The Pitfalls of Vanity Metrics

In today's digital age, marketing professionals are armed with a variety of data metrics that offer valuable insights into their campaign performance and strategies. These metrics play a vital role in measuring success, but not all are created equal.

Enter vanity metrics – (or what we like to call outcome metrics), data points that may appear impressive at first glance but fail to provide meaningful insights or drive actionable decisions.

In this blog, we'll dive into the world of outcome metrics, their allure, and the potential pitfalls they present for marketers.

Data Overload and Temptation of Vanity Metrics

By harnessing predictive analytics techniques used in data science, machine learning and AI, businesses can easily move from reactive to proactive decision-making. Through the analysis of historical data, patterns and trends can be identified, enabling accurate predictions of future outcomes. This empowers businesses to make informed decisions ahead of time, such as predicting customer churn or forecasting sales and stock requirements.

Control the Controllables

There is common theme that comes with vanity metrics: they are often uncontrollable and lagging indicators, measuring only the output or outcomes of a series of actions instead of what moved the dial to get there.

It is far more valuable to focus on what the retail giant Amazon likes to call ‘Input Metrics’, these are the controllable metrics that lead to the outcomes and goals. You can look at them as the actions or steps you need to take as a marketing team to really show outstanding performance. Input metrics should be tracked regularly as they will end up looking after your topline vanity metrics if you get them right. It’s a win-win situation!

Sound confusing? Let’s look at an example.

Let’s say you are an e-commerce business, and your marketing goal is to increase the amount of organic revenue generated via your website, this goal becomes your ultimate outcome (vanity metric) and is dependent on a chain of events.

You start with looking at traffic to your website, which in turn is dependent on how your website ranks versus competitors, which is reliant on the content and technical elements that search engines value.

This is where your elusive Input Metrics lurk, the elements or actions your team can take to really shift the needle.

Going back to our Organic Revenue example, you need to look for input metrics that will help improve your search engine result page ranking. Some good input metrics examples could be:

• # of pages published in the last X days
• % of pages updated in the last X days
• % of pages with slow speed

Identifying these ‘inputs’ is key because they shape our efforts, influence decision-making, and align the entire team towards what matters most.

Defining Your Input Metrics - Using the Flywheel Method

Identifying the right metrics to gauge marketing success may seem straightforward, but it's often more complex than you first think, as they are not a one size fits all. In our experience, it often involves trial and error to pinpoint the ones that matter to your organisation.

A great place to start defining what you want to measure is by using a concept from Jim Collin's legendary book, "Good to Great" – the Flywheel.

This innovative idea replaces the traditional linear marketing funnel with a circular, self-reinforcing system. The Flywheel centers around a set of controllable input metrics that drive a single key output metric.

Amazon’s Flywheel, for instance, focuses on attracting customers, engaging, and delighting them, and fostering advocacy. By prioritising customer satisfaction and loyalty, their Flywheel leverages the power of positive word-of-mouth and referrals, attracting new customers and creating a self-perpetuating cycle of growth. They then align their metrics with elements of their unique Flywheel.

Amazon didn’t find their input metrics at their first attempt, they went through a process of defining them, measuring, analysing, and improving them to ensure they were driving the right behaviours and not the wrong ones.

Conclusion

We are not saying that you shouldn’t measure your outcomes(vanity metrics), but to be mindful that sometimes they can just be a distraction and meaningless unless you get ahead of them and measure the inputs it takes to achieve them.  

By embracing a well-defined approach to input metrics and continuously refining your strategies, you will be empowered to make informed decisions, optimise your efforts, and deliver exceptional customer experiences that drive bottom-line growth. Remember, it's not always a straightforward path to find the right input metrics, but the journey is worth it to achieve sustained success and meaningful business outcomes.

If you are interested to know more, we recommend reading Working Backwards by Colin Bryar and Bill Carr on the Amazon way of doing things.

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