“If you can’t measure it, you can’t manage it.”

Peter Drucker

Generally misattributed to Peter Drucker, this idea forms the foundation of the data-driven culture that almost every company lays claim to these days. The only problem is, not all data are equal, and simply being data-driven isn’t enough.

It’s been virtually four years since Eric Ries spoke negatively on vanity metrics, nevertheless they are still actively used by several companies. But what’s the big deal about it? Running your company based on bad metrics could get you into more trouble than not having any metrics at all.

Let us suppose that you and your team are building a new mobile app and are committed to focusing solely on actionable metrics. That pretty much makes you decide between CAC, ARPU, MRR, LTV and other similar fun acronyms. So which metrics should really make a groundwork for your KPIs? Using the idea of the one metric that matters (OMTM), delineated nicely by the authors of Lean Analytics, the solution depends on your business model and what stage your company is in at the moment. In other words, as your business evolves over time, the metrics that are tied to the success of your business do so too.

Early-stage startups in search of a less complicated metrics framework would benefit from (re)reading Marc Andreessen’s blog post on product/market (P/M) fit. Spoiler alert: it’s the sole factor that matters. As such, attempting to measure the lifetime value (LTV) or concentrating too much on client acquisition cost (CAC) at this stage is maybe not the best use of your time. Instead, you should focus on P/M fit: do you really have a product or service that customers really wish to use, whether it be an iOS app or Web application?

How does one confirm whether or not you’ve achieved P/M fit? In his post, Andreessen states, “…you will perpetually feel product/market work once it’s happening.” Creating a lot of objective assessment will be non-trivial. Also there is a good survey approach by Sean Ellis who devised to assess whether or not customers realise the real value in a product or service. You can think about P/M fit in the context of engagement: are your customers using your product on a daily, ongoing basis? Measuring engagement is thus another way to evaluate your P/M fit (using a metric that’s most relevant to you business).

Let’s transcend P/M work and a few other metrics that will be key to your business (again, all depends on your model and stage) and the way they’re calculated:

- Churn rate (r)

Some choose to focus on retention rate, which is calculated as 1 – r

- Conversion rate (CR)

- Customer acquisition price (CAC), or subscriber acquisition price (SAC)

- Average revenue per user (ARPU)

- SaaS businesses tend to focus instead on monthly recurring revenue (MRR)

- Lifetime price (LTV), typically spoken as time lifetime customer value (LCV)

- Average client time period (ACL)

Churn Rate

Churn is most relevant to subscription businesses and whereas calculating it looks trivial, the fact may be a bit more complicated. Considering that Churn is a rate it is taken into account over a certain amount of time, typically monthly or annually. One of the easiest way to represent churn rate is:

However, this formula doesn’t yield comparable results for periods of various length (monthly vs. quarterly vs. annually). Though slightly a lot of complicated, the subsequent formula produces current, timely, and comparable churn rates (in this case, for a amount of thirty days).

Conversion Rate

Any call to action includes a funnel of behaviour that the user is pass through so as to complete the CTA. Conversion rate allows you to quantify the effectiveness of your funnel and is solely calculated by dividing the quantity of users converted into sales or leads by the quantity of users you've had at the top of the funnel e.g., number of landing page guests.

Customer Acquisition Cost

In order to calculate CAC, divide your sales and promotion expenses by the quantity of users that were not acquired. Sounds straightforward, however there are some nuances to contemplate on.

First, to urge a real sense of the complete CAC your numerator ought to include variable as well as fixed costs, salaries and overhead expenses, for instance. Second, if your business model includes a free trial, bear in mind that an acquired user is equivalent to a paying user i.e., you've got to consider dropoff from free trial users who don’t convert to paying users. As your company get so much enough on where you'd be able to confidently calculate LTV (described below), you’ll wish to contemplate on the quantitative relation of CAC to LTV, that ought to be within the 25% 35% range.

Average Revenue Per User

ARPU may be a comparatively straight-forward metric that's calculated by dividing total revenue in a period of by the quantity of buying customers throughout that point. SaaS or subscription-based businesses tend to like watching monthly recurring revenue (MRR), which needs separating revenue generated by recurring customers from that generated by new customers, and is a complement of types to churn.

Lifetime Value

LTV may be a semi-controversial metric that has distinguished critics and proponents. Be aware that early-stage start-ups e.g., those having but twelve months of customer data, are going to be challenged to calculate an accurate LTV. As Bill Gurley points out, it’s a tool, not a method. LTV will function as a gauge for how effectively you’re acquiring and monetizing users, however it’s not the end metric to grow your business by. The LTV formula is written as:

Where Costs represents the annual costs needed to support a client throughout the given time period, SAC is corresponding to CAC, and WACC, weighted average cost of capital, factors the time value for money over the course of the users lifetime period i.e., a dollar attained today is worth more than one attained a week from now.

Start-ups are most likely best off employing a simpler version of this formula where LTV = ARPU – CAC. Arguably less rigorous, this formula can simplify LTV-based decision making process and additionally reflects the fact that start-ups usually don’t/can’t access capital markets to deploy capital.

Average Customer Lifetime

In order to work out LTV, one should understand a user’s (or a cohort’s) average time period. ACL is most for instance, a 5% monthly churn rate corresponds to a twenty months Average Customer Lifetime.

A Final Note

Defining your business’ key metrics is non-trivial, as is that the challenge of calculating them properly. No 2 populations of users are identical, and understanding true client behaviour needs segmentation and cohort analyses so as to avoid the pitfalls of using averages.

The article is based on "Startup Metrics: Don’t Let Your SAC Get WACC" article by Andrei Marinescu

by Dmytro Bilkun