Magic Numbers: The Context of Data with Carla Faustino and Adam Jensen

Carla Faustino is a decision scientist at The Marketing Store, where she is responsible for tasks including analytical assessments, ad hoc deep dives, and BI reporting to support business decision making. Prior to joining The Marketing Store, she spent five years with GLG working with the firm's financial services clients. Carla earned her MSc at the London School of Economics and Political Science and her BA at American University. Outside of the office, she enjoys traveling, volunteering with the Junior League of Chicago, and taking advantage of Chicago’s food and beverage scene.

Adam Jensen is coming up on a decade of data analysis experience, the last few coming as a senior decision scientist for The Marketing Store. He previously worked at MRM//McCann and graduated with a B.B.A. in Marketing & Economics from Grand Valley State University, where he nearly grabbed a B.A. in Creative Writing as well (his preferred excuse is that he couldn’t afford a 5th year – he was also too lazy). While he deals with data at nearly every stage, he prefers to work at the tail end of the journey; that is, data aggregation, and its written and visual interpretation. Adam also enjoys cooking, photography, reading, and watching TV, acknowledging that the final hobby is by far his most frequent.

LBB> What’s the number one question that clients are coming to you with when it comes to how they can better use data to enhance the creativity of their content and experiences?

Carla> How can we use the data that we have to drive more customised, personalised experiences?

LBB> How can you make sure that data is elevating creative rather than forming a wind tunnel effect and knocking all the interesting or unique edges off that make something distinctive? 

Adam> Everything involving data depends on context; 'interesting' and 'unique' creative decisions perform a certain way for a reason, and for every intended impact there are usually one or two unintended ones that come along with it. The goal of an analyst should be to provide context for those impacts; trying to answer why something performed the way it did and how the data can be used to support future decision-making, as opposed to simply stating that something did or didn’t ‘work.’ Analytics shouldn’t be about knocking the edges off or standardising something distinctive, it should be about identifying which edges are worth pushing and which direction to push in. 

LBB> Can you share with us any examples of projects you’ve worked on where the data really helped boost the creative output in a really exciting way?

Adam> One of our main projects focuses on a loyalty app with a weekly cadence. As one might expect, the data shows that getting repeat/weekly use from users early in their lifecycle is a strong driver of overall app performance and brand loyalty, and also that users respond well to personalisation. There are a number of creative decisions that have been made with that focus in mind, including an upcoming refresh of the app that will include a personalised streak counter and gamification badges. By eliminating the noise and identifying the trends, we allowed the creative team to focus on making habitual usage a main focus of the latest creative refresh.

LBB> More brands are working to create their own first party data practice - how can a brand figure out whether that’s something that is relevant or important for their business?

Adam> It seems obvious to state, but data is only as usable as it is reliable. The world’s best analysis based on incorrect data is useless and coming to ‘data-informed’ decisions that are not, in fact, data-informed, can have negative impacts far beyond the short-term. Therefore, brands should consider timeline and scalability. Standing up a working, accurate data practice takes time, and as a company grows the data that company will need to process will grow exponentially. Inaccurate data and a cumbersome internal structure will offset much of the benefit of starting a first-party data practice.

LBB> We talk about data driving creativity, but what are your thoughts about approaching the use of data in a creative way?

Carla> It comes down to figuring out what information best answers our clients’ questions. Sometimes that’s a pretty straightforward task. Other times, it involves a fair bit of trial and error. My team is very collaborative and it’s not uncommon for us to discuss various ways we can approach the data to tackle the questions that come our way.

LBB> "Lies, damned lies, and statistics" - how can brands and creative make sure that they’re really seeing what they think they’re seeing (or want to see) in the data, or that they’re not misusing data?

Carla> I like to dig a few layers into a client’s question (or questions) before getting started. Something as simple as ‘how much did X impact Y’ might contain several layers of assumptions and context; parsing that out helps me really understand what’s driving the inquiry and think creatively about how to structure my work.

LBB> What are your thoughts about trust in data - to what extent is uncertainty and a lack of trust in data (or data sources) an issue and what are your thoughts on that?

Carla> Being upfront about what the data capture – or doesn’t capture – helps build trust with your stakeholders. It also surfaces opportunities to think about different ways to quantify and measure something.

LBB> With so many different regulatory systems in different markets regarding data and privacy around the world - as well as different cultural views about privacy - what’s the key to creating a joined up data strategy at a global level that’s also adaptable to local nuances?

Adam> Data privacy regulations vary not only at a cultural level, but often within a sole market from one client to another; complete standardisation of data privacy at a global level is likely a pipe dream at the moment. To that end, it is important that a company’s core goals and practices regarding data privacy are enacted at a global level, but it is also important that local resources be given the support and flexibility necessary to comply with the different regulatory systems that they encounter.

LBB> What does a responsible data practice look like?

Carla> Documentation, documentation, documentation! We are huge proponents of documenting everything – data dictionaries, past client deliverables, SQL queries used for regular reporting, etc. In addition to serving as a repository for your team’s past work and the inputs that go into it, it’s a great way to knowledge share across a team (or teams) and helps new joiners get up to speed.

LBB> In your view, what’s the biggest misconception people have around the use of data in marketing?

Adam: Although the world has made great strides over the last few years, many people still regard data-driven decisions as boring or mundane; that by involving ‘numbers’, you rob a campaign of its creativity. To many, data represents a box in which creativity goes to die because to involve data is to immediately stifle creativity, or at least set a boundary upon it. In reality, the goal of data analysis should always be to boost and support creative performance, not suppress it. Data isn’t a box or a boundary, it’s a ladder!

LBB> In terms of live issues in the field, what are the debates or developments that we should be paying attention to right now?

Carla> A lot of professionals are thinking about striking the right balance between consumer demands for privacy and customisation. We’re seeing consumers increasingly opt-out of tracking both in apps and online, while also leaning into content and experiences more tailored to their interests. This is an area where an analytics practice can really deliver value – doing more with less data and providing a POV on the most impactful information that we can ask of consumers.