Welcome to Season 4 of the Marketing Science Podcast, the podcast for sales and marketing professionals working within science, engineering and healthcare.
We’re delighted to welcome Jamie Grabert for episode one, Director of Media at DeanHouston. Jamie shares her knowledge of data-driven marketing strategies, the application of data and how to utilize it to make business decisions that define your goals and objectives.
The podcast covers the following topics;
- How important key decision makers and the wider team are in developing a data-driven strategy
- At what stage a company should think about having a data scientist involved
- The danger of manipulating data to prove a hypothesis
- Finding the right balance between data-driven thinkers and creatives
- Data monetization in scientific marketing
- Creating buyer personas
- How to stay ahead of tracking legislation and privacy
- Recommended tools for data marketing
"Whenever I ask for something from leadership, I go to them with a handful of data points. No more than that, because I don't want them to get bogged down in the details - And whenever I take that approach, I'm never told no."
How important key decision makers and the wider team are in developing a data-driven strategy
Jamie explains that when setting up a data science platform you need everyone’s buy-in, from sales to production. A group of marketer's biggest obstacle is ROI, and without communication from the sales team, how will they know which activities are actually working? Knowing the impact of a marketing campaign from the sales team allows the marketing team to know how the audience resonates with their efforts.
“You need to communicate with sales and say, okay, here's what we're doing but we need you to close that loop for us. We need you to tell us what resulted in a sale."
At what stage a company should think about having a data scientist involved
For medium and large businesses, Jamie feels data science is going to be critical. Most businesses already hold more data than they realize, which can be harnessed into usable information to effectively target segment audiences.
How to effectively use data for storytelling and sharing brand messaging
Jamie clarifies that first and foremost we need to define the difference between reporting and storytelling. Reporting simply shows what the data says, creating a narrative through the data points allows marketers to show what the data has shown from multiple angles and how to move forward using that information.
"That's what data storytelling is for me. It really blends things that I love. I love to learn new things, and be strategic, and think about how things work, and how to make things better."
The danger of manipulating data to prove a hypothesis
You can make data say whatever you want it to say, Jamie explains. But, data scientists are smarter, feeding raw data into Python, R, Tableau and other engines to let the data explain itself. Finding the data points that are explaining themselves rather than data points to support a narrative, will show what is really going on.
Finding the right balance between data-driven thinkers and creatives
Jamie describes her team as a data analytical driven piece of their organization, they are creative people but very detail oriented. By sharing their recommendations to inform the creative team from their findings, the feedback and data support ideas for future advertisement without taking away from the content team’s ideas and input.
Data monetization in scientific marketing
Examining how you can use data gathering activity to generate revenue, Jamie discusses how audience engagement with a particular topic can be expanded into further content creation with the backing that it is more likely to generate revenue.
“How can you use the data that you have to generate revenue, very simply. For example, it's seeing, wow, people are really engaging with this topic. Maybe we need to have a newsletter about that."
Creating buyer personas
Using your business goals and objectives to define your target personas, Jamie illustrates, data analysis can show the content that has already been engaged with and lead to content planning inline with those engagements. Continuing to build your data set then creates niche target markets to pinpoint your marketing efforts to.
How to stay ahead of tracking legislation and privacy
Start testing non-intrusive ways to collect quantifiable data now. This will stop you from falling behind when legislation gets tighter. Jamie discusses how we need to be smart and strategic about data collection.
Recommended tools for data marketing
Jamie recommends taking some of the classes on LinkedIn for a better understanding of data science, alongside webinars and podcasts. Start with learning, then identify your goals and objectives and research tools to assist with those specifically, like Microsoft BI and Adobe; before moving into JSON, Python and R further down the line.
“Then talk to your vendors, and have them walk you through how to set it up. If you're paying that kind of money for something, your vendor should meet you halfway and teach you how to use it."
Leave a comment on LinkedIn
Want to be on the Marketing Science Podcast? We are always looking for guests who can share an interesting story and value to our listeners. If that sounds like you, then get in touch by contacting Danny on LinkedIn.