Data-Driven Work Cultures: David Tiberia of Analytics Bluewater On How To Effectively Leverage Data To Take Your Company To The Next Level

An Interview With Pierre Brunelle

Pierre Brunelle, CEO at Noteable
Authority Magazine
Published in
14 min readJun 19, 2022


Whether we like it or not, work in the current environment doesn’t typically allow for a lot of time to methodically think though problems. The example above isn’t isolated as many analytics teams can take weeks to provide data and analysis. Expectations of speed dictate that the time an employee can spend working on or researching a specific problem is usually limited. If you’re going to encourage team members to use data to make decisions and drive progress, then you’ve got to figure out ways to make data rapidly accessible. Otherwise, some of the most important questions your teams come up with will never get answered.

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 David Tiberia, Partner and VP of Analytics at Bluewater, a direct marketing and advertising agency based in Clearwater, Florida. With almost 15 years in direct-to-consumer advertising, David has diverse hands-on leadership experience in most major disciplines of multi-channel D2C advertising. A true, modern advertising “renaissance man,” he’s embraced a career of constant evolution and growth. He currently leads a team of talented data scientists and analytics pros at Bluewater to develop advanced solutions that give brands deep insight into consumer response. He’s always ready to discuss attribution and advanced measurement techniques or how data can lead to better decisions. He and his team developed a leading-edge visualization platform and continue to find new opportunities for innovation. Every client benefits from his knowledge, looking beyond the raw numbers to provide insight and direction that leads to brand scale.

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 started in the media world at a very young age. I saved to buy a pro camera in high school, built a non-linear rig and was working jobs for local businesses. I started a computer consulting firm in college to continue to invest in additional gear and had my work on national TV before the age of 20. I worked at a Fortune 100 company out of college, but my entrepreneurial drive led me to join a small agency and learn the craft of creative for direct-to-consumer advertising. From there, I turned into a bit of an advertising “renaissance man” spending time directing creative, managing operations, TV media, digital media, media strategy and most importantly: data and analytics. This has been my focus for a while no. It’s been an amazing journey working with data when most brands saw it as a novelty, compared to now, where brands ACTUALLY want to talk about data.

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?

Early in my creative career, one of the trends at the beginning of movies was to change the studio logo to be themed around the upcoming movie. When working on a TV commercial, I took the same idea and had our designer tweak the client’s logo to match the color scheme of the spot and place it on the ad. Somehow a rough cut of the spot made it to the client that way and I got a sharp rebuke from their team about changing their brands logo. After the review, my boss poked his head in my office and said plainly: “Never (bleep) with a client’s logo.” It’s a lesson I’ll never forget.

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?

Being an advertising guy, when I read ‘Ogilvy on Advertising’ I was really impacted on how he was using data to impact creative decisions in the 60s and 70s. They were adding codes to print or mail ads and measuring response to those ads. They were then using that data to make changes and the recoding the impact. Personally, I have a weird mix of both a creative and analytical thinking process. The things he talked about in that book really tickled both side of my brain. It’s this beautiful mix of creative and data science before data science was even a thing. It really showed me how you can even impact creative decisions with data. I don’t think I would have willingly embraced the data side of our business so easily had I not read this book. Plus, unrelated to data, David Ogilvy was a genius copywriter. There are such great examples of the power of persuasion enshrined on the pages of that book.

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

We have been working on an amazing data visualization and analysis toolset called the IQSuite. For me, “people” are brands and other companies that want to lean into data to drive their business forward. The tools we’re developing are going to help brands understand how their advertising is impacting their business and how to invest more wisely. Most companies really struggle to look at all of their marketing activity and sales activity in one place on a regular basis. Historically most companies looked at this after the end of a campaign or quarter. Compiling all the information into one place was both complicated and time consuming. While some of this may seem like it would be easy to do with modern tools, consider that we’ve integrated with over 30 different platforms to accomplish this. Each one has its own API and data granularity available. Some platforms don’t even have an API. Each platform refers to metrics in different ways. Just combining all of it accurately is a lot for an individual company to take on. Our tools have been met with really positive feedback from the clients that are using them. Even very large companies are saying: “this is something that would be really helpful for us to use.” I think this is going to lead to companies being able to free their people up to do more meaningful work. It will lead to more question asking and actual analysis instead of wasting time doing tedious repetitive data tasks that add limited value. Plus, we’ve created some unique ways to look at marketing data and joined both automation and attribution tools that will give us the flexibility to meet any size company’s needs. These attribution tools don’t require the use of “personally identifiable information” or PII. This is going to be critical as the need for consumer privacy is going to be increased in the future.

