Data-Driven Work Cultures: John Cheng of Baotris On How To Effectively Leverage Data To Take Your Company To The Next Level

An Interview With Pierre Brunelle

Democratize decision making — Data democratization enables everybody in an organization to have access to relevant data that they can work with comfortably. At my last company, we scaled from 300 employees to 3000 very quickly. This meant it was no longer possible to always know the right person to talk to for any specific question. Instead we built a centralized platform where self-service data was made accessible and visualizations were easy. We also built an analyst team for harder questions that were shared across the entire organization and contributed to company growth and strategy.

As part of our series about “How To Effectively Leverage Data To Take Your Company To The Next Level”, I had the pleasure of interviewing John Cheng.

John is the CEO of Baotris, a growth investor that equips ecommerce brands with data superpowers and provides capital to act on opportunities discovered in their data. Before founding Baotris, he helped pioneer the adoption of analytics in the mobile gaming industry, scaling a platform to over a billion players. He’s also a reformed investment banker with over 10 years practicing M&A on Wall Street.

Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

I’ve always been fascinated by applying data to problem solving. I started in investment banking building financial models to predict the combined operational performance of acquired companies. I took many of those skills with me to co-found a company called Playnomics that used machine learning to understand people through their game play. That was an incredible opportunity to combine my passions for game play and data. I consider myself incredibly fortunate to have created a career out of things I enjoy most.

Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘take aways’ you learned from that?

The transition from banking to startups was not as straightforward as I would have hoped. Overnight, I went from managing a team of highly disciplined financial analysts to a rogue band of software engineers. Needless to say, when I tried to apply the same command and control management techniques in the startup world, it quickly blew up in my face. While I eventually figured out how to connect with the team, for a while I was wondering how I was going to explain to investors that I had been deposed in a bloodless coup.

Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?

Recently I read “Man’s Search for Meaning” by Viktor Frankl. The book had been recommended to me several times but I didn’t really know what it was about. I ended up picking it up on a family vacation and found myself both shocked and humbled. The story of one man’s ability to find purpose in the midst of unspeakable atrocities spoke to a strength I hadn’t really known existed. For me, it’s now a tool that I turn to when I need to feel gratitude and inspiration.

Are you working on any new, exciting projects now? How do you think that might help people?

Baotris is our attempt at bringing the data advantages that large enterprises enjoy to smaller ecommerce brands that wouldn’t have access to them on their own. We believe that independent brands and their founders matter and by helping them leverage their own data better, they can compete on equal footing with the incumbents in the space.

The biggest barrier we see for small brands is the ability to “close the loop” when it comes to data. Without the right resources, most of the value is never unlocked. For our brands, we supply software to help collect and process data, a team of experts to analyze and develop insights, and finally the capital to put a plan in motion that is data driven.

Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” My work centers on the value of data visualization and data collaboration at all levels of an organization, so I’m particularly passionate about this topic. For the benefit of our readers, can you help explain what exactly it means to be data-driven? On a practical level, what does it look like to use data to make decisions?

In my experience, data-driven organizations are ones which have a culture of acting on data, it’s installed in their DNA. The most effective of those companies use rigorous methods to test and iterate across everything that they do. While many companies can use data to answer “what happened?”, it’s the most data driven companies that can derive actual insight from data to answer “why did this happen?” and, perhaps the holy grail “what should I do about it?”

Which companies can most benefit from tools that empower data collaboration?

While all companies can benefit from data collaboration tools, it’s most critical to those that are deliberately trying to build a data driven culture. On a practical basis, this means implementing tools that make data and analytics a part of the daily work for everyone in the organization, this must be done hand in hand with instilling a system to influence employee mindsets and incentives to encourage behaviors that leverage data. It’s not enough to just act, it’s always imperative to know why you are acting.

We’d love to hear about your experiences using data to drive decisions. In your experience, how has data analytics and data collaboration helped improve operations, processes, and customer experiences? We’d love to hear some stories if possible.

I’ve often seen data become the most impactful right when startups start to scale. While founder intuition was critical for the initial stage of finding product market fit, the complexity of decisions continues to grow and inevitably gut based decisions start to break down, especially when trying to expand into new markets.

For example, we invested in an electric bike company with a great set of founders who had a great design aesthetic that enabled their product to stand out. As their brand started to take-off, however, they found themselves trying to compete with much larger brands for the same customers — millennials and commuters. Upon analyzing the data of their website traffic and conversion funnel, it became clear that their customer was actually much older and more interested in safety and stability. With this insight, they were able to reposition the entire company and brand to carve a sustainable niche that wouldn’t have otherwise been apparent.

Has the shift towards becoming more data-driven been challenging for some teams or organizations from your vantage point? What are the challenges? How can organizations solve these challenges?

