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The rise of the marketing scientist (2023)
and how you can start with data in your business
Thomas Varekamp
January 06, 2023
Hey there 🙋♂️, it's Thomas.
In today's issue, I will talk about the rise of the Marketing Scientist and how you can start with data in your business.
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In the fast-moving world of business, it's more important than ever to make informed decisions based on data. One profession that can particularly benefit from data-driven insights is marketing.
Currently, there are a lot of gaps in this space. Most marketers make decisions based on best practices from 10 years ago, or wrong intuition.
One of the roles I see more and more is the Marketing Scientist: a marketeer that uses data science to maximize the returns on marketing. He or she is able to conduct rapid marketing tests to determine the effectiveness of various marketing activities. With the analytical skills to set up experiments and analyze results, the marketing scientist is equipped to make the best decisions.
One key approach is the use of predictive analytics, which can help marketers anticipate future trends and customer behavior. By analyzing data on past customer interactions, marketers can build models that can predict how customers are likely to respond to different marketing campaigns or messaging strategies. This can help businesses to optimize their marketing efforts and make more informed decisions about how to allocate their resources.
Another way that marketing scientists can use data science is through the use of machine learning algorithms. These algorithms can help marketers automate certain processes and make more accurate predictions about customer behavior.
For example, a marketeer might use a machine learning algorithm to analyze customer data and identify patterns that indicate when a customer is most likely to make a purchase. This can help businesses tailor their marketing efforts more effectively and reach the right customers at the right time.
But data science isn't just for marketers. In fact, having basic data analysis skills can be valuable for any business professional. A supply chain manager may use data analysis to optimize inventory levels and improve delivery times. An HR professional may use data analysis to identify trends in employee retention, performance, and satisfaction. And a customer support center may use data analysis to identify common issues that customers are facing and to improve their support processes.
By now you're probably wondering how you can start. It's normal to feel clueless when starting with data.
Here's a tip: start with questions.
What questions do you have in your business that when answered, will help in an important decision? If you have questions, you can search for the data to answer these questions.
I compiled 20 questions to ask your data:
Sales
What is the revenue per customer?
What is the revenue breakdown by device?
What is your cost of acquiring a new customer?
How many new customers do you get per month?
Is most revenue coming from new or repeat buyers?
Customers
Who are my most valuable customers?
What % of customers are discount buyers?
What % of customers are frequent buyers?
What % of customers are one-time buyers?
Which customers are most likely to buy again?
Marketing
What is the revenue per email?
Which promotions drive the most sales?
What is the monthly abandoned cart rate?
What % of sales come from which channel?
How many subscribers actually read emails?
Products
What are the margins per product category?
What product categories are best performing?
Do specific zip codes have higher product sales?
Which customer is interested in this new product?
What is the purchase frequency of certain products?
Analytics has become very accessible to all. By using data to inform decision-making, businesses can stay ahead of the competition.
Final notes
You shouldn't use data for all your decisions. Data can be a powerful tool for informing decision-making. By analyzing data, you can gain insights and understanding that you might not have otherwise had, and this can help you make more informed, rational decisions. But it is not always practical or even possible to analyze data for every decision you make. Sometimes, you need to make a decision quickly, and in these cases, you should rely on your intuition
As a rule of thumb: Use data for decisions that have significant consequences or long-term impacts. Use intuition for quick, routine decisions.
If you found this helpful, please forward this email to 1 friend or colleague. They'll appreciate you and you'll help to spread the word of data.
See you next week!
Thomas