This is your host, Tori Kinlick, and today I want to welcome my colleague Allison to the show. Allison, do you want to give a quick intro here? Hi, my name is Allison Lomond. I'm a VP of Demand Generation here at Refine Labs.
And I'm really excited to kick this off. And this is a topic that we're going to talk about today very near and dear to my heart. So, we've got a great topic that I'm excited to jump into, but before that, a little bit of an exciting mini announcement here. So, we're trying something new with our second growth podcast and a few of us are going to be buddying up on a couple episodes for a period of time.
I don't think we're exactly sure how long the experiment is going to run for. But Allison and I are going to be the dynamic duo leading you through this episode and at least one other every week for a little while here. We'll kind of see how things go. And today's topic is a great one.
But I think what I'm most excited about just related to this partnership I have with Allison and the topic here is that I was doing some thinking today and I realized I'm going to blow up your spot here, Allison, that I have recently identified what Allison's superpower is. Allison, her superpower is that she does the best work when she is helping other people do their best work. And so what I mean by that, I kind of call it the Michael Jordan effect that people who are great at what they do are able to up level everyone else around them just by doing their job by taking on the roles and responsibilities that they're being tasked with and all the people that are working with and for that person end up just effectively up leveling their work as well. And so that's something that I have seen from Allison and the team that she has been building around here over the last couple months.
And that's why I'm also really excited that we get to start partnering on some podcasts because hopefully that means that she's going to make me do my job a little bit better, which is what I'm secretly hoping for here. So Allison, you know, figuring that start things off a little bit with some flattery here and yeah, just kind of get the ball rolling into our topic from here, which is. Well, that's a much nicer reason. I was in Sam excited to work with you because we've got Shiteown, Philly, great sports teams and then you go and compare me to like the best Chicago athlete of all time.
Michael Jordan, this podcast is off to a great start. All right, good stuff, good stuff. Well, I'm glad that that was received well. I guess I didn't really think through this Chicago affiliation there, but yeah, I was like a White Sox Cubs reference that could have gotten dicey, but we're good.
All right. So today we're going to kind of talk through, I guess we're telling the episode early indicators for measuring demand creation impact, which is really a long winded way of saying like, when can we marketers who are starting on this demand creation journey? When can we start seeing some results from it? And it's not always such a black and white answer as far as when those results are going to come in.
There's certainly a lot of nuance to it depending on the size of the deals that you're working on, the length of those sales cycles historically. There's a lot that gets factored into it. But there is, I think, some commonality in terms of like the leading indicators and the different data sets that marketers can and should be looking at. And so that is, I think what we're going to focus quite a bit of our conversation on today, because it is a frequent question we get from our clients.
It's, hey, we've been doing this demand creation thing. We've been working with you for six to eight weeks now. And the higher ups are asking me, where's the ROI? What's coming from this investment?
These un-attributable sources that we're now spending a lot of time and energy building up. And so how do we approach this? And it's a great question and not always a straightforward one to answer, but one that Alison and I have definitely been posed with a number of times. And so we're going to take you through a little bit about how we typically address the question.
And some of those different data points that are going to make the most sense to look at. And before we dive into all that, which Alison, I think, has a great framework to take you all through, my contribution here, I think, is more so the upfront expectation setting, because that's going to be absolutely critical to getting people on board and practicing the patients that's going to be required to see this through. Because the reality is creating demand takes time. If you think about it from the buyer's perspective, it's rare that you're going to be scrolling through your LinkedIn feed and just see an excellent ad.
As great as an ad can be, that's going to make someone just on a dime stop what they're doing and go make a purchase. People just don't buy that way. And so it's all about that consistency and getting your ads in front of people, trying out some different tactics and strategies and figuring out what the right mix is going to be. And I think the other part to consider here is just where your brand is, where your solution is in terms of the awareness levels of your buyer.
So there's that spectrum. They're the unaware, the category aware. Do they know that they even have a problem right now? Or maybe they know it, but don't really want to admit it.
The problem aware, right? They know they've got a problem. Don't know the solution, solution aware. They know they've got a solution, but don't know which product to solve.
And then you can kind of get into that like brand aware and purchase intent where people are much more likely to actually take some type of action and throw up that signal that they're ready to enter the sales process. So that's the preamble, right? Those are kind of all the upfront things. But getting to the actual meat of the question, Alison, what is the best way for marketers to be really measuring success before that success might start coming in the way of CRM dashboards getting lit up and all those KPIs that everyone's waiting for?