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?

Personally, I believe that being successful a creating a “data driven” environment is threefold:

  • Providing data to team members in a way they can access it at any time
  • Building and innate sense of curiosity in team members to ask meaningful question and then finding the answer using data.
  • Trusting the outcome of your analysis even if it’s counterintuitive to the way you think

Being curious is something that I can’t emphasize enough. Can you get your team to “want to know the answer” to something that doesn’t make sense? Or to desire to know what’s actually driving a particular outcome with your customers or internal team members? Curiosity is what drives that and is what I’ve always seen in companies that have successfully become more data driven. I want people to ask questions. Sometimes they’re bad questions and that also has to be OK. No one can be afraid to challenge the status quo if there’s a legitimate reason to do so. You can have all the data in the world, but if no one wants to ask any questions then it won’t do you any good. Being data driven means your people have to be curious to know answers.

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

Every company can benefit from data tools that empower collaboration. It sounds cheesy to say that, but trends can be found in almost any industry at any level. What company doesn’t have things about their business that if they knew more, they could do more? The trick is identifying the data that you need to come to the answers you want. If I had to pick some specific company traits, and I may be a bit biased here, I think consumer facing companies can benefit the most. Especially those that engage in significant advertising. Additionally, any business that has a vested interest in creating repeatable experiences for customers or better control repeated processes should find really low hanging fruit if they aren’t already using data broadly.

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.

Data has been a central tenet of our company for a long time. The fact that we weren’t being provided data from our partners drove us to grow our business into more areas. That growth into other services gave us access to data that we used to create better client outcomes which grew our business. When you create success for others, other companies want to be a part of it. One of our customers early on went all in on data with us. They agreed to send us retail scans (sales) and web traffic weekly. We connected data flows and provided visualizations to them on an ongoing basis. At the time, this was a more novel idea for a direct-to-consumer brand with a retail sales component. The data that we looked at gave us all confidence that the dollars being invested were providing real impacts on consumer behavior which led to more significant investments in the future. These investments helped them literally build a category that didn’t exist before. They’ve grown more than 10x and are in a position to go public in the future.

Another example is a consumer product that we were lucky enough to do the initial ad testing for. Everyone was under the impression that the product was going to resonate with a female audience. The first test ads on TV drove terrible response. I mean bad — sales were awful and the client was concerned that there may not be much demand at all for their product. After a detailed analysis of their consumer response, we found something interesting: it looked like more men than women were responding. Based on this analysis, we convinced the client to invest in further testing with media that focused on a male demographic. The response levels were 5x immediately and sales followed closely behind. Because of this one adjustment, their product is now in over fifteen thousand retail doors and revenue has grown exponentially.

Both of these examples led to success for our company due to increased revenue from brands that wouldn’t have invested in advertising otherwise. But most importantly, it’s had a lasting impact on the growth of their companies and the people that are a part of their teams. There are so many more examples I could share. I shared these because I love that they are so simple. I think that when a lot of teams embark on this data journey, they think they need sophisticated tools, big data and complex models. You don’t. What you need is the desire to know more and look. It’s choosing NOT to look that can lead to big misses. Simple insights can lead to huge wins.

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?

There are always challenges making a transition and this is especially true when becoming more data driven. We work with a lot of data or analytics teams at other companies since we are an agency, and our clients are other companies. One of the number one challenges I see is a lack of data accuracy. Data flows are becoming more complex and increasingly requiring the blending of multiple data sources. This is especially true with marketing and customer purchase data. Naturally as a company becomes more data driven, they start working with more data which can lead to data accuracy problems. When we onboard new clients, we take a deep dive into their data flows and ask a lot of questions to understand what’s happening behind the scenes. Multiple times a year we uncover significant accuracy issues, even at larger companies, which are impacting the quality of their decisions. Companies that are trying to become more data driven need to devote resources to make sure that the data they are looking at is correct. Most of the time the initial answer I get when we point out something that looks suspect is “that’s just the way it is.” Then upon further review, there are actually issues and they’ve been looking at bad data for a long time. In house data teams have to be relentless about accuracy. At first, members of our team were annoyed about my laser focus on accuracy but our experiences at other companies have proven that it’s not unfounded. The foundation of becoming more data driven is the data itself. If the data isn’t right and the foundation is shaky, everything will eventually come crumbling down.

