Magic Numbers: Finding Unique Opportunities to Use Data with Tim Schatz

Tim has more than 10 years of analytics experience in several industry verticals. Tim’s expertise spans data management, data visualisation, dashboard design, measurement planning, and uncovering insights and recommendations to optimise multimillion-dollar marketing campaigns across all channels. He also has an MBA in finance and is able to make complex analyses easy for all stakeholders to understand. Tim’s expertise has levelled-up H/L’s analytics capabilities, furthering their ability to Make Momentum for their clients. Visit here to find out more about how H/L can Make Momentum for your brand. 

LBB> What does a responsible data practice look like?

Tim> I think transparency is the foundation to a responsible data practice. For an ad agency specifically, a responsible data practice looks at the data objectively and provides observations and insights with the analysis. 

Transparency is something we are very proud of at H/L, and we make our data fully transparent to our clients. A lot of agencies will build a report once a month and cover up the bad performing data points and only highlight the good ones. I think it’s more responsible to own up and highlight the issues, concerns and problems so that we can address and correct them. Sure, we pat ourselves on the back when we see really solid performance but we also notice when there are issues and we don’t hide the problematic points that say things are not perfect, because things are never perfect. 

One of our agency brand values is “be frank, be friendly”, and we take this value seriously in our dashboard & analytics practice. We believe in being honest with data, and being candid about the results, whether they are good or if there are opportunities for improvement.

To facilitate transparency, we give our clients access to dashboards with un-filtered, raw data, so they can dig in and look for issues, wins, losses, opportunities. This allows them to work with tens of millions of rows of data in a single working session with a very fast and easy-to-use interface that lets them do their own analysis, in addition to the analysis we provide, if they choose to do so.

LBB> 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?

Tim> First and foremost, I don’t think you should go into any analysis wanting to see anything. Rather than having a preconceived notion, we prefer to find something new or novel that we didn’t expect. If we are only finding the things that we want or expect to see, then we are not really learning anything, we are just reinforcing what we already know or assume. It is actually more exciting and powerful to find something that you didn’t expect—or perhaps something you did not want to see—because that can help guide you forward.

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?

Tim> Trust in data is absolutely a challenge that we deal with on a regular basis. Most data are incomplete, either through sampling or limitations on data collection. Regardless, we can rarely put full trust in our data sets, and we must take insights derived from these data directionally. I would always recommend validating insights from multiple data sources vs. trusting that a single source is sufficient. No matter what, we almost always have to layer in assumptions based on our expertise to better understand to what degree we can shift business decisions based on what the data are telling us. 

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

Tim> A lot of people, outside of marketing professionals, think that we can track what everyone is doing online, see what credit card purchases they’re making, see what ads they’re seeing and zoom in on any one person and know everything about them. The reality is we are not looking at data in that way. Everything is at the aggregate level, looking at cohorts of people and how those cohorts think and interact and touch the brands with whom we are working. 

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?

Tim> The number one question is always about who the consumer is. Our clients want a better understanding of their customer, what they are thinking, and what information they need in order to engage with the brand. Brands are almost always collecting a lot of data on their customers—sometimes so much it becomes a challenge to process and make sense out of it. Using data science, we have been able to help our clients find relationships between disparate data sources to tell a more complete story of the customer journey, combining data from consumer insights surveys, sales data, web metrics and media engagement data.

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?

Tim> Data should inform creative, but never define it. I consider it a supporting tool and one of the many inputs that helps creative ideation and concepting. Keep in mind that it never should be followed 100 percent because no data set is ever perfect, complete or tells the whole story. I like to think of it as a useful mechanism to help inform creative.

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?

Tim> With our client Toyota, we have access to a robust leads tracking system that collects data from various sources including Toyota’s regional site, national website, dealership visits, Kelly Blue Book trade-ins, etc. All these different sources feed into one digital lead management tool.

Recently, we conducted an analysis of those leads—looking at which types of leads and sources were most likely to convert to a sale at the fastest rate, the highest conversion rate to sale and the lowest cost per vehicle sold. This allowed us to determine lead types that are most likely to convert to real business outcomes. Then we were able to tweak the weighting and prioritisation of the conversions within our marketing systems to favour those that were more likely to convert to a sale.

This analysis did help inform what kind of taglines and copy we should develop in our creative. At the end of the day, we were able to see which leads were going to drive the next step so we could determine the most likely path that gets selected by a consumer. Basically, it helped define the customer journey and navigate the customer shopping experience. Plus, we were able to achieve both media optimization and website customization through this analysis, furthering our ability to make momentum for our client’s business.

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

Tim> Data can absolutely be used in very interesting ways. We find unique opportunities to use it when we combine data sets, which typically requires some strong engineering and technical skills. However, when we are able to blend multiple data sets in a way where we can look at the data holistically, we are able to get creative. We combine our consumer insights, our creative, our media data and our client’s business data to build a more holistic story of the customer experience. This enables us to determine what is driving their decisions around product usage, submitting lead forms, visiting a website, interacting with a brand, changing their perceptions and attitudes. It’s all about finding ways to combine data sets that were otherwise not connected.

While our analytics team does roll up under the Media Department, we have begun expanding our area of focus beyond just media and creative metrics. Some of our clients are not even media clients at all. We are spending more and more time analysing finance data, sales metrics, consumer insights surveys and automating many of those data pipelines to empower other teams to be more data-driven and savvy.  

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?

Tim> First-party data is extremely important today, especially as privacy regulations have more of an impact on cookies and other forms of data collection. Since we are less able to rely on cookies and tags, we are more reliant on first-party data. It does add layers of complexity in terms of the regulations—such as is it safe to store that data or what are the compliance considerations around that storage.

However, we have found that working with first-party data provides some of the most powerful targeting opportunities. We encourage all of our clients to create a first-party data collection and process. In reality, if you don’t have your own first-party data then you are paying for someone else’s third party data.

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?

Tim> While we want to have as much robust and granular first-party data as possible, this is where we can start running into problems around data privacy—especially when we start collecting personally identifiable information. In some cases that is totally okay. For example, if a brand has an opt-in on its website it must include the appropriate language that meets local regulatory requirements customised to every specific market. So, when someone submits a lead, they’ve opted into sharing their data and approving the environment in which the data is going to be stored. This is normally the first step in collecting data, basically meeting those opt-in requirements so that you can collect data and store it.

However, there can be issues around deleting data. If someone wants to have their data removed you have to find that person across all data sets and delete them within a 30-day window and be able to inform that person about what kind of data about them you have stored.

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

Tim> The combination of AI technology and first-party data will allow for more personalization at scale of websites and ad creatives. With the industry moving toward a more privacy-focused framework, websites are able to collect less information about a user than before. This means more sites will likely start to require authentication so that they can validate who their visitors are, and customise the web experience. The internet is largely free content due to the collection and selling of user data. Once the current cookie-based framework goes away, sites will need new ways to collect and monetize data. The big players out there (Google, Facebook, Amazon, etc.) are already working on re-writing the web ecosystem to benefit their own ad networks. We’ll definitely be keeping a close eye on how this develops over the next few years. 

LBB> Is there one final takeaway that you think would be relevant for other agencies or brands to keep in mind when thinking about marketing analytics?

Tim> Definitely. I would say one overarching concept that we keep needing to emphasise with our clients is to break down data silos and look at data more holistically. Many of our clients and partner agencies struggle with having too many data sources, too many disparate data views to analyse and a lack of connectivity between data systems. Without technical data engineering skills, this can be a serious challenge to tackle, so we have expanded our offering to now include data engineering and data management as a standalone service we can provide to clients or other agencies. We have taken on a number of recent projects to help businesses with data automation, data warehousing and other technical engineering tasks. One of our agency core values is to Practise Perspective. Without the ability to link disparate data sets and structure data in such a way that marketing efforts can be analysed holistically, you will likely end up with fractured insights that are lacking perspective.