Analytics. I used to think they were just nice-to-have stats for big tech companies. Turned out I was wrong.
When I launched my first e-commerce site about 15 years ago, I focused on building a perfect user experience. Tracking analytics wasn’t even on my radar. Within days, my site traffic flatlined. Panicking, I poured more money into ads only for clicks to fizzle out on our home page.
Why has no one bought my products? I had no idea. The work that took months was useless, and there wasn’t a single clue on what to do.
Sometime later, when I was working as a freelancer, I built a slick mobile app for a client, but analytics were neglected again. On launch day, everyone mentally popped champagne as downloads poured in. But visible engagement on the app tanked hard over the next few weeks. The app may as well have been invisible. Ghost town.
Then came my biggest facepalm yet. Much later, when working as a dev team, we built an automated chatbot to execute different commands in Slack. All was well initially, and users reported that they enjoyed the bot. But when we started doing user research months later, it turned out nobody was using the bot anymore. How did it happen that we couldn’t catch the moment when the usage declined?
I finally learned the lesson. Now, analytics are the foundation of everything we build as a team. We obsessively track each page’s click rates and know which ones engage visitors most. We monitor usage and user behavior when building apps and remind the users to aim to send push notifications each time engagement drops. As for neglected bots, we now monitor and improve bots daily based on the conversations people have.
Sure, analytics aren’t sexy. But flying blind is a thousand times worse. Data is the compass that guides your product to success. We’ve come to depend on our analytics as a pilot relies on their instrument panel. As Peter Drucker said, “If you can’t measure it, you can’t manage it.” Can’t agree more with this statement.
Analytics Your Product Needs
Analytics aren’t optional — they’re the difference between a smooth flight and a tailspin. Here are some key analytics every product needs from the very first launch.
Website Analytics
Your website is the first opportunity to connect with prospective clients and test whether your offer will resonate. Creating a simple landing page and driving traffic to it through ads provides priceless early feedback before you sink too many resources into developing a product or service. But you can’t just throw up a website and hope for the best — you must closely monitor how visitors interact with it, at which stages of the funnel they drop off, and how well they convert into actual clients.
Sign up for tools like Google Analytics and Hotjar to start getting insights into your visitors. See where they come from, how much they engage with your content, and which cohorts better convert to signups or sales.
You might notice things like high bounce rates, which may either signal poor engagement or that ads do not match the website. Use Hotjar’s heatmaps to literally see where people click and scroll and fix issues like signup buttons hidden below the fold. The key is continually testing and optimizing based on data and insights to figure out what images, headlines, or calls-to-action resonate with your audience. You can increase conversions overnight with simple tweaks informed by analytics.
App Analytics
Launching your app is just the first step — next comes the critical work of monitoring usage and battling issues before they impact retention.
You’ll want visibility on key metrics like daily and monthly active users to see whether engagement remains sticky or starts dropping off over time. Short session lengths may signal problems with the user experience. High churn indicates how many users uninstall and stop using your app monthly.
This is where analytics tools like Mixpanel and Amplitude come in handy to spot usage patterns. But don’t rely on analytics alone — be proactive about monitoring app store reviews and social media conversations to get qualitative data on how real humans react to your app. Complaints or concerns can improve your roadmapping a ton.
For technical performance, a tool like Airbrake allows you to catch crashes and errors before users even notice them. Closely monitor web page and app load times to guarantee a prompt server response. The key is combining analytics with human feedback to spotlight opportunities to optimize. For example, you may discover engagement peaks at certain times of day when you could better prompt users with notifications.
Data Analytics
Congratulations, your product is live and loaded with behavioral data on your users. But data alone provides little value — someone has to actively analyze it for insights that drive optimization. Dig into the numbers through SQL queries, reporting, and visualizations. Where are users most and least engaged? When do they use your product? What drives conversions?
A platform like PostHog is an easy way to start unraveling the stories in your data. Spot usage patterns around the most and least used features. See if certain times of day or user locations correlate to more activity. Find the factors that convince passive users to convert to buyers. The goal is to turn observations into action.
For example, an edtech company my friend worked at noticed their platform usage plummeted from 7 p.m. to 9 p.m. They strategically sent push notifications during these “prime time” hours and saw a bump in engagement. The story was in the data all along — you just need to look for it.
Analytics are essential for any product. In the beginning, use free tools to make data-driven choices, even if you don’t have a big budget.
Focus on critical numbers that show how users engage with your product, keep using it, and how it performs. Use these insights to understand how people use your product.
Make improvements based on what you learn. Try A/B testing different versions, fixing tech problems, and adding new features.
The more you track and test, the better you can meet user needs. Analytics turns guesses into smart decisions backed by data.
Treat analytics as an ongoing process, not a one-time thing. With the right data, your product vision will succeed.
Originally published on Medium.com
