TLDR: The need for marketing ops to surface dollar values, improve processes, and validate ideas makes data science a natural ally. When MOPs and data science teams work together, revenue and lead generation become easier to predict, benchmark, and grow.

The importance of data literacy: Marketing is now a data-driven discipline, where a top priority is to understand what generates revenue and drives growth. Data literacy is crucial for MOPs to handle data, structure their systems, and answer decisive business questions.

The problem for most MOPs teams: Unfortunately, teams often lack the skills and resources to manipulate and turn data into an asset that generates value. Data scientists are the ideal collaborators for MOPs to validate ideas and improve processes, but they’re hot commodities in every workplace.

How to get the collaboration green light: When budgets are tight, it’s easy for C-Suite to overlook marketing when approving spending for data science projects. So, if you want the green light on a collaborative project with data science, show your CFO and CIO that the ROI makes sense.

What’s in this article for you? In this Tough Talks Made Easy, we’ll guide you through the conversation you’ll need to have with your CFO. You’ll learn how to:

➡️ Make data-driven decisions.

➡️ Collaborate effectively with data science teams.

➡️ Justify data-driven investments to leadership.


How data science enriches marketing

One of the most persistent challenges marketing teams face is proving their success.

If you’re in a low-margin business in particular or otherwise facing cost strains, there’s extra pressure from your CFO to show your contributions to the bottom line.

Marketing as a space also has many ‘common sense’ generalizations of best practices floating around, but the likes of “never send an email on a Friday” don’t hold water for your business without evidence.

Without the data or the know-how to interpret it correctly, your team is validating decisions and measuring success in the dark.

The need for MOPs to surface dollar values and make good judgment calls makes Data Science a natural ally.

MOPs collects lots of data from campaigns, which Data Science can turn into detailed customer profiles and identify purchasing behaviors.


“Data science connects and maps the entirety of your business’ data to spot patterns and understand how to optimize processes.”


Data science connects and maps the entirety of your business’ data to spot patterns and understand how to optimize processes. Where Marketing generates leads, Data Scientists automate changes to the lead journey to trigger positive engagement behaviors.

When MOPs and Data Science work together, revenue and lead generation become easier to predict, benchmark, and grow.


Collaborating with purpose

Data science teams work their magic using emergent technologies, like machine learning and artificial intelligence, which are expensive for companies to deploy.

This means collaborative time with Data Science and new tools requires a budget for development, which involves your CFO and CIO.

Considering the costs, your C-Suite is looking to allocate data science resources only to teams that can justify the investment with impactful results.

You can make a few points to leadership in response.

👉 By modeling the business end to end, Data Science can see what brings in the most revenue, and as one of the most commercially-minded teams, Marketing should be at the top of the list. The more you invest in making campaigns compelling in response to audience data, the more likely the business will win deals.

In other words, investing in Marketing boosts the whole organization.

👉 The insights that Data Science provides can create a strong audience for a product/service and attract more customer segments to it.

👉 Collaborating with data science can help find solutions to streamline operations through automation and cutting processes to achieve better outcomes.

Bottom line: Whatever your proposal, frame it to C-Suite with intended results and impact in mind. 

After all, you’re not running experiments for their own sake — you’re working with Data Science to help Marketing make or save more money than you spend, investing less per lead generated than you bring in. That’s the language your CFO and CIO speak.


Set appropriate expectations

Leadership can be adverse to risk or expect quick results, which means your CFO or CIO might be hesitant to play the long game.

A dose of reality: if you’re trying something new, you need time to ride it out, make sense of findings, and realize the benefits.

Suggest running campaign experiments with small subsets of your audience first, as a proof of concept, to make the idea more palatable to a hesitant CFO. 

On the whole, explain the analysis and modeling you want to do, the included limitations, and what you’re trying to achieve with revenue when testing certain actions.


“If you can estimate the ROI at 1.5-2x what you spend, you’re likely to get the green light.”


Focus on how the results can benefit the business, and if you can estimate the ROI at roughly 1.5-2x what you spend, you’re likely to get the green light.


Investing in success

MOPs and Data Science together can be a force of nature, making the wealth of data that Marketing collects actionable and steering better strategic decisions.

Come to any conversation with leadership with a clear plan of action and a confident sense of how collaboration with Data Science can boost the bottom line.

Need some help with data? Drop us a line to chat