your core activity data (Mixpanel).
Quality of Revenue / Depth of Engagement
Our final step in Growth Arithmetic considers what would happen when our SaaS fictional company allows their price to be variable and each customer can pay a unique amount per month. In this case, in addition to straight churn and acquisition, paying customers can also pay more or less than they did last month. Therefore, with variable revenue the Quick Ratio is written it as
where N(t) is the dollars coming from new and resurrected customers, E(t) is the additional dollars coming from customers who are paying more (expanded), D(t) is the contracted dollars leaving as a result of customers paying less (decreased) and C(t) is the dollars lost from customers who stopped paying. These customer segmentations are represented in the following diagram:
where returning users are broken into those that expanded, contracted and stayed the same. Measuring revenue growth provides more detailed information than simply measuring paying customer’s growth as a company’s pricing options become more complex. It is important to note the difference between paying customer growth and revenue growth can be significant and lead to very different quick ratios and associated metrics. Previously we used the paying customer framework to apply to active / engaged customers identified by performing a “core event”. We make the same analogy to activity by identifying the retained active users whose engagement contracted (decreased) and expanded (increased).
Conclusion
We are entering a new era in funding driven by data and rooted in quantifying traction as the earliest indicator of product market fit. In this post we’ve articulated a framework for measuring traction that can be applied not only to revenue-based business models primarily used by B2B startups, but also engagement-based business models to assess the potential of consumer startups that may ultimately derive revenue from advertisements. For both business models, this framework is applicable to measuring the rate of growth of the customer base and their depth of engagement. For a visual representation of this framework see our infographic.
Grow. Don’t pitch. Let your data do the pitching. Sign up for VentureFund.io to measure your traction and share it with a universe of potential early investors while you focus on growing your startup.