Yeah, exactly. Everything that you just touched on is really the information that you need to have to build the case to run demand generation. So that is definitely step one is level setting. The playing field in terms of how long demand creation is actually going to take within your organization, looking at things like sales cycle and your overall buyer awareness levels.
And then it kind of turns into this launch strategy. So typically what I see as you get buy in, then you spend a lot of time creating your first maybe round of creative, your go to market messaging, and then you've launched and then it's kind of like what now? And I think that's the biggest question that a lot of marketers are looking to answer. And it actually is a question that even if it's not your first launch, it's something that you're going to be answering all the time, probably monthly.
What should I be looking at? What is indicating success? And so one of the things that I really love about refined labs is that we take very complex processes, which performance marketing in platform paid media marketing is can be very, very complex. But we take something that is complex and we try to make it simple to understand, to digest and to help our clients have the right narrative to be able to go internally and share the success that they're seeing in a really easy to understand story.
And I think where that starts is having a good understanding of the objectives that you're trying to reach within your paid platform. So today I'm going to just talk pretty specifically about leading indicators from demand generation from a paid advertising perspective. Of course, we know there are a lot of other components that go into demand gen, certainly organic, social being an absolutely huge one, employee advocacy. All of those are other kind of arms.
But where most people start and it makes sense, they start with paid advertising because it's the easiest way to get your message in front of your target market. So my objectives and KPIs are really going to be focused on primarily the LinkedIn and meta platforms. And essentially, there's only a few things that you really need to understand as you go into your new demand generation strategy, which is hopefully very focused around reaching the most amount of your target audience as possible and focusing less on that direct response or that direct conversion campaign objective. So going to assume that you've made the switch, you are running reach-based campaigns, you're optimizing for reach, maybe you're optimizing for video views, maybe you have some traffic campaigns in there, but you've made that switch from direct response.
And so when you've done that, you really need to look at a few main KPIs to understand what type of success could I reasonably see. And those for me are always what is the estimated audience size on these platforms. I'm going to start here with that. So estimated audience size, easiest way to do this is to go into LinkedIn, build out your ICP.
So whether this is by job title, maybe it's by geo, there's a couple different ways you can segment your ICP. You want to start building out those individual audiences and understanding, okay, sales decision makers, sales leader decision makers in North America, LinkedIn is saying there are 400,000 of those on the platform. So that is my total market size. What LinkedIn is estimating is active on the platform.
Asuna, let me just jump in right there. So any guidance for our listeners there about like, you know, just a general rule of thumb in terms of what a healthy audience size might look like when you're optimizing for reach, right? I feel like for so long marketers were all about hyper segmentation, the smaller the audience is, the more personalized the message, the better. But we're out here right now kind of saying that, you know, it actually might be more beneficial to have a larger audience.
You know, if you are effectively optimizing for reach, reaching more people is the objective. So maybe could you just spend a moment kind of talking through that rationale? Absolutely. So my rule of thumb is to start with a wide net.
And as you mature your programs over time, you can start exploring different segmentation. I think the key to this, you mentioned it is personalization. If you do not have personalized messaging that is specific to that segment you're creating, then there is not an immediate value in segmenting or sort of siphoning off that audience. With the exception of a lot of companies do have certain budgets per, perhaps like segment different segments within your organization.
And sometimes you, for unit economics, you do need to separate those. So of course, every business is slightly different. But even if that is the case, let's say you work for a company and they have different budgets by geographies, if you're segmenting by geo, then you don't want to then again segment by job title. You want to try to lump all those as many decision maker job titles as possible within that segment if you're not just going completely global.
So go with the end logic instead of the or logic for this exercise. Go with the end logic, absolutely. Until you are ready to mature your program. There is a time and a place for segmentation.
There's a time and a place for ABM. But typically when you're just starting, especially if you haven't focused on demand generation before, bigger is better, especially to get those quick learnings. So once you know your estimated audience size, you want to understand how often you are willing to or how much you're willing to spend to reach that audience at a certain share of voice and a certain frequency. So sometimes you can do this two ways.
Usually what I like to do is I like to give my hypothetical budget, does it matter guess. And I like to plug in. I want to try to hit this audience. I want to reach at least 40% of them.
