You’re so vain. You probably think this data’s about you.

In a world of constant change, persistent growth and consistent uncertainty, data is your best friend. The right data can get to the heart of seemingly impossible problems, provide guidelines and guardrails for navigating new territory, uncover the insights to drive innovation, efficiency and creativity and ultimately, unlock a world of untapped revenue and resources. 

The increasing importance of data for organisations has also transformed, it is inherently more valuable. In fact, the value of all raw consumer data in 2019 in the US alone was quoted to be worth $106 billion. Elsewhere the story is similar (you can even get an estimate of the value of your own personal data here), and those figures are only continuing to grow in response to the challenges of the last 18 months. 

We’re certainly no strangers to the value of data at We Are Unity. It’s part of our DNA. But there are inherent risks and missed opportunities that arise when organisations focus on what we call ‘Vanity Metrics’ – the data that tells them how good they are, rather than the data that tells them how to be better. 

The Vanity Dilemma

Vanity metrics – from engagement to traffic to impressions – will make your business look and feel good on paper. But without a tangible connection to ROI or performance outcomes, they do nothing to help you understand your performance in a meaningful way that can influence future strategies. 

That’s not to say that vanity metrics have no value. Sure, they may not help you uncover the root cause of your problems, but they still have their place. The right ones can tell you if you’re moving in the right direction, help you articulate a compelling business case or provide a surface understanding of what is working and what isn’t in your business. And sometimes the positive reinforcement of a well timed ‘pat on the back’ can do wonders for motivation and morale. 

Ultimately though, these metrics can at best act as indicators towards growth or improvement, but without any actionable or controllable element to them, there is no outcome to learn from or iterate on going forward.

Vanity in action

Take the impressions or views of your organisation’s website for example. Knowing how many times a page has been viewed might feel nice, but it doesn't tell you much of substance on its own. On the other hand, measuring where each page view comes from would allow you to understand how to target and draw more people to your page.

Diversity and inclusion is another area of focus that spends too much time with vanity metrics. Sure, your raw data may help your organisation feel like they’re hiring diverse talent and ‘closing the gap’, but suppose you’re hiring refugees only in entry level roles; or hiring women in areas that already skew to hiring women. Not only are you not addressing the root cause of the issue, but your ‘performative commitments’ are unlikely to have much impact, as increasingly, “employees, recruitment candidates, and consumers are holding organisations accountable for meaningful change”. 

So how do we trade in our vanity metrics and identify the performance metrics that can embed actionable insights into our business’s decision making process? In other words, how do we understand what data is actually useful and how best to use it?

Uncovering data that ‘does something’.

When making a report or dashboard to provide your business with insights, there are a few simple steps to ensure your data is actionable and valuable. 

Step 1: Define the problem and link it to a measurable outcome that you want or need to track.

Make sure the outcomes are something you can replicate, measure and identify if there are any data gaps between the problem and the outcome.

Keep it simple and pointy. Something like: A shrinking pipeline means we need to bring in more sales opportunities. But first, we’d want to track a series of online marketing campaigns to identify which have the best ROI.

Step 2: Think like a scientist, creating a hypothesis for what data you think will measure and track your outcome. It’s important here to scrutinise the data and ensure what you are looking at is valid, objective data that will help you build your case. Check that the data you are looking at is working in service of answering your hypothesis, and define a repeatable task that will test that your metric is tracking the right things.

Using the same example; we’d track the number of new opportunities per month as we roll out each  of our different campaigns to see which has the greatest ROI. The three hypotheses being tested here are “Online marketing campaigns can increase the number of new opportunities each month”,  “The longer I run my campaign, the more effective it is” and “One social media platform brings in more opportunities than another”. 

Note: To guarantee your hypotheses stand up to scrutiny, make sure that aside from the measures you are testing (in this case different social platforms), everything else is consistent.

Step 3: Validate your theory before you then scale the solution. At this stage your data should be measuring something you can control and replicate. To validate your hypothesis, perform a task that will produce an expected change in data, and see if the proposed change occurs. If you can’t validate your theory, adapt your hypothesis or the data you are measuring to try again, adopting a test and learn mentality until you get it right.

Think of the questions you want your data to answer when it comes to reviewing your campaigns. Is one platform bringing in better results than another? Has the number of new opportunities increased from the previous month?. Now run the campaigns again with a new variable at play, perhaps this time you run them for 3 months instead of 1. Does the data suggest the same results? Or has the length of the campaign impacted its effectiveness? If not, look at another variable you can test. Maybe this time you up the frequency of posts? You can keep doing this with new variables until your hypotheses have been confirmed or disproven.

Vanity is skin deep

It’s always nice to be able to see when you’re doing a good job, and there’s nothing wrong with taking pride in your wins. But ultimately, vanity metrics will only ever make for catchy headlines. If you want to be able to turn that win into many more, you must be able to understand why you’re doing a good job. For that, vanity simply won’t cut it – you’ll have to scratch a little deeper.

If you think your data could be doing more for you, get in touch with us at hello@weareunity.com