In my experience access to data, and tools to work with that data, are often the biggest hurdles for widespread data driven decision making in organizations. The rank and file want to make better decisions but the systems often have not been built out that enable that sort of collaboration. A good way to start is by building out a data analyst team that works with different departments. Initially, they help with queries but their ultimate mission is to educate teams and to build better tools that the teams can use themselves. While this takes time, an incremental process has worked well because it delivers value at each step and encourages teams to want to do more themselves. It’s a go slow to go fast situation.

Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Effectively Leverage Data to Take It To The Next Level”? Please share a story or an example for each.

Data has been a lifelong passion of my career. Across banking, mobile gaming, and ecommerce, the most impactful uses of data have been to:

1. Democratize decision making — Data democratization enables everybody in an organization to have access to relevant data that they can work with comfortably. At my last company, we scaled from 300 employees to 3000 very quickly. This meant it was no longer possible to always know the right person to talk to for any specific question. Instead we built a centralized platform where self-service data was made accessible and visualizations were easy. We also built an analyst team for harder questions that were shared across the entire organization and contributed to company growth and strategy.
2. Personalize customer interactions — Ongoing customer data collection is crucial to ensuring customers and prospects feel valued and heard. Today’s customers are no longer willing to accept a one size fits all approach to their needs and spend accordingly. Mobile gaming marketing was at the forefront of this by giving every player a custom onboarding journey based on their specific traits, as well as custom advertising within the game. This has led to outsized increases in engagement and spending and no doubt will be the norm in commerce as well.
3. Data driven product development — Iteration in product development is critical as most products that get launched are not perfect from day one. As an example, when building our gaming platform, the user insights found in our usage tracking were used to inform everything from what types of content resonate, to leading causes of subscription cancellation. We literally watched thousands of users using the software to create higher-performing content thanks to data analytics.
4. Improve internal data story-telling — Visualizing customer data in a way that executives understand is a powerful way to gain approval of budget, especially if you are able to make the data relatable. Include stories to bring your data to life. Humanizing the data with real customer examples is a powerful way to lead business decisions.
5. Connect better with your customers — Data helps us understand what works and what doesn’t by providing measurable insights on key business outcomes. Analytic capabilities can not only help you sharpen your message and better reach your audience but can help you prove the value and impact of communications with stakeholders. The right analytical tools, structures and processes can help any employee illustrate their ROI.

The name of this series is “Data-Driven Work Cultures”. Changing a culture is hard. What would you suggest is needed to change a work culture to become more Data Driven?

At the most basic level, changing the work culture has to come from the top. Leaders have to demonstrate that evidence based decision making is the new norm. This may mean visibly stepping back from decisions that were previously made by leadership opinion, in favor of data supported options. Incentives should be put in place for recognizing decisions made by data.

The future of work has recently become very fluid. Based on your experience, how do you think the needs for data will evolve and change over the next five years?

I believe that the next five years will be about data access and enablement. If data is the new oil, over the last several years we’ve found more and more sources of data through better instrumentation and capture. However, crude data by itself is not enough. Bad data is everywhere. It needs to be cleaned, refined, and converted into a form that every day users can not only access, but utilize. More jobs will rely on data analytics as a key decision making tool. This means that not only must data be available, more people will have to be taught how to use it to extract the most value. With analyses being decentralized, new insights and opportunities will be identified that haven’t been contemplated before. Further, with the changes we have already seen in data-privacy laws (Apple’s IDFA, Facebook Ads targeting, and soon to come Google), first-party data will be more important than ever as it will be the only accessible data most companies will have access to until a pay-for-play data model is introduced.

Does your organization have any exciting goals for the near future? What challenges will you need to tackle to reach them? How do you think data analytics can best help you to achieve these goals?

We’re focused on helping small businesses use data smarter to acquire customers who are the best fit and run their businesses more profitability. Our platform brings together data from across the different systems that are required to run an ecommerce business. By having marketing, operations, supply chain, and fulfillment data all in one place, we enable founders to get a 360 degree view of what’s happening. The next step for analytics will be using data to prescribe actions that may not be apparent. Automatically allocating marketing spend to the most profitable channel, predicting lifetime values of prospects to focus sales efforts, forecasting the effect of discounts on revenue and profits are all within reach with the right systems in place.

How can our readers further follow your work?

I’m active on our blog at Baotris.com and would love to hear from readers at @jbaotris on Twitter.

Thank you so much for sharing these important insights. We wish you continued success and good health!

About The Interviewer: Pierre Brunelle is co-CEO and Chief Product Officer (CPO) of Noteable, the collaborative notebook platform that enables teams to use and visualize data, together. Prior to Noteable, Brunelle led Amazon’s internal and SageMaker notebook initiatives. Pierre holds an MS in Building Engineering and an MRes in Decision Sciences and Risk Management.