When you're building products, efficiency and speed are paramount. Who has time for meticulous planning and data analysis when there's so much code to ship?

Experimentation tools might promise optimization and insights, but let's be honest—they're just obstacles on the path to rapid deployment. Here are five compelling reasons to avoid them altogether.

1. Experimentation takes too much time

Implementing experiments requires meticulous planning, setting up hypotheses, controlling variables, and analyzing results. All this effort detracts from the primary goal of deploying features as quickly as possible. Who needs to spend time validating ideas when you can just push code to production?

Remember that time we rolled out a new UI without any testing, and it caused a 30% drop in user engagement? Sure, it took weeks to recover, but we learned so much from the chaos! Besides, moving fast and breaking things is the hallmark of innovation.

What you should do instead:

Ship fast and don't worry about measurement too much. If users encounter issues, they'll let you know—eventually. After all, customer support teams need something to do. Plus, emergency patches make the job exciting!

2. It's too hard to choose metrics

Selecting the right metrics to track success is a complex task. It involves deep understanding of user behavior, business goals, and statistical significance. That's just extra work piled onto your already overflowing to-do list.

Why bother figuring out whether to measure click-through rates, conversion rates, or user retention? Just pick a number—any number. "Number of smiles per day" is a good KPI - it sounds cheerful, and it's entirely unmeasurable.

What you should do instead:

Just make up some metrics after the fact. Any number can be persuasive with the right spin! If the data doesn't support your narrative, just create a new narrative. Pro tip: graphs with upward trends look impressive in presentations.

3. Setting up an experimentation tool is a pain

Integrating an experimentation tool into your tech stack can be cumbersome. It might require significant code changes, data pipeline adjustments, and learning new systems. Why disrupt your smooth development workflow for the sake of controlled testing?

What you should do instead:

It's much easier to just fix your app after it breaks or deal with bad decisions in quarterly reviews. Think of it as on-the-job training for your development team. Downtime builds character and strengthens team bonds during those late-night emergency fixes. Besides, who doesn't love a good firefighting session at 2 AM?

4. Experimentation tools are too expensive

These tools can be a significant investment, consuming resources that could be used elsewhere. Licensing fees, infrastructure costs, and the time spent learning to use them all add up.

What you should do instead:

Just spend all your money on Datadog. With enough logs and dashboards, who needs controlled experiments? Monitor everything in real-time and react on the fly. Overhead costs are a myth when you're chasing performance metrics 24/7. Plus, colorful dashboards make for great office decor.

5. Your ideas might not always be right

Experimentation might reveal that a beloved feature isn't performing well. Facing such truths can be demoralizing. It's better to trust your instincts and avoid the disappointment of data contradicting your genius ideas.

If the data shows that a new pet feature is driving users away, you have to believe! Keep it, lose some users, and stand by your vision! Innovation requires courage, even (especially) in the face of overwhelming evidence.

What you should do instead:

Just ignore the data and keep on shipping. Confidence is more important than evidence! After all, if Steve Jobs didn't rely on focus groups, why should you rely on data? Visionaries don't need validation—they create it.

To summarize

Why bother with experimentation tools when you can take the quicker, easier path? After all, what could possibly go wrong? Embrace the thrill of uncertainty, trust your gut, and keep pushing code. Who needs data-driven insights when you have unwavering confidence?

In the end, success is a journey, not a destination. And if that journey involves a few missteps, well, that's just part of the adventure. So go forth and ship recklessly—the future waits for no one!

But if you do want to experiment...

If you disagree, and you think you could benefit from using your data to its fullest, give Statsig a try. (It's free!)

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