RevOps Leaders

Data-Driven Farm Management: A Conversation About Agri-data and RevOps with Granular’s Mollie Bodensteiner

Our latest Data Superhero, Mollie Bodensteiner, discusses the joys of operationalizing revenue funnels, forecasting data disasters, and what it’s like transitioning from the world of software services to soil science.

All Mollie Bodensteiner wants to do is, in her words, “build cool sh*t.” Today, we sat down with Mollie to chat about the joys of operationalizing revenue funnels, forecasting data disasters, and what it’s like transitioning from the world of software services to soil science.

“When I started at Granular they asked me, ‘What do you want to do?’ and I replied, ‘Solve problems that center around the customer.’ Just let me build things that provide value to the customer,” she says.

Mollie is a frequent speaker at the American Marketing Association’s Iowa chapter, where she shares her thoughts on how RevOps teams can grow and mature. She was raised in Des Moines, where her career began as a marketer for education and healthcare companies. With each successive role, she has gravitated to increasingly technical positions — from business implementation manager at Marketo to her current role as Director of Revenue Operations at Granular, the digital arm of an agricultural leader.

Many things make Mollie unique. One is that because of her skill as an individual contributor, she is often elevated into leadership roles, but she still sees the value in contributing despite management duties. Call it a “player-coach” type role. The other is that few people I know have a more granular (pun intended) understanding of how revenue systems work, and that gives her an uncommon ability to spot thorny problems years before they emerge.

Nick: What was it like transitioning into the agricultural space?

Mollie: It was weird. Despite being from Iowa, I never anticipated working in agriculture. I’d worked at Marketo, and before that, a health insurance company, but what I realized looking into this role is that across verticals, the same concepts and problems exist. If anything, it’s some of the less stereotypical modern industries that have their RevTech figured out. It’s often the SaaS companies who you’d think would be cutting-edge who are a real mess on the backend. You wouldn’t believe how many MarTech companies who email me still use the default Marketo unsubscribe page. I always reply, saying, “You should have your team look at this.” It appears there’s a bit of marketing myopia in software.


Can you tell us what Granular does?

I think of it like an operating platform for farmers. It’s a suite of farm management applications that allows farmers to manage their entire operation—from team efficiency to soil productivity. For instance, Granular provides satellite imagery so that farmers can spot problem areas in their fields and take action accordingly. We also have a planning, inventory, and revenue analysis tool that functions like an accounting software specifically built for the agricultural industry. And then we have the ability to analyze data directly from the farm’s machinery to provide agronomic expertise specific to each customer, right down to differences in each field.

Ultimately we’re focused on helping farmers leverage data to optimize their inputs to produce better returns. With Granular, they can ask questions like, “How is my field performing compared to my yield targets?” and “Am I putting the right nutrients in the ground?” There’s a whole data science component that gets into predicting weather patterns and their implications and it’s all quite cool.

What questions are you asking yourself today?

From a RevOps standpoint, I’m asking, “What am I putting a band-aid on that’s going to leave a scar?” In RevOps I find you have to continuously step back and re-confirm what you’re trying to accomplish, otherwise you end up with short-term fixes that leave lasting damage. If you let something sit too long, it may become impossible to rip out.

I’m also asking, “Are we doing right by the customer?” Because very often, it’s the operations that drive customers’ feelings about whether we know them or not. When the customer interacts with us, they expect we know everything they’ve provided us previously. They know the last time they logged in. And they know the last ticket they submitted. They also expect that we know it too, and if we have access to all that data, and we should. I see it as RevOps’ job to surface that information in a way that drives higher-impact customer interactions.

When you have sales, marketing, and support all interacting with the customer independently, you really have no concept of the holistic customer journey. So much of what customers feel hinges on the right people having the right information, and it’s the difference between a good interaction and a bad one.

Companies that have the data operations focused on doing right by the customer are always more successful, in my opinion.

What’s the most important aspect of RevOps as a practice?

I think one of the most important aspects is that RevOps brings similar functions together. When you have the people who own the sales technology, marketing technology, and customer success technology in one spot, you have a team that’s able to consider the big picture.

One other important aspect is that RevOps creates a useful wall between administrators / operations pros and the organizations they serve. A sales operations person who reports to sales is forever putting out fires. But if they sit in RevOps, they can do a better job prioritizing what’s going to be most helpful to the customer.

What other teams do you work closely with?

Here at Granular, we work very closely with the product and data analytics teams. Ultimately, they’re the keepers of the all-important product usage data we need to surface. So while we support go-to-market, we’re really the bridge between go-to-market and product, which gets fun, especially on the systems side, integrating all of the products and data that goes along with each.

One of the big initiatives we kicked off last summer was solidifying a single view of the customer, which I would say is more of a mindset than a precise reality. You’re never going to flip the switch and have every piece of data in place and know exactly how to use it. But if you aim for it, you’ll wind up with a more holistic view of the customer so you can better anticipate their needs and know what happened to them last or how they’re actually using the product. For that to work, you need tight data alignment across the organization, not just go-to-market.

What’s one of the biggest mistakes you see RevOps make?

It ties to one of my favorite Steve Jobs quotes: “You have to start with the customer experience and work back toward technology.”

So often, I see Revenue Operations professionals putting technology before people and process. We get so distracted by the shiny objects that are at our disposal (it seems like there is a tool for everything nowadays) that we make a technology decision before really establishing the problem that needs to be solved.

It’s so important that if the people and process components are not defined before investing and implementing a new technology solution, you shouldn’t make that investment.

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What’s your favorite thing about RevOps? Operationalizing revenue funnels, for starters

There’s really nothing I love more than understanding and operationalizing the customer journey. That’s always my winning moment. Just because there’s so much value in actually going in and filling those processes out, and everyone having to ask, “What happens next?” Then you whiteboard your customer journey and ask, “How do we operationalize that?” And then, “How will we report on it?”

Operationalizing revenue funnels is my gold-star moment because if your company doesn’t have a revenue funnel/flywheel that you’re evaluating every six months, you don’t know your customer. And if you don’t know your customer, how does anyone know what they should be doing? What should Sales be doing? What should Marketing be doing? And what should Customer Success be doing? What’s the value you’re providing at that stage?

And of course, there’s the biggest question of all, “How will we measure what we’re doing?” Without a baseline, it’s hard to know whether you’re being successful, which makes it difficult to be successful. All of that stuff you have to build to answer those questions, and that’s the part I enjoy the most.

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