Metrics are instruments to evaluate the performance or progress of business activities. Searching for purposeful metrics within your business is a necessary pursuit. Necessary, because gaining sense out of a huge dataset is impossible without first defining the metrics that matter. We help our clients do this by executing a Data Sprint in which we assess all possible analyses. Here, we walk you through the Data Sprint step by step.
Your job as a data analyst is to take the raw data and interpret the numbers as efficiently as possible. However, before doing so there must be a clear understanding of the objectives, in order to make sense of the data. Think of it like this: it’s much easier and more efficient to do your weekly grocery shop when you have made a shopping list beforehand. Unfortunately, determining metrics in data modelling is a more thoughtful and complex process than simply shopping for groceries. So allow me to elaborate on what metrics primarily entail.
How to define your metrics
It’s important to note that metrics reveal themselves in certain contexts. Whether it’s to acquire or activate customers, increase their retention time on your platform, grow revenues or encourage customers to promote your product; determining the function of your metric remains an indispensable task. Metrics are relevant if they are connected to an important business KPI.
Conditions of suitable metrics
One way to do this is by evaluating the metrics according to the following conditions.
Firstly, the metric should be simple. Meaning that a metric should either be displayable as a single number, or at least be legible. It should therefore be a metric that is comprehensible to a broader audience.
Secondly, the metric should be measurable instantaneously. By definition, it should be possible to produce the metric at any given time. For instance, a conversion metric ‘from trial to paid subscriptions’ does not meet this condition: It´s a lagging metric, i.e. time needs to pass by before it can be interpreted. An alternative would be to look at the number of features utilised, or time spent by a user within its trial period.
Thirdly, the metric should be actionable; it must offer the opportunity to take operational or strategic actions. If you would not act upon a metric when it is extremely low or high, the metric is presumably non-actionable.
Fourthly, making it comparable ensures you can make up the balance over time. This allows you to set measurable goals instead of playing by ear.
Fifth and finally, the metric should be fundamental. More specifically, it must drive your revenue (in)directly to ensure your efforts are effective. If a metric meets all of the above conditions, it’s likely to be a suitable metric for analysing your business.
A method for selecting your metric: building a funnel
A constructive way of defining the most important metric for your digital product is by building a funnel of your platform. This step not only leads to your metrics, it also provides insight into the customer journey. This is why we highly recommend this data-driven method when defining your metric. Depending on the success of your business, you can focus on a metric that lays increasingly deeper in the funnel.
Examples of Metrics
Let’s take a look at one specific business case to make it more visual : A new streaming platform (like Netflix). The retention element within a streaming platform has the function of persuading customers to use their product frequently and to watch their content for as long as possible. This can be expressed in metrics such as engagement, most recent activity, total activity over a period of time and churns. Together, these metrics unveil the stickiness and success of the streaming platform.
Let’s dive deeper into one metric: engagement of users. We can measure engagement by looking at the daily, weekly or monthly active users of the product.
This metric is relatively simple and it measures the number of active users for a given period of time. Moreover, it can be measured immediately for any given moment. The only shortcoming here is that when evaluating data for longer periods of time, it may become a lagging component.
It is actionable because your organisation can determine which customers have (not) been active. It is comparable against competitors’ numbers and can be evaluated over time.
Lastly, it is fundamentally important; the goal may be to make customers loyal to the platform in order to increase revenue.
Presenting of the Tesla Bot, August 2021
Final note
There are many benefits of defining metrics, including reaching the objectives of your business and promoting a clearer focus within your organisation. Furthermore, it facilitates data-driven experimentation with an eye to improving the products accordingly.
In conclusion, defining metrics for your business is crucial for achieving your goals. ONBRDNG executes Data Sprints to define and operationalise the metrics that are crucial for your business.
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