Another major challenge is trusting what the data tells you. There will come a time when data is going to suggest something that is VERY counterintuitive to your organization or your own way of thinking. The desire is going to be to “go with your gut” and ignore the data. Or someone internally is going to loudly disagree that testing the outcomes of the analysis is a bad idea or ‘dangerous.’ This type of thinking or response will create a chilling effect on your efforts to become data driven. If you’re going to commit to be data driven, you have to respect the findings and be willing to take some risks on things that may not make sense up front. You can be smart and try things without risking the business, but not acting on the findings at all won’t make your team want to find innovative ideas because ultimately they won’t be tested or used.

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.

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?

One of the biggest challenges to creating a data driven culture is removing barriers of access to the data. In my experience, many people will ask meaningful questions that can be answered with data. But if it’s too difficult to get an answer in a reasonable amount of effort or time, they will not bother or have time to look for the answer. Unlocking access to data in a rapid and digestible format will allow those same people to find the answers now.

I was visiting a client a few years back and we were sitting in their board room with all the executives talking about future marketing strategy. As everyone was talking, we started asking questions about the timing and impact of certain holidays on their sales. Part of our onboarding process was to model both their direct sales and retail sales flows. Right there in the board room, we were able to re-blend the data to answer the question and uncover some pretty significant trends. As we were answering questions realtime in the meeting, the president exclaimed that it would have taken them “at best weeks to get the same answers from their in house team.“ By exploiting the trends uncovered during our meeting, the company, which was mature and had been in market for over 20 years, was able to grow sales that year by over 100%. We’ve all been there. You’re in a meeting, someone has a great question or idea that would influence the decision you’re making but getting to the answer is going to take time. Either you don’t have time to wait because you have to decide now, or no one actually gets around to getting the answer. Maybe you got busy. Maybe there weren’t enough resources available at the time due to other projects. So, the answer is never found and someone eventually ‘goes with their gut.’

Whether we like it or not, work in the current environment doesn’t typically allow for a lot of time to methodically think though problems. The example above isn’t isolated as many analytics teams can take weeks to provide data and analysis. Expectations of speed dictate that the time an employee can spend working on or researching a specific problem is usually limited. If you’re going to encourage team members to use data to make decisions and drive progress, then you’ve got to figure out ways to make data rapidly accessible. Otherwise, some of the most important questions your teams come up with will never get answered.

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?

One of the things that I tell people all the time is: “In the future, there will be more data, not less.” Seems like a simple idea but the ramifications are huge. Today, everything is being measured in some way. This is going to lead to a major problem for many organizations. That problem is deciding what data is VALUABLE to look at. When we were developing our visualization platform, we asked repeatedly what mattered and what didn’t. What could we take out of this page so that the insights were clear? What do we need to add in here that would help someone make the right choice? This constant questioning helped us build a product that is focused and exceptionally good at answering specific questions clearly. As data continues to massively increase, the temptation will be to “use it all.” Following this temptation will lead to teams that spend a lot of time looking at information that is essentially noise and will provide no additional important insights.

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?

As much access as our team has to data, I don’t think it’s enough. We’re in the process of looking at even more ways for everyone to be able to ask and answer their own questions. I believe that this is going to come through the increased usage of data visualization. Our analytics team has been good at working with all team members companywide to create data solutions on an as needed basis which has led to a lot of success for my company and for clients. But I really want everyone companywide to be able to do some ad hoc analysis on demand anytime. It’s a goal that we can achieve as we are focused on preparing strong, well-documented data sets that anyone can access and work with in a standardized visual tool. This is going to require us to be really detailed and continue to dive headfirst into data automation, so data is always ready and available. In order to really make this happen, users are going to have to have great experiences the first time. If it’s complicated or frustrating, then team members won’t want to come back. I’m certain that the next level of client success lies in the brains of our team and their desire to drive better client outcomes. Giving them the tools to do so will be one of the ways we are successful in the future.

How can our readers further follow your work?

You can reach me on LinkedIn →

Or via email:

Check out our company’s latest developments →

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



Pierre Brunelle, CEO at Noteable
Authority Magazine

Pierre Brunelle is the CEO at Noteable, a collaborative notebook platform that enables teams to use and visualize data, together.