We make things. You, reading this, make things; directly or indirectly. We work to make and support things. We do what we do for a reason, for a purpose. We want to be successful. Success can mean and look like many different things. So, how do you figure out what success is and what leads to it? It takes curiosity, patience, and 3 questions.

What does success look like?

Success happens when goals are realized. It’s an amazing feeling when time spent working amounts to real measurable results. The catch is that we can’t arrive to that feeling of deep satisfaction if we don’t ask the question – What is success?

No matter the industry you work in, it’s crucial to have your finger on the pulse of what makes the things you’re involved in producing successful. This applies to things big and small; from features and buttons to entire sites and applications. By answering this question, you and the entire team get clarity on what you’re trying to achieve (and why) for everything you do. Once you know what success is, the next question naturally arises:

What measures will you use to define that success?

For the purposes of business and working in teams, success should be measurable. If it isn’t measurable, redefine what you see as success. At this stage, you need to connect what you see as success (growing a user base, retaining users, increasing engagement, etc.) with numbers. Don’t worry about tools yet, those come later. For now, just make sure that success can conceptually be tied to numbers. For example, you may want to increase the user base, so the measure used to define that success would be amount of signups or monthly revenue. Simple. Now this gets fun:

What are the leading indicators of that success?

Once we know what success looks like and what measures we will use to define it… well, now we’re ready to think about how we arrive to those measures. Because, you see, things like sign ups and monthly revenue are lagging indicators. Things like home page bounce rate, click through to sign up, sign up form drop-off, etc. are leading indicators. Leading indicators make the news, lagging indicators report the news.

What you pick as leading indicators always start as hypotheses, as educated guesses. We’re not touching actual data yet, so get informed about all the magical trackable touchpoints available and use your instincts to make educated guesses about what you think will lead to those measures of success you defined.

As soon as you have a good idea of what success looks like and what may lead to it, you will then be ready to manifest your vision and think about tools. I’ll write about picking the right tools in a later post.

1. What does success look like?
2. What measures will you use to define that success?
3. What are the leading indicators of that success?

Without knowing what you’re trying to measure and why – any tools you select will only serve to complicate an already significant undertaking. For now, focus on these first 3 questions – answer them well and you’ll know what to do next. Choosing tools is the fun part, and much easier, when you know what you want the tools to do.

Finally, it should be said that this isn’t easy. Asking difficult questions about success can make anyone slightly nervous, but at the end of the day everything we do is done for a purpose – knowing this purpose and understanding what success is for all you do will help you make truly epic shit.

@marcopetkovski

When we ask, “Why does this exist?” we’re really asking, “What are we trying to do and how are we going to prove it worked?”. This question should be asked over and over again, because we inevitably get very involved in the craft and often lose sight of the purpose.

Qualitative and quantitative are best friends who love this question

The qualitative discovers what Jobs to be Done the solution must accomplish from existing and potential customers as well as the refinement of conceptual goals into a guiding creative purpose.

The quantitative takes this purpose and defines exactly how the goal will be represented, measured, and optimized with real actions taken by users.

When you set out to measure these defined goals, it should be SMART:

1. Specific
2. Measurable
3. Attainable
4. Realistic
5. Time-limited

This way, you learn a whole lot of things that you simply wouldn’t know otherwise; what’s working, what isn’t, how you can improve, where you can take your ideas, what you should be testing, and especially if what you’ve created is actually making an impact on your objectives.

You want to “fail small” in a test and find out something will not work so you don’t “fail big” when there is a lot of money on the line.

This is the mantra of optimization. Before we were collecting every bit of information from digital experiences, we only had our gut to rely on. In this new age of data, analytics, and strategic measurement we now have real objective insight into what works and what doesn’t.

The most challenging thing that any of us will encounter when trying to optimize is fear.

Fear that we’ll discover that our work isn’t as good as we think it is, fear that the very thing we have hung our skilled hats on is really an illusion.

Gathering data, measuring it, and optimizing means accepting that it’s OK to fail.

There are 2 possibilities when we measure our performance:

1. We will discover that what we assumed to work actually works

2. We will discover that what we assumed to work doesn’t actually work

These are equally powerful outcomes as each of them shows us an objective reality that we can synthesize into a thoughtful response; either to repeat success or optimize away from ineffectiveness.

Defaulting to what we find to be the comfortable alternative and avoiding objective insight seems comfortable, but only because of the ignorance that it affords. It takes courage and commitment to make inspiring work, to want to make it better, to know it’s OK to fail.

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