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?

Istarted my journey with data working in direct mail. Everything was measurable, testable, and results-driven. Decision making was easier and logical. Where we saw results, we added content, and where we saw engagement decline, we reduced. Working with data made sense to me; it provided a scoreboard for success, and having grown up playing sports, that appealed to me. As paid media and email became more prominent, we applied the same principles we were using on the direct mail side of the business to digital. My career matured along with the media, and I became more of a generalist who was always rooted in data. When I came to Collective Measures, I was provided the opportunity to focus solely on data and measurement strategy, which is where my true passion is.

It has been said that sometimes our mistakes can be our greatest teachers. Can you share a story about a humorous mistake you made when you were first starting and the lesson you learned from that?

I would like to say I have not made any mistakes along the way, but that would be a lie. I have made plenty of mistakes! One mistake I caught through measurement was an errantly placed quick response or QR. Long ago when free wifi, or wifi at all, was not as prevalent as it is today on flights, we were asked to measure the success of a marketing QR code that was placed in the back of the plane seats. Not a single QR code had been triggered! This taught me a lesson about having difficult conversations, since the marketer running this campaign was not anticipating these results. This also taught me the importance of measurement strategy and the tactics aligning with the desired outcomes. This is why I strongly believe in taking the time upfront to map out how objectives align with outcomes so you understand technically how you plan to measure, as well as measuring the ideal action for a given tactic.

Leadership often entails making difficult decisions or hard choices between two apparently good paths. Can you share a story with us about a hard decision or choice you had to make as a leader?

Decision making in a technical field can often be difficult because of the pace at which things move and the natural tendency for disruption in the market. Being given the opportunity to develop an intelligence engine at Collective Measures was certainly one of those times I felt the pressure to choose the right path. While there were many routes we could have taken, we did market research and collected as much data as possible to help inform our decisions along the way. Ultimately, our findings allowed us to focus on a core set of capabilities that were naturally flexible so that we could move with the market should technology change or a disruptor enter the market. This flexibility afforded us the opportunity to not have to be concrete and to edit our roadmap as the agency progressed.

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

As of late, we have been working on a number of SEO (search engine optimization) projects. We are taking a fresh look at the page and keyword data provided by webmaster tools platforms and transforming them into meaningful segments. This allows our teams to consistently measure the performance of page groupings, editorial themes, or technical optimizations in a way they had not been able to in the past. This segmentation helps our teams provide deeper insights for optimization and allows them to move faster to capitalize on changes within the search engine results page.

You are a successful business leader. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?

Observant: I see my team as the glue that brings other teams together through measurement. By being observant and understanding what other teams are doing, how they work, and what is key to client success, I can make recommendations for solutions, process improvements, or start to get ahead of issues before they become larger than they need to be.

Rational: Being rational has allowed me to not be married to my own ideas and open up to others who may have better outcomes for our clients or our product. Creating the space for the best idea to bubble up sparks new ideas and a collaborative work environment. It also keeps the decision-making criteria transparent; by stating the measurement outcome we are looking to achieve, others can rally around that outcome as they provide solutions.

Sincere: Being sincere has always allowed me to be straightforward with my team, make tough decisions easier by doing the right thing (even though it might not be the easy thing), and provide my team with as much information and context as possible. Sincerity makes having difficult discussions just a little bit easier as people know where you are coming from and where your intentions lay.

Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” Based on your experience. which companies can most benefit from tools that empower data collaboration?

Big and small. Creating a common language with data is critical; it creates the context needed for others to understand the recommendations or decisions you are making. By creating a collaborative environment with data, the gap in understanding begins to shrink, and dialogue opens up between cross-functional teams. Generally, teams are siloed and often look at different things for different reasons. Bringing the data together is the first step in having cross-functional team discussions about how you look at and interpret the data. In some cases, other siloed datasets hold the context of what is happening in another team’s data. A collaborative data environment eliminates miscommunication among teams, which is crucial to understanding insights at the deepest level.

Can you share some examples of how data analytics and data collaboration can help to improve operations, processes, and customer experiences? We’d love to hear some stories if possible.

Personalized content can provide an increased customer experience. Through SEO analysis, our teams work to develop content that aligns with the customer journey. We are working to address known questions in a logical order and make them easier to find. My team has been working cross-functionally with our SEO partners to look at on-site experiences against content needs within the customer journey. Through this collaboration, we can provide insights into what content is impactful — and better yet — when it is appropriate to put it in front of the consumer.

In terms of operations, we have been working with a manufacturing client to provide media mix modeling (MMM) insights. We have not only involved the marketing teams, but have also been working closely with their operations and finance teams. This collaboration has provided us deep insight into economic and manufacturing factors, allowing us to provide a more accurate view of how marketing is impacting their business. The collaboration is helping their operations because they are getting insight into how media plays alongside the business factors they deal with day in and day out. This collaboration will enable us to provide a more measurable media plan because of the various cross-channel inputs we are including in our modeling.

From your vantage point, has the shift toward becoming more data-driven been challenging for some teams or organizations? What are the challenges? How can organizations solve these challenges?

We do not see technical challenges as the limiting factor in shifting to a data-driven organization. Today, data are being centralized and democratized; however, teams that were not data-driven to begin with are now in the midst of making this culture shift. This is where teams are falling down most since this is a true culture change, requiring not technical solutions but management changes across the organization. Building the muscle to include data in the decision-making process can help businesses change their culture, but they also need leadership support in making what can seem like bold choices when using data.

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.

1. Understand your customer: Data can be used to teach and inform others within your organization about your customer. We all have ideas about how a customer acts, but there’s not just one type of customer. Developing customer cohorts using data based on user behavior can be supplemental to early audience research or personas developed from external research. We see this all the time when looking at data about the paths to purchase, for example. There are thousands of permutations users take before making a purchase, most of which don’t make logical sense or conform to how we think a consumer makes a purchase. Through this detailed review of data, you may even find things that are blocking customers from making a purchase or engaging with you in the future.
2. Scale: Tools like AI and other automated tools are making our lives easier. Thinking about these as that — a tool that can allow us to work more efficiently and not something that will replace our jobs — is a must. These tools can allow you to work on larger initiatives with smaller teams and reduce the amount of time spent on mundane tasks. Most data platforms today have built-in capabilities that can assist with routine tasks, monitoring, or automation. Spend time understanding and building these out so you can focus your efforts on higher-value projects that can impact your clients or customers.
3. Data-informed optimizations: Today, most platforms are set up to leverage first-party data to inform media optimizations. These types of tactics allow marketers to target users who look like their customers, reduce costs by excluding customers, or deliver highly relevant content to your customers. If you have not integrated data into your media execution, you are missing out on more efficiently running media campaigns.
4. Knock down silos: Data can be used to knock down silos that exist today within organizations. Most organizations have more data than they know what to do with. They need people to effectively create the connections between the datasets to bring them to life. Whether it is two marketing teams running similar campaigns and sharing benchmarks, or operations teams sharing efficiency metrics for improved performance, data have the potential to inform all aspects of the work we do.
5. Invest: Data were once called the new oil. Like oil, data need to be refined before they can be used effectively. Making an investment in engineering has changed how we work, opening up possibilities for Collective Measures in ways we could not imagine. Do not assume your work with data is done once it has been captured — you need to continue to invest in it to make it valuable for your organization.

Based on your experience, how do you think the needs for data might evolve and change over the next five years?

We are seeing it now: Those with exclusive access to datasets are winning as the development of unique datasets will be a competitive advantage. This will become more prevalent over the next five years. Large data providers are already closing their doors and making business decisions to not integrate with open doors. Secondly, you are seeing large players creating retail-like spaces specific to industries like finance and healthcare. On a micro level, those who have not invested in their data infrastructure will continue to struggle to make gains against their competitors as the advantages become more significant.

Thank you for your great insights, We are nearly done. You are a person of significant influence. If you could inspire a movement that would bring the most amount of good to the most amount of people, what would that be?

Start small. Be nice to your neighbor and be active in your community. If everyone took this approach, we could provide a lot of people with a lot of “good!”

How can our readers further follow your work?

Connect with me on LinkedIn and check out Collective Measures!

This was very inspiring. Thank you so much for the time you spent on this. We wish you only continued success.