Zhuoqun (Richard) Qian, Head of Growth at Teambition, talks candidly about why behavioral analytics is essential to him, his team and to the business. Here’s a snippet of what he has to say.

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What inspires you to want to explore your data?

I believe there are lands to grab through exploring data and the tools are easy enough to use to help you get started.

Being able to make a serious impact on our product evolution inspires me to explore data. For example, I discovered that by using insights from data on how users interact with our solution, I tweaked a few third party form systems and improved lead process conversion by 33 percent.

What are some of the coolest insights you’ve found while exploring your data?

We all know that the majority of users are easier to distract than most of us expect. At Teambition, we found that less informative and simpler web pages are way better at converting users.

Also, I learned that the correlation between certain actions and retention vary. I found that the action most related to retention is having coworkers use our platform and make comments. Now, we plan to retrofit the whole onboarding process based on this finding to increase retention.

What are the top two ways data is impacting the company?

Product managers evaluate their work much easier and create incentives for their teams to make great decisions. Also, people directly manage their teams’ contributions and more scientifically adjust strategies to improve efficiency in crucial parts of the business.

The second way is around collaboration. Connecting people with their work and the results boosts morale especially when they know their work leads to a 30%+ improvement in conversion through an onboarding funnel.

What drew you to behavioral analytics? What problems were you trying to solve?

We track critical performance metrics like, daily active users, retention, percentage of users who are active at least 5 days per week, and hours active out of 24. It’s not enough to just have those metrics. We need to understand what impacts those metrics, to what extent, and how. To answer those questions, extensive behavioral analytics on our data is required.

Also, we need to determine if a feature launch was successful, see how much of the new feature is used, and how that impacts the overall metrics we track.

What positive changes are you seeing by making data available to more people?

We’ve established a data-driven culture which helps us solve disputes and clear confusion. And, we’ve achieved a more efficient product iteration.

People take a more informative approach when making important decisions like, what’s the priority for apps on certain platforms, what’s the smallest size of a screen that’s worth support, and what features are a priority for our users?

What are some key takeaways that you can share with other companies that want to do that same thing that you’ve done? 

Patiently invest in your analytics infrastructure. Think about what you want to learn from your data and how you want to structure event data dimensions. Make sure the foundation to operate an analytics infrastructure is firm, it will pay dividends.

Always keep in mind, in order to make it work, implement your analytics solution to make it easy for everyone to access and use (truly self-service). It only works when there is low friction to access data.