So in my experience, when you're running ads to a cold audience, you're never really going to get reach above that 40%. So don't ever assume you can hit 100% because within a 30-day period, it's not likely that every single person who has a profile, LinkedIn is going to log in. 40% is pretty much the maximum, the firing of all cylinders that I typically see for cold, really big audiences. So hypothetically, if I wanted to reach 40% of this audience and I want to reach them as frequently as possible without being annoying, is typically on LinkedIn a frequency of nine logos.
Hopefully that's spread out over roughly three ads. So each ad is getting about three frequencies, a frequency of three per ad. And on Facebook, you can go up to 11. It is a little bit more of a crowded platform.
So we do have a higher tolerance for frequency on that platform. But you want to reach 30% of this estimated total audience at least nine times. And that will give you kind of like a max monthly budget because you can plug in a desired CPM as well. Maybe you have historical data that already sort of tells you what an average CPM is.
You can plug that in or you can say, I don't really want to go above $50 CPMs or $100 CPMs. You can kind of get a feel for this max monthly budget just by doing some simple calculations. And obviously, if budget isn't an issue, then that's what you're going to roll with. How you're going to fund that segment, that's how you're going to go to market.
You're going to make sure you have at least three ads in there and you're really watching the performance of that. But a lot of times people have to scale back. And so you have to understand, all right, am I willing to maybe still reach 40% of that audience, but only at a frequency of six logos over 30 days. That will naturally sort of scale back your cost within that segment.
So it's really a push and pull between reach and frequency to understand how much money is hypothetically going to cost you to reach that audience over a period of 30 days. Can I be out being CPMs? It's an auction. Those are always fluctuating.
They're on the side of a little bit of a higher CPM than your average just to be safe. But sometimes you can experience some really great efficiencies and you might actually end up spending less than you think. So it's kind of like baseline how I go into prepping for this. Yeah, so you're laying the foundation here.
You're giving a great crash course to everyone in terms of just how to think about structuring your campaigns. What are the right metrics to be optimizing for in terms of getting your ads in front of people with a certain amount of times over the course of the month as not to be annoying. I think that that's fair. Now that we've got the foundation set, and let's say our ads are live, everything's running.
And we're now all of a sudden kind of arriving to that point one to two months in where people are saying, okay, you asked me to be patient and I haven't said anything for six weeks now, but here I am. I'm coming out and I want an update. And so we don't necessarily expect that our clients or people that were recommending these strategies were going to start seeing their demo volume explode and their pipelines and close one revenue. Everything's up and to the right.
This is still very much in that foundational phase. And so where do we go from here? What's the right way to start understanding if we are headed in the right direction? Are there leading KPIs we can be looking at at this point?
And if so, help walk me through what you think the right approach is there. Yeah. So that's why it's so key to go into these paid platforms. I did forget to mention quickly that Facebook doesn't give you a great estimation of audience size in the way that LinkedIn does.
So as a rule of thumb, I typically assume about 35%. If you're using a third party tool like metadata or clearbit, there's other tools out there or matched lists. Obviously, we never recommend running native targeting. I wouldn't begin to have an estimation there for audience size, but if you're using a third party tool, you can assume about 35% of what you found.
That's a really timely point of clarity there too, because I know that Facebook did release some new native targeting capabilities last week. And I don't know about you, but from what I gather, they're still predicated on people putting their job information into Facebook, which I can't tell you the last time I did it. If you go and look in there, I'm probably like, I don't know, waiting tables at a restaurant I worked at when I was 15 years old. So if that's what they're trying to target me on as for good luck with some of that new criteria, but I think that that's a great clarification there.
Yeah. So that's why laying out foundation and approaching the way that you budget for and plan creative for these strategies so that you have enough budget to reach your share of voice and enough budget to sustain the level of frequency that you're willing to have. That's why you want to do all that prep work up front, because now you have a story. So now you can say, all right, this was what I estimated was going to happen.
This is what's actually happening. So let's say I was expecting to reach 30% of my sales decision maker audience, but I'm only seeing 20% after about 30 days. Now I can dig into why is that? Oh, my CPMs were really high.
Okay, so this audience has a lot of competition right now with other brands. And that's why that's that's more high. So what I have to do is now make sure my organic strategy is complimenting my paid strategy so I can make up for some of the difference of the reach that I wasn't able to obtain from that paid channel. So you can start to have like more conversations about how to reach goals if they were missed from your original projections.
