Okay, Reagan, what is the best snack you have in your house right now? If I ask you to run to your cabinets and grab something good, what would it be? Oh, my goodness. I'm not really a snacker lately, but I would say the best snack in my house right now would be just like turkey pepperoni, just like grabbing it out of the container and just putting it in my mouth.
That is, that is what I snack on. It's Guilfry and it's really, really yummy. Welcome back to second growth snacks. I'm Steph Canola and I'm here with director of demand gen for refine labs, Reagan Dotson.
We're talking about building a data democracy. Last episode, you heard Reagan talk about all of the benefits of building a data democracy, why it's so important. And today we're going to actually talk about how to do that. So where do you start, Reagan?
If you want to make sure that all of your employees have access to the data they need, but you don't want to overload them with a waterfall of data right at the top, how do you start the process of building this data democracy? I think the first thing that I would do is invest in self-serve tools, data tools. So that's going to give the teams tools and access to enter with the data without relying on others. And another thing that I would make sure of in this roadmap is to make sure the CRM, the marketing automation and analytics platform argues are friendly and accessible.
So that could be another project within itself. When establishing a data democracy, that could have a long project lifecycle. Depending on where you're at in this journey, you might have to procure something new, you might have to rip some things out and replace them with more user-friendly tools. But during that journey, I would definitely hire or onboard an implementation consultant to make sure that it's done the right way and really bring in that third party to educate and help you enable those folks that are going to be self-serving.
This kind of begs the follow-up question of if you're giving all of the data to all of your employees, letting them have access to all of it, they don't necessarily need all of it, right? So how would you coach individual employees to empower them to analyze the data that they have access to that they need, but be able to move past the data that they maybe don't to not be overwhelmed? That's kind of where the siloed approach would come in, right? Because I think sales and marketing teams should be looking at the same data, but however, sales really doesn't need to get into the nitty gritty of marketing campaigns.
And I think that marketing should have all of their visibility into what sales is doing and what that sales cycle looks like, right? So I think the first thing would be centralizing data governance. Another data needs to be clean and reliable first, and then you would need to set up governance processes that ensure data quality, security, consistency across the board and really outline and define what those metrics are for each group. So that sales notes, okay, when I go to this dashboard, this is what I'm looking at.
Marketing goes to their dashboard, this is what I'm looking at. This is how the data is pulled. Customer success, this is what this looks like. And you have a whole SOP where you can, as a marketer, I want to see what the customer success metrics are looking like, what are renewals looking like.
And you have that blueprint of how other teams are looking at the data and how you should be also interpreting your own data. So would you recommend a kind of full pause, get this data organized, and then move forward little by little with training employees who either come in new or who are getting used to this? Is it something that you want to try to do all at once or would you take a little by little approach? I think it just depends on the organization, right?
And I think our main philosophy here, refine, is that it is better to invest in this now and not wait because you're wasting money every single day that you have bad data. And so my whole philosophy is if you have the resources, you have the budget, do it now and make it a priority and get stakeholders involved. If you don't have the resources, if you're a series A, if you're a series B and you're like, I know this is an issue, but we don't have the in-house resources, but you can always come to refine labs and we can help you build out that project, right? We will help you with marketing apps and bread labs and things of that nature to kind of take the project planning off of your back.
And we have partners that will also help with that as well. So if you are like, I really can't afford a full-time hire, but you can afford an agency, then you can start there. And a lot of times third-party people that come in or companies that come in are taken more seriously than in-house employees for some reason. I don't know if it's just any perspective and there's like, I'm paying this person, which you're paying your employee, which makes no sense.
But I see the job getting done a lot faster because they've done it a lot for other companies and they know what that project lifecycle looks like. Do you think there might be some sort of objectivity there as well if someone new is coming in that you trust them to be objective about your data infrastructure and your organization rather than someone internal who might be too close to either folder management or naming conventions or any of those things that could be a barrier to using someone in-house? Yeah, I think that's definitely what it is. There's a lot of times where projects, I've seen projects move so much faster.
Just by when I was in-house market, I'd be like, I'm bringing in this implementation consultant to help us and kind of echo what I've been saying this entire time and they're trusting a little bit more. And then obviously too with how we consult with our clients, we're a fresh eyes and they're a lot of our infrastructure and we know exactly what to look for, what our infrastructure philosophy is. And so I think that a lot of our clients just trust us right off the bat because we're something matter experts in that area. Now, you love data.
You love keeping data clean and organized and efficient. What are some kind of quick tips that you have for someone looking to get started to start organizing their own data? I'd say gain some qualitative insights first. Do those listening tours like I mentioned with stakeholders to see how they feel about the data integrity of your systems.
If you are getting mixed reviews, that means that something is definitely wrong. If your CMO and your CEO are constantly going at it and meetings, you should definitely start there. The second thing is document what they want to look at. So the CMO is like, I really care about looking at pipeline velocity.
I really care about looking at ROI from all of our campaigns or channels or whatever the case may be, then listen to them, write it down and keep them along for the ride and build a whole project plan off of that. And really document every single dashboard that you would want to create, what you want those visualizations to look like based on what your stakeholders are saying and create that project plan. The next thing is to start looking at your tech stack to say, what are we using? You could have some tech debt because a lot of times I'll see companies, they have all of these different marketing analytics platforms, attribution platforms to try to bandaid what their business intelligence team doesn't have for marketing.
A lot of the times are BI teams. They don't understand the marketing realm and what data comes from marketing. And so it's really important for you to partner with your BI team because they're going to be the engine behind making sure that your data is clean. So I would take them along for the ride and then get rid of any tech that is not working, that you've just procured and reinvest that into this project.
So those are a few tips that I would use to start and also just simply asking what fields are you looking at to other people outside inside and outside marketing? And if it's totally different, then you know, you know, do a complete field on it and see where the waste is there. So that's great information. Thank you so much, Regan.
Next episode, we're going to get into the maybe daunting conversation of communicating all of this to your leadership. And I'm really excited to hear some advice and tips for that. So we will see you all next time.