Marketing science is the application of data analysis and data science to solve marketing problems. The idea is to deeply understand individuals at a granular level and use that insight to drive highly differentiated experiences.
Bring together the creative aspects of data science and marketing to increase your impact.
I started in this space before it got cooler. I've always been good at math and science and loved using data and analysis to solve problems. Prior to joining Rapp, he was a partner and regional director at Blend360, where he spent 20 years shaping the marketing science practice at Epsilon and FedEx.
Currently, I report to Rapp's CEO, Marco Scognamiglio, and lead a global team of marketing scientists from around the world. Depending on how you count between Rapp and his OPMG, our numbers range from his 250 to his 1,000. We are present in many different markets around the world, not only because we have customers from all over the world, but also because we are always looking for the best possible talent.
The required skill sets are in high demand but in short supply. That's why we ensure that we recruit and develop the best possible talent from around the world. We have open positions and continue to grow in nearly every region.
We create innovative, data-driven approaches. These data-driven approaches are inherently aimed at enhancing our clients' campaigns, optimizing the customer experience, and driving measurable results.
We want to ensure that the results are tangible, quantifiable, and that they benefit our clients and their customers. We focus on leveraging advanced data science and AI. But we do it in a way that demystifies that complexity for our clients.
Most of our clients now want to become data-driven. We provide them with insights that enable progress. Or, provide users with advances in AI, such as accessible tools that help automate both mundane and traditional creative activities, and conversational AI integrations that democratize AI. Instead of relying on thousands of records, you can ask questions and get answers in English.
We bring together relevant data, content, and decisions to enhance customer interactions, while remaining committed to privacy and ethical considerations. None of this would be possible without a talented and high-performing marketing science team.
I talk to clients every day about providing and pitching solutions. You need to put yourself in their shoes. The important thing is to be able to communicate in plain English and not get caught up in the buzzwords of the day, being aware that the solutions that may be used may be complex.
Don't worry about the jargon. Words are not as important as the story. It's not just about telling the story of sausage making; The key is to tell the story of your results and analysis. That means what our clients need to do to make an impact, and how we can help them do that.
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It's important to be able to tailor your communications based on who you're interacting with. A conversation with a CMO is very different from a conversation with a chief data officer and chief information officer. This is easier said than done.
What problem are we solving? What kind of data do we have? What is the best quantitative approach we can use? After we have done that analysis and developed the model, we can What are your findings? Based on them, what recommendations or changes would you like to try? What impact would you expect to make on your business if you make these changes?
The core questions of business haven't necessarily changed. But AI is everyone's top priority. What does that mean to me? How can we make it real? How can I generate quick wins so that this isn't just something that exists in Powerpoint? What are the steps I need to take in the next month, within the next three months?
To be successful as a data scientist, you have to have depth in terms of skill set, but you also need brand expertise in terms of thinking through problems.
As told by Sam Bradley
