The 3 Roles You Need for Your Marketing Analytics Dream Team
Getting your marketing analytics function started is hard.
The hiring process takes too much time. You can’t know for certain if you picked the right candidates, and let’s not get started with the time-consuming onboarding process…
You really can’t afford to go wrong with this. According to the U.S. Department of Labor, a bad hire can cost your company 30% of the employee’s first-year earnings. The Society for Human Resource Management (SHRM) puts the cost closer to 40% when accounting for the total cost including lost productivity, lost hours of training, etc.
At MASS Analytics, we have advised Fortune 500 firms on building their internal Marketing Analytics teams. Additionally, our experience successfully delivering Marketing Mix Modeling projects has provided us with genuine organizational insights for selecting analytics talent, in terms of skillset and character.
In this article, we focus on the 3 key roles you need to build a highly effective and agile marketing analytics team. Whether you’re an advertiser looking to in-house your MMM process, or an agency setting up a Marketing Effectiveness function, this will serve as a useful guide for the right talent to look for.
The Project Architect
The Project Architect charts a realistic project timeline and keeps everyone on the team accountable for delivery. They regularly review the work of the team and make sure the final output satisfies clients’ requirements. They are also deeply embedded in the technical side of the work and have a clear sense of the time each phase of the MMM workflow will take. The Project Architect’s superpower is their ability to juggle multiple projects at the same time all while managing clients’ expectations.
When considering candidates for this position, our Director of Marketing Analytics suggests asking these questions:
- What are the key factors and macro-level steps for successful MMM Projects?
- What are the strengths and weaknesses of MMM methodologies and how do they compare against the other marketing effectiveness measurement approaches (MTA, experiments)? Can these approaches be complimentary and how?
- How do you ensure your MMM model combines the science stemming from the mathematical methodologies and the artistic side based on business understanding?
The Senior Marketing Analyst
The brains behind the operation, the senior marketing analyst builds the models and develops a commercial interpretation of the results.
Keenly aware that Marketing Mix Modeling is both an art and a science, the senior analyst reviews & fine-tunes models, making sure they are statistically sound. Most importantly however, they make sure that the final results reveal a story that makes business sense to stakeholders, thanks to their strong storytelling and data visualization skills.
You can count on them to present the findings coherently, beautifully, and succinctly.
One superpower they have is their ability to push through difficult bottlenecks and ensure the full delivery of a Marketing Mix Modeling project.
Meher, Senior Marketing Analyst at MASS Analytics recommends asking the following when interviewing candidates:
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- How do you evaluate the relationship between Media and Customer purchase action, is it immediate? How can we reflect such a relation with data?
- Imagine you have 2 models. What is the best way to compare them and decide which one is the best? Do you think statistical metrics are enough to assess models? If not, what are the other options?
- What is the nature of the relationship between Media Spend & Revenue, what is the best way to visualize it? Which purpose do we use it for?
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Skills to watch out for
Project management, regression modeling background, experience in MMM, ability to build models & develop a commercial interpretation of results, storytelling, expertise with data visualization tools (Power BI, Tableau, Excel)
The Junior Marketing Analyst
Junior marketing analysts work on all, or some, steps of the MMM workflow under the guidance of the senior analyst. They clean and prepare data, do the early model iterations, and shape a story behind the model.
Data cleaning and processing in particular is a priority for junior analysts. This phase is critical because it determines the quality of the model results. It demands someone with good attention to detail, making sure there’s as few anomalies as possible!
Skills to watch out for
Regression modeling background, data management & preparation skills, attention to details to investigate and discover data anomalies, Data Charting & Visualization, knowledge of dashboarding & visualization tools.
Conclusion
It takes the right talent to run Marketing Mix Modeling projects. With careful planning and execution, you can assemble an MMM team that will take your business to the next level. At MASS Analytics, we help companies with Marketing Mix Modeling, learn more here.
