Welcome back to Sacking Growth Snacks. I'm Stephanie Ola and I am here with Reagan Dodson, director of demand gen at Refine Labs. Reagan, I'm so excited for you to be here today. I'm so excited to hear all about the way that you've taken your marketing ops background, your demand self-proclaimed demand nerd and creative junkie in marketing analytics, the fact that you are an infrastructure queen.
I love the fact that you are so passionate about data and streamlining all of this information to make it accessible and to have companies operate with integrity and efficiency. Thank you so much for being here. So happy to be here. Thank you.
We're getting started with the good stuff. What was your favorite childhood snack? Pizza rolls. Ooh.
Okay. Right out of the microwave or do you have the patience to let them cool? It just depends. When I was playing PlayStation, it would be right out of the microwave, but they're the best one in the oven.
And fun fact, if you dip them in Steakhouse A1 sauce, it's a game changer. We are talking about building a data democracy. Reagan, what is a data democracy and why is it so important? What a data democracy is and why it matters is that in too many orgs, especially what we see here, is that data is stuck in silos.
And it's controlled by a few key people. And what happens is if those people leave, everyone is left scrambling for insights. And this leads to misalignment, slow decision making, and wasted effort. So at its core, what we're really talking about is that data democracy is about ensuring that everyone in your org, whether it's marketing sales, your revenue teams, has real-time access to the data to drive outcomes.
And those outcomes are revenue-based, right? So a lot of the time, the CMOs are waiting on reports and there's a lot of bottlenecks or like the C-suite are waiting on reports. And really that data democracy is going to allow for clean, organized data that is streamlined between systems. And it's going to give you those real-time actual insights that feel smarter decisions and faster results.
Those are pretty clear positive outcomes right off the bat. What else is a benefit? Are there any other benefits of democratizing your data that go beyond access and the data itself to create maybe a better environment in your company? Essentially, what you want to do in a democratized data organization is it's going to enable very streamlined way of your normal marketer or your normal salesperson or your normal customer success employee to be able to interpret and act as a data analyst.
What that means is that it really opens the door for everyone. So it's not just data scientists or IT to leverage the same insights real-time. So there's going to be that better collaboration between marketing and sales, faster pivots when needed, and that's going to give you that unified view of what's driving growth. Another thing is like, why is it critical for marketing and revenue teams is that for marketing teams, you get immediate feedback on campaigns.
There's no retroactive view on campaigns. Of course, you need to do a retroactive analysis to see what really happened because especially on B2B, we know that campaign cycles and our sales cycles can be very long. But if you need to make adjustments, especially on digital advertising, a lot of what we deal with here at Refine Labs, you get those real-time insights into what's working, what's not, and you can make adjustments on the fly as a marketer and not have to go to your data scientist. Like, can you pull me this report?
And can you run this analysis because that's going to create a bottleneck? I imagine it creates more of a teamwork feeling as well. If you're not having to constantly ask for data, then these decisions can move from team to team. It feels like you're working as a full company rather than siloed departments.
Exactly. And that leads me to my next point, which is, why are your revenue teams looking at different metrics and data, right? So there needs to be a full-blown, I like to call them listening tours. So if you are embarking on this journey, which I definitely recommend that you embark on this journey, you need to do a listening tour, your operations teams, go do a listening tour, go talk to the C-suite, go talk to sales and all of your leaders.
What are they looking at? A lot of the times, probably 90% of the time, don't quote me on that. But everyone's looking at different metrics of what performance, good performance looks like, right? And so that's another thing of building a data democracy is making sure that you guys are defining what metrics matter, success metrics at that.
Are there any downsides or negative impacts from democratizing your data? Is there anything that becomes more difficult or a longer process that might be worth it, but something to consider when you're starting this journey? It does put a little bit of burden, especially on your marketing and sales team, to kind of take ownership, especially those entry level, mid-level associates or marketing sales, et cetera. But in the end, they're going to learn so much.
I think it's like one of those take a few steps back to come up and the project can be very, very lengthy. Another thing is, is you'll probably see C-suites getting into it about metrics and attribution when all of this stuff is uncovered. I think that would be a downside. I've seen it play out before where the big weeks are in meetings and they're like, oh, my goodness, attribution has been a mess for five years.
And we've been looking at the wrong data for five years. And marketing has been over or underreporting for this amount of time because the data has been a mess. So you're going to uncover either good insights or bad insights based on how your infrastructure has been throughout the last few years. Take that and just say, okay, we're here now and we're going to fix it.
But there's going to be a lot of things that are going to be brought up when a lot of resurfacing insights that could be positive or negative. It sounds like a tough process but a really, really worthwhile process. In the next episode, we're going to talk about what that process actually looks like and how to democratize your data. So we'll see y'all then.