But it also gives you it doesn't have to necessarily be a bad thing, but it gives you the narrative that you want to tell your stakeholders, your sales partners, your leaders is that here's our audience. We reach this many people this amount in a 30 day period. Now let's dig into some of the actual demographics that LinkedIn shares with us. So this is where I love doing a call with my stakeholders or sales people where we're looking at the job titles that are actually getting impressions on the ads, clicking on the ads or engaging with the ads and we're having real time discussion.
Like, yes, we put in VP of sales, but somehow a marketing ops role snuck in there. And that's because LinkedIn is not exact. It's still an algorithm and it's going to make mistakes. So now I know that I need to negate marketing ops as a job title because I don't want to have wasted impression.
I don't have wasted exposure to an audience that's not a decision maker. So doing these sort of live demographics, and having conversations like, okay, we're seeing the manufacturing industry eating up a majority of the impressions. Is this an industry that we're prepared to sell into? Do we have enable material around it?
If we start generating a lot of demand in this industry, are we able to support that? Oh, actually, no, this isn't like a top industry priority for us. So maybe we negate that and exclude that from the campaign for the time being while we build up our enablement. But it's good to know that we, those people are on LinkedIn and they're engaging.
We've already seen the brand. Now we can have some conversations about how to be prepared for if we generate demand for that industry. Yeah, I well said. I think that those qualitative insights at this juncture, at this early juncture are critical.
And don't shy away from, like Alison's talking about here, something that she does with her clients where they're opening up some of the ads and looking at the engagements from people. Are the people that are liking, commenting, sharing? Are these people in our ICP looking at the demographic reporting? Again, is this the right target audience for us to be reaching?
And then one further, I think the firmographic makeup of the audience that you're reaching at that point. So I just walked through this exercise with a client maybe a week or so ago where we noticed that in the early goings, a large bulk of their impressions were being shown to some really, really large companies like Google and IBM. And while technically there is a fit there realistically, it's probably not going to happen for that particular company that Google is going to come inbound. And so when you start to get realistic about where a lot of your impressions are going, it can help you say, okay, maybe I want to exclude this company or this list of companies from my target audience so that the impressions aren't getting eaten up by the massive companies and all the employees that had some of these companies that might actually be a demographic, excuse me, a firmographic fit, but maybe just aren't exactly what we're going to be looking to spend our money on right now.
So yeah, I think it's not just a way to start looking at some of those leading indicators for success and are we headed in the right direction, but also a way to make sure that the campaigns that you've structured and set up are set up efficiently and are going to set you up for continued success in the future if you let these things kind of continue to run and of course with some ongoing management and optimization. So no, that's a great point. Just wanted to call out there. But back to you.
What else you got? And I think doing something like that. So a lot of people will actually try to predict what they want to exclude from the beginning. While I will always exclude things like my current company, any partners I have, current customers, current competitors, those are kind of table stakes.
I do try not to go crazy with negations until some of the data is flowing in just because I want to get a sense for who is actually active on the platform. It does also help you make some judgment calls on are these the only core platforms I should be focusing on or do I need to diversify into other communities and other channels. I think having a good, honest look, if you're non, if more influencers instead of your decision makers are really getting that impression share, it's like, that's fine. But now you kind of know, okay, this might be a channel that's more uses like a support, whereas now I need to really create a separate strategy for these decision makers who are clearly living in other platforms.
So don't go too crazy on the negations that upfront and instead have that real time feedback with your stakeholders and sales teams, I think they tend to get really interested and excited about providing their subject matter expertise on that topic. And it's a really good way to ensure that the linemen have good activity to do together. So I think like once that you're kind of talking through things like job titles, industries, geographies that are engaging and being shown the most impressions of your ads. The other thing I like to look at is the different types of engagement metrics that the platforms offer.
So there's two engagement metrics that I had totally slept on before having to leave this charge for multiple clients here at Irvine Labs. And in Facebook, it's the Save Engagement metric and on LinkedIn, it is the C-more. So both of those are really interesting to me because the Save on Facebook to me is an indication of somebody is going to use this information later. And that is a really strong signal of how to continue to create thought leadership content around the sort of the theme of that ad.
So if that ad was useful enough for somebody to save, then how can you build out more content and continue to educate in feeds so you get more saves on that topic. So that's one that I really like to sort of dig into and have some light assumptions about what that might mean. And then the on LinkedIn, I love the C-more because it includes other actions that people took on your ad other than clicks or likes or shares. And primarily it's composed of people clicking that C-more at the break of the post copy.
So you know, they'll only show like a line or two. And it's an indication of how many people are clicking C-more, which is another indication of like how well you were able to educate in the feed. So I think those are two really strong metrics to keep your eye on to continue to create a culture of utilizing paid advertising as a vessel for thought leadership and not so much like direct response, I have to get a demo. I have to, you know, convert someone on a debug.
It's not necessarily a performance metric, but it's something that I think marketers can use to continue to build and solidify their case. And it's something that you should highlight at the appropriate time, like probably not in a board meeting, but in other meetings when you're talking about creating more content or being more, you know, un-dated content, being more content-first content focused, I think those metrics can add a lot of support to other marketing initiatives. Yeah, I think that's a really important distinction there, right, about, you know, who is the right audience to be sharing some of this information with? Because I think there's going to be a large percentage of our listeners right now who are thinking of this for their own edification, right?
Okay, I'm running the strategy. What should I be looking at? But then there's the other element of like, what should I be socializing around? Because there's a lot of stakeholders that are waiting around with bated breadth to kind of see what's going to come up this demand creation experiment.
You know, we've got this marketer over here talking all kinds of crazy talk about no longer pumping money into Google and direct line attribution. And I don't really know about all these things. So, you know, we need to feed them with some metrics as well. And I do know that, you know, you had wanted to talk a little bit about like some website metrics.
And I think that because there are so many people around the company that have familiarity and eyes on the website, oftentimes they are a little bit, let's say, safer to put in front of some business leaders in terms of, you know, pointing to as a leading indicator for success. So what are some of the website metrics that you're typically looking at and how do you kind of, you know, unpack some of those? Yeah. So I think about like my narrative as a whole, it's kind of resting on like a school almost.
And the first leg is like, what am I seeing in platform? And we just talked about that. And the second leg is, what am I seeing in the website in terms of traffic or just time? The three that I really look at is time on site pages viewed, procession and bounce rate.
And then the third, which I'll touch on lightly before we wrap up is just what's happening in the CRM. So if we go back to sort of that second leg of website engagement, there's, it's really important to think about website analytics from a holistic level and not just specifically what's coming from a specific channel. Because if you remember, we may have some campaigns that are optimized for website traffic, but a majority of our budget is going to be going to those reach campaigns, which essentially will keep people in the feed. And you're not likely to see a huge correlation between investment and web traffic if a large portion of your budget is going to reach.
So when you look at website traffic, you want to look at, of course, your platform referrals. So Facebook, LinkedIn, Instagram, other, any other Google AdWords, anything else that you're running, you do want to look at that. But then you also want to include organic direct. And then I like to sort of lump organic direct and paid brand into paid search branded, sorry, into like its own category.
And I've done some LinkedIn posting on this. This isn't really anything revolutionary, but it's a really great way to see like, are people coming to your site organically, directly clicking on your branded ads, you have to really be able to make that connection that that is a result of what you've been doing in the paid media feeds. That is a very strong correlation. It's something we see across our entire book of business with our customers.
That is something that is reasonable and we should feel confident in presenting those metrics as a sign of success as a leading indicator that we are growing traffic from those channels. And then you can start observing what are they doing on your site? How long are they? They staying?
How many pages are they viewing? What is the bounce rate over time? And that really starts to show like, are you attracting more loyal and interested people to your website? What are they looking at?
What can you do more of to continue to build off of that momentum? Yeah. And I think that the metrics you're talking about kind of, you know, almost aggregating together there is such a better viewpoint than let's just say like site visitors or, you know, user sessions because what we're talking about doing, you know, holistically is creating a lot of upfront strategy and targeting to ensure that we're driving the right people to our site. And so based on what was done historically, those things are going to look different from company to company, you might find that your actual website traffic is down.
But based on the metrics that you're recommending everyone look at, that is a much cleaner view to understand are we driving the right traffic to our site? And are those people ultimately getting some type of value that they're looking for when they landed on the site? As compared to just the role number, okay, we saw X percentage more or less than the last month. And so, you know, we know that our demand creation efforts are not working.
I've made that mistake in the past. And, you know, I hope that we can kind of talk our audience here through the support so that they don't make the same mistake that I did because, yeah, I think that those numbers can be a little bit deceiving. And so, you know, I think that's what we're talking about. It's a much better, it paints a much cleaner picture of, you know, are we driving the ICP traffic to the site?
And if we continue to do that in time, we expect that that's when the conversions start to lift. You know, if we just continue to get the right people landing on our site, continuing to absorb information, get value, then those are the people that we want to raise in their hands, not just the higher volume of people or junk leads that might come in otherwise. Absolutely. And, you know, even as we're talking here, even in my head, I'm like, man, this is just it sounds so simple.
And it really is. And I think that's where things actually go wrong is when we're trying to bring in too much data or tell too deep of a story, if you focus on to start at least just nailing these metrics, nailing the understanding of how to find this information and how to share it internally and how to make decisions off of this information, then you can, you know, continue to mature and make your strategies more complex and more intricate. But to start, like it really is something there is something freeing and having the ability to just approach it from a very simplistic standpoint. And I think that's what, you know, just makes me so happy to work with my clients because they're all very much bought into like, let's just bring it back to what we know works and continue to grow and get better from there.
Yeah. And I think, you know, for those of you out there that might have a little bit more of a difficult audience that might not be so bought in, same thing applies, simple as better. You don't want to overwhelm those people with metrics and data. Thinking that, you know, more data is always better.
That's not always the case. Instead, the right data is better. And ensuring that, you know, you've got some of these different indicators here, whether it be the qualitative indicators that come from looking at, you know, the people that are engaging with your ads, you know, who a majority of those impressions are going to, you know, are those, those same people, are those same, you know, cohorts of your audience, are they the ones that are coming to your site and sticking around and ideally, you know, requesting demos, that's what we're looking for here. We don't just want the, you know, the all up numbers to be increasing.
Although, you know, that can suggest that we might be on the right path, could also quickly lead us astray. And so I think you've done a great job kind of summarizing some of the different approaches here for ensuring success at the start of a campaign as you're building it and structuring it, but then also helping the audience understand what some of those leading indicators that they should be looking at in the early days are. So with that, any other words of wisdom or actionable takeaways you want to share with the audience, your Allison? Yeah, I'll wrap up just with that sort of third leg that I mentioned.
So obviously early on in the process, it's going to be difficult to see a lot of correlation directly in your CRM, but there are some things that you can start to look at to just make sure that you're always bringing in that true business performance level of reporting to your success within your demand creation program. And I think, first of all, we've got a lot of podcasts on time and date stamping in your CRM. Before you do any sort of demand creation, really try to get with your sales ops team, your rev ops team and make sure that you're tracking things effectively in your CRM. Go listen to some of those podcasts, but assuming you've got a really nice clean salesforce setup, start looking at form submissions, high intent hand raisers that come in.
Let's say you start a demand creation program in September, start looking at that as a cohort. What's happening to those people? How quickly are they moving from stage to stage? What are the job titles of those hand raisers in comparison to cohorts from months past?
Do we see more job titles? Even if it's just a few and far between to start, but do we see any sort of positive correlation between what we're targeting the platforms and what's coming into our CRM that month? You can also kind of loosely look at any self-reported attribution that they may have filled out on the form. And I think even in the early days, you're not going to see a flood of, oh, I saw you on LinkedIn, I saw you on Facebook, but you might have one or two that's week through that month.
And so that's another indicator that you can use from your CRM data. So definitely to sort of orient yourself on CRM metrics, try starting with just the cohort of hand raisers that you earned in that first month of your sort of your new strategy shift and see if there's anything new or interesting that's happening within that group. And I think that will add that level of business performance that it might feel like that's missing if you're just focusing on platform or website. This is a good way to sort of tie in the CRM and set the stage for how you'll actually be able to be focused more on the CRM in the next four months to six months is probably when I switched to mainly CRM reporting.
So, yeah, that's, honestly, that's exactly where my head was going. I think we might be doing an episode on cohort reporting coming up because there's definitely a lot to talk through there. And it's another concept that I was a little bit familiar with before I started working at Refine Labs, but then met a bunch of people who know a whole lot more than I did and it really opened up my eyes. So I think you might be teeing up our next episode, Allison.
So, yeah, let's definitely noodle on that a little bit. But I think that about wraps it up for today. So thank you everyone for listening. This will be the first of many episodes with Allison and I.
So hope you all enjoyed it as much as we enjoyed it. Yeah, thanks